250+ Directory of Influential Women Advancing AI in 2020

With a large majority of events and networking opportunities moving online, we thought there was no better time than now to find new Women in STEM to follow and connect with (at least over the web for now). Therefore, we took our Women in AI blog to the next level, creating our first Women in AI directory! Make sure to click through to their Linkedin accounts below and follow them for updates on their work!

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Fei-Fei Li, Associate Professor CS Dept, Stanford

Fei-Fei is an Associate Professor in the Computer Science Dept at Stanford alongside being Director of the Stanford Artificial Intelligence Lab and the Stanford Vision Lab, where she works with the most brilliant students and colleagues worldwide to build smart algorithms that enable computers and robots to see and think, as well as to conduct cognitive and neuroimaging experiments to discover how brains work. She received Ph.D. from Caltech.

Timnit Gebru, Research Scientist, Google

Timnit is a Research Scientist in the Ethical AI team at Google and just finished her postdoc in the Fairness Accountability Transparency and Ethics (FATE) group at Microsoft Research, New York. Prior to that, she was a PhD student in the Stanford Artificial Intelligence Laboratory, studying computer vision under Fei-Fei Li. Her main research interest is in data mining large-scale, publicly available images to gain sociological insight, and working on computer vision problems that arise as a result, including fine-grained image recognition, scalable annotation of images, and domain adaptation. She is currently studying the ethical considerations underlying any data mining project, and methods of auditing and mitigating bias in sociotechnical systems. The New York Times, MIT Tech Review and others have recently covered her work. As a cofounder of the group Black in AI, she works to both increase diversity in the field and reduce the negative impacts of racial bias in training data used for human-centric machine learning models.

Chelsea Finn, Research Scientist, Google Brain

Chelsea is a research scientist at Google Brain and post-doctoral scholar at Berkeley AI Research. Starting in 2019, she will join the faculty in CS at Stanford University. She is interested in how learning algorithms can enable machines to acquire general notions of intelligence, allowing them to autonomously learn a variety of complex sensorimotor skills in real-world settings. She received her PhD in CS at UC Berkeley in 2018 and her Bachelors in EECS at MIT in 2014.

Tamanna Haque, Senior Data Scientist, Jaguar Land Rover

Tamanna is a Senior Data Scientist at Jaguar Land Rover, using data science and the connected car to unlock business value and shape cars of the future. Tamanna holds previous data science and analytics experience within retail and financial services and is particularly interested in the commercial application of AI to deliver value, continually advancing through tech to enable modern, quick and optimal solutions to her stakeholders and customers. Tamanna has shaped a new team at JLR and have spoken about AI and analytics to industry experts, students, and women's leadership and diversity groups.

Alison Darcy, CEO and Founder, Woebot Labs

Alison is the CEO and Founder of Woebot Labs Inc. a company that aims to make the best psychological tools radically accessible for everyone. She created Woebot, a friendly AI-powered chatbot that delivers cognitive behavior therapy at scale. A clinical research psychologist, Alison was Faculty in Psychiatry and Behavioral Sciences at the Stanford School of Medicine for a decade where she developed digital health interventions for young people. With both a technical and scientific background, Alison works at the intersection of mental health and technology.

Joy Buolamwini, Founder, Algorithmic Justice League

Joy is a poet of code on a mission to show compassion through computation. She is a Rhodes Scholar, Fulbright Fellow, Google Anita Borg Scholar, Astronaut Scholar, A Stamps President's Scholar and Carter Center technical consultant recognized as a distinguished volunteer. She holds a master's degree in Learning and Technology from Oxford University and a bachelor's degree in Computer Science from the Georgia Institute of Technology. Her spoken word visual audit "AI, Ain't I A Woman?" which shows AI failures on the faces of iconic women like Oprah Winfrey, Michelle Obama, and Serena Williams as well as the Coded Gaze short have been part of exhibitions ranging from the Museum of Fine Arts, Boston to the Barbican Centre, UK.

Danah Boyd, Principal Researcher, Microsoft Research

Dhana is a Principal Researcher at Microsoft Research and the founder of Data & Society. She’s a Visiting Professor at New York University's Interactive Telecommunications Program, and an academic and a scholar with research examining the intersection between technology and society. For over a decade, her research focused on how young people use social media as part of their everyday practices. More recently, Danah has turned to focus on understanding how contemporary social inequities relate to technology and society more generally. She’s collaborating with researchers working on topics like media manipulation, the future of work, fairness and accountability in machine learning, combating bias in data, and the cultural dynamics surrounding artificial intelligence.

Kate Crawford, Co-founder, AI Now Institute; Distinguished Research Professor, NYU

Kate is a leading researcher, academic and author who has spent the last decade studying the social implications of data systems, machine learning and artificial intelligence. She is a Distinguished Research Professor at New York University, a Principal Researcher at Microsoft Research New York, and a Visiting Professor at the MIT Media Lab. Her recent publications address data bias and fairness, social impacts of artificial intelligence, predictive analytics and due process, and algorithmic accountability and transparency.

Aleatha Parker-Wood, Machine Learning and Algorithmic Privacy at Humu

Aleatha leads a team of Ph.D. researchers dedicated to protecting you and your data, using state-of-the-art ML and security expertise. In addition to research, Aleatha also teaches and mentors helping bring up the next generation of scientists and engineers. Feel free to connect if you're interested in networking or mentoring. Alethea also Co-created ScAINet, an industry-academic conference at the intersection of ML and security, with Symantec as founding sponsor, building Symantec’s ML brand

Yinyin Liu, Co-Founder & CTO, XOKind

Yinyin co-founded XOKind in October 2019, a company with a mission of simplifying human planning and decision making by distilling the world's information, and launching their first product in the travel and leisure space. Their goal is to bring AI technology directly to users with beautiful, human-centered design, and to build products that enable users to experience and accomplish more while maintaining a strong respect for user privacy. Skilled in machine learning algorithms and research, data science, software engineering and customer collaborations, she also has a Ph.D focused on Machine Learning.

Julia Hu, CEO, Cofounder at Lark Health

Having been too often sleep deprived and dropping off exercise and diet regimens, Julia's goal is to make people happier and healthier as the CEO of lark technologies. Named Top 10 Most Innovative CE Companies in the World by Fast Company, lark is a mobile and wireless technology company that uses behavior change to personally coach people to feel great. A serial entrepreneur, she has focused on growing early-stage startups in the consumer products and cleantech space. Prior to lark, she ran global startup incubator Clean Tech Open, her own green buildings startup, and worked in China to build consumer electronics with D.light Design.

Claire Delaunay, VP Engineering, NVIDIA

Claire is vice president of engineering at NVIDIA, where she is responsible for the Isaac robotics initiative and leads a team to bring Isaac to market for roboticists and developers around the world. Prior to joining NVIDIA, Delaunay was the director of engineering at Uber, after it acquired Otto, the startup she co-founded. She was also the robotics program lead at Google and founded two companies, Botiful and Robotics Valley. Claire has 15 years of experience in robotics and autonomous vehicles leading teams ranging from startups and research labs to Fortune 500 companies. Claire holds a Master of Science in computer engineering from École Privée des Sciences Informatiques (EPSI).

Jana Eggers, CEO, Nara Logics

CEO of Nara Logics, a neuroscience-inspired AI company, providing a platform for recommendations and decision support. Her career has taken her from 3-person business beginnings to 50,000-person enterprises. She opened the European logistics software offices as part of American Airlines, dove into the internet in 1996 at Lycos, founded Intuit’s corporate Innovation Lab, helped define mass customization at Spreadshirt, and researched conducting polymers at Los Alamos National Laboratory.

Carla P. Gomes, Director, Institute for Computational Sustainability at Cornell University

A professor of Computer Science, Carla’s research has covered several areas in AI, including complete randomized search methods, optimization, and machine learning. Carla is also the founding director of the Institute for Computational Sustainability and is noted for her pioneering work in developing computational methods to address challenges in sustainability. In 2007 Carla was elected a Fellow of the Association for the Advancement of Artificial Intelligence "for significant contributions to constraint reasoning and the integration of techniques from artificial intelligence, constraint programming, and operations research". She obtained a PhD. in computer science in the area of artificial intelligence and operations research from the University of Edinburgh. She also holds an M.Sc. in applied mathematics from the University of Lisbon.

Clara Durodie, Executive Chair, Cognitive Finance Group

Clara Durodié is a leading  technology strategist specializing in applied artificial intelligence (AI) in financial services. Clara’s work is focused on trusted AI for business growth and profitability. She is internationally recognized for her expertise, advising Boards of leading financial institutions, investment funds, think-tanks, and governments. She also mentors AI companies on funding and growth strategy. Clara is a frequent speaker at leading conferences and guest lecturer at universities such as Harvard, MIT, and Oxford. Clara recently published “Decoding AI in Financial Services”. This is the first book that examines how AI impacts corporate governance, business strategy and profitability in financial services. With excellent industry reviews, the book is regarded as the essential reading for corporate Boards. Clara is based in London and is  the founder of the pre-eminent advisory, Cognitive Finance Group, specialists in the design, selection, and implementation of trusted AI solutions for financial services.

Rumman Chowdhury, Responsible AI Lead, Accenture

Rumman comes from a quantitative social science background, and is a practicing data scientist. As a Senior Principal at Accenture, she works on cutting-edge applications of AI and is the Global Lead for Responsible AI. Rumman also leads client solutions on ethical AI design and implementation, working with organisations such as the IEEE and World Economic Forum. She has been named a fellow of the Royal Society for the Arts and is one of BBC’s 100 most influential women of 2017.

Rosalind W. Picard, Professor, MIT Media Lab, Co-founder and Chief Scientist Empatica, Co-founder Affectiva

In 1991 Rosalind joined MIT as a professor, and during her career there has founded and is director of the Affective Computing Research Group, as well as co-director of the Media Lab's Advancing Wellbeing Initiative. Picard also co-founded Affectiva, where she worked as Chief Scientist until 2013. In 2014 Picard then co-founded Empatica, where she is currently Chief Scientist and Chairman. Empatica has combined machine learning with wearable sensors to create 2 wearable healthcare products. Throughout her career Rosalind has been awarded with various best paper prizes and authored the book Affective Computing.

Hanna Wallach, Senior Researcher, Microsoft Research

Hanna’s research is in the interdisciplinary field of computational social science, and has developed machine learning and natural language processing methods for analyzing the structure, content, and dynamics of social processes. Hanna’s work has been recognised throughout the industry, having won the best paper award at the Artificial Intelligence and Statistics conference in 2010, and named as one of Glamour magazine’s “35 Women Under 35 Who Are Changing the Tech Industry” in 2014. Hanna has also worked to increase diversity and has worked for over a decade to address the underrepresentation of women in computing, having co-founded two projects to increase women’s involvement in free and open source software development - the Debian Women Project and the GNOME Outreach Program for Women.

Beena Ammanath, AI Managing Director, Deloitte

Global VP - Artificial Intelligence, Data and Innovation, Hewlett Packard Enterprise
Prior to her current role at Hewlett Packard Enterprise, Beena was the Vice President of Data Science and Innovation at GE, working to transform the company into a digital industrial company leveraging data, analytics and AI. Beena has shared her expertise in technology as a board advisor in various Artificial Intelligence companies, including Predii, which uses patented Machine Learning technology to provide ‘Repair Intelligence”. Beena has also been leading efforts to increase diversity in technology, having been the Board Director of ChickTech, a non-profit dedicated to increasing the number of women and girls pursuing technology-based careers, and retaining women already in STEM workforces. In 2017 Beena founded nonprofit organization Humans For AI, which focuses on increasing diversity in technology.

Carol Reiley, Founder, Stealth AI Healthcare Startup

Carol has eight technical patents, and is the author of more than a dozen papers published in various scientific conference proceedings, refereed journals and conferences, with a research focus on ‘intelligent robotic systems that can aid humans in performing skillful tasks more effectively.’ Carol has previously served on the various boards, including the IEEE Robotics and Automation Society and JHU Engineering Diversity Council. Carol has built up a large collection of awards over her career, and has been listed in the Silicon Valley Business Journal Most Influential list in 2017 and Inc Magazine’s Most Innovative Women Entrepreneurs.

Cynthia Breazeal, Founder & Chief Scientist at Jibo, Inc.

Cynthia is an Associate Professor of Media Arts and Sciences at the Massachusetts Institute of Technology where she founded and directs the Personal Robots Group at the Media Lab. She is also founder and Chief Scientist of Jibo, Inc. She is a pioneer of Social Robotics and Human Robot Interaction. She authored the book Designing Sociable Robots, and she has published over 100 peer-reviewed articles in journals and conferences on the topics of Autonomous Robotics, Artificial Intelligence, Human Robot Interaction, and Robot Learning. She serves on several editorial boards in the areas of autonomous robots, affective computing, entertainment technology and multi-agent systems. She is also an Overseer at the Museum of Science, Boston.

Rana el Kaliouby, Founder, Affectiva

Computer scientist, technologist, entrepreneur and business leader, Dr. el Kaliouby believes that “humanizing technology gives us a golden opportunity to re-imagine how we connect with machines, and, therefore, how we connect with each other.” Co-founder and CEO of Affectiva, the pioneer of Emotion AI, she invented the company’s award-winning emotion recognition technology. The Emotion AI platform combines facial expression and tone of voice to infer how a person is feeling, using deep learning and the world’s largest emotion data repository of more than five million faces, analyzed from 75 countries. Rana has today also released her book, Girl Decoded, which you can read more on here.

Daniela Rus, Director, CSAIL, Professor at MIT

Daniela Rus is the Director of CSAIL at MIT. She serves as the Director of the Toyota-CSAIL Joint Research Center and is a member of the science advisory board of the Toyota Research Institute. Rus’s research interests are in robotics, mobile computing, and data science. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, and a member of the National Academy of Engineering, and the American Academy for Arts and Science. She earned her PhD in Computer Science from Cornell University.

Daphne Koller, Founder and CEO, insitro

Daphne is the Chief Computing Officer at Calico Labs, an Alphabet (Google) company that is using advanced technology to understand aging and design interventions that help people lead longer, healthier lives. She is also the Co-Chair of the Board and Co-Founder of Coursera, the largest platform for massive open online courses (MOOCs). Previously, she was the Rajeev Motwani Professor of Computer Science at Stanford University, where she served on the faculty for 18 years. In January Daphne become the founder and CEO of Insitro, incorporating machine learning into drug discovery. She is the author of over 200-refereed publications appearing in venues such as Science, Cell, and Nature Genetics.

Devi Parikh, Research Scientist, Facebook

Devi Parikh is an Assistant Professor in the School of Interactive Computing at Georgia Tech, as well a Research Scientist at Facebook AI Research (FAIR). With interests in computer vision and visual recognition problems, her recent work involves exploring problems at the intersection of vision and language, and leveraging human-machine collaboration for building smarter machines. She received her Ph.D. from Carnegie Mellon University in 2009. Devi’s contributions in the field have been widely recognised by the community, and she is a recipient of numerous awards, including the NSF CAREER award, and an IJCAI Computers and Thought award. Devi has also featured in a Forbes' list of 20 "Incredible Women Advancing A.I. Research."

Meredith Whittaker, Co-Founder and Co-Director of the AI Now Institute

The AI Now Institute at NYU is an interdisciplinary research center dedicated to understanding the social implications of artificial intelligence. AI Now's work focuses on four core domains which are rights and liberties; bias and inclusion; labor and automation; and critical infrastructure and safety. Meredith also leads Google's Open Research Group which collaborates with open source and academic communities, and the Google Measurement Lab. Meredith is also a Research Scientist at New York University.

Sarah Bird, Principal Program Manager, Microsoft

Sarah received her PhD in Computer Science at the University of California, Berkeley. Now at Facebook, she leads strategic projects to accelerate the adoption and impact of AI research in products. Before joining Facebook, Sarah was an AI systems researcher at Microsoft Research NYC and a technical advisor to Microsoft’s Data Group. Her research includes reinforcement learning systems and AI ethics. Sarah is also one of the researchers behind Microsoft’s Decision Service, one of the first general-purpose reinforcement-learning style cloud systems released.

Tara Sainath, Senior Staff Research Scientist, Google

Tara received her PhD in Electrical Engineering and Computer Science from MIT in 2009, with a focus in acoustic modeling for noise robust speech recognition. After her PhD, Tara spent 5 years at the Speech and Language Algorithms group at IBM T.J. Watson Research Center, before joining Google Research. In addition, Tara is a staff reporter for the IEEE Speech and Language Processing Technical Committee (SLTC) Newsletter. Her research interests are mainly in acoustic modeling, including deep neural networks, sparse representations and adaptation methods.

Hillary Mason, Data Scientist in Residence, Accel Partners

Hillary is a VP of Research at Cloudera. She is also the Founder of Fast Forward Labs, a machine intelligence research company, and was the Data Scientist in Residence at Accel and the Chief Scientist at bitly. Hilary is currently working on something new, so keep your eyes peeled....

Raia Hadsell, Senior Research Scientist, DeepMind

Raia Hadsell, a senior research scientist at DeepMind, has worked on deep learning and robotics problems for over 10 years. Her thesis on Vision for Mobile Robots won the Best Dissertation award from New York University, and was followed by a post-doc at Carnegie Mellon's Robotics Institute. Raia then worked as a senior scientist and tech manager at SRI International. Raia joined DeepMind in 2014, where she leads a research team studying robot navigation and lifelong learning.

Lucia Specia, Professor of Language Engineering, Sheffield University

Dr. Lucia Specia is Professor of Natural Language Processing at Imperial College London (since 2018) and the University of Sheffield (since 2012). Her research focuses on various aspects of data-driven approaches to language processing, with a particular interest in multimodal and multilingual context models and work at the intersection of language and vision. Her work has been applied to various tasks such as machine translation, image captioning, quality estimation and text adaptation. She is the recipient of the MultiMT ERC Starting Grant on Multimodal Machine Translation (2016-2021) and is currently involved in other funded research projects on machine translation (H2020 Bergamot, APE-QUEST), multilingual video captioning (British Council MMVC) and text adaptation (H2020 SIMPATICO). She was previously involved in 10+ funded research projects and has completed the supervision of 11 PhD students.

Mounia Lalmas-Roelleke, Head of Tech Research, Spotify

Mounia is Head of Tech Research in Personalization. Mounia also holds an honorary professorship at University College London. Her work focuses on studying user engagement in areas such as native advertising, digital media, social media, search, and now music. She has graduated 10+ PhD students; supervised 20+ MSc students; managed 25+ scientists, post-docs and interns and examined 25+ PhD, MSc, HDR worldwide. She currently holds senior scholarship roles including programme and thematic chairs at major conferences on web, search, and data mining.

Katja Hofmann, Principal Researcher, Microsoft

Katja is a Principal Researcher at the Machine Intelligence and Perception group at Microsoft Research Cambridge. Her research focuses on reinforcement learning with applications in video games, as she believes that games will drive a transformation of how people interact with AI technology. She is the research lead of Project Malmo, which uses the popular game Minecraft as an experimentation platform for developing intelligent technology. Her long-term goal is to develop AI systems that learn to collaborate with people, to empower their users and help solve complex real-world problems.

Verena Rieser, Professor in Conversational AI, Heriot-Watt University

The ongoing theme of Verena's research is to develop intelligent conversational systems, such as chatbots and virtual personal assistants, where she researches machine learning techniques to automatically build these systems from data. She has authored over 100 peer-reviewed papers in this area. For example, Verena was one of the first researchers to introduce Reinforcement Learning to optimise task-based dialogues. For the past 2 years, Verena's team was the only UK university to enter the finals of the prestigious Amazon Alexa Challenge, which aims to build open-domain chatbots.

Kriti Sharma, Founder, AI for Good UK

Kriti is an AI expert, business executive and humanitarian. In 2017, Kriti was named in Forbes magazine's 30 Under 30. She was appointed as United Nations Young Leader for the SDGs in 2018. Kriti is currently Vice President of Gfk & Founder of AI for Good UK. She has been leading efforts to create more diverse and ethical artificial intelligence and “embracing botness” which means that artificial intelligence does not have to pretend to be human, instead it needs to be useful. Jeremy Wright, Secretary of State for Digital, appointed Sharma as an adviser on AI, Data Ethics and Innovation in 2018.

Danielle Belgrave, Principal Researcher, Microsoft

Danielle’s research revolves around integrating expert scientific knowledge to develop customized probabilistic graphical models to understand the progression of disease symptoms and comorbidities. Her previous research has focused on the development of machine learning models in the context of asthma, but this is generalizable to profiling patients with greater accuracy to allow us to move towards more personalized disease management strategies. Danielle’s University research website can be found here.

Xiaolan Sha, Director of Data Science, Carlson Wagonlit Travel

Xiaolan graduated from Southeast University in 2005 with a Bachelor in Software engineering, before going on to her masters in communications and computer security at Telecom Paris. After interning at Ericsson, she quickly moved into her first role as a software engineer at Amadeus before starting her PhD with EURECOM. Having worked as both a data scientist, then lead Data Scientist at Sky, Xiaolan is now Principal Data Scientist at CWT with a special focus on AI.

Maria Liakata, Associate Professor, University of Warwick

Maria is currently lecturing, supervising students, leading research in natural language processing and applications at University of Warwick. She has a DPhil from the University of Oxford on learning pragmatic knowledge from text and her research interests include text mining, natural language processing (NLP), related social and biomedical applications, analysis of multi-modal and heterogeneous data (text from various sources such as social media, sensor data, images) and biological text mining. Her work has contributed to advances in knowledge discovery from corpora, automation of scientific experimentation and automatic extraction of information from the scientific literature. She has published widely both in NLP and interdisciplinary venues.

Chanuki Illushka Seresinhe, Lead Data Scientist, Popsa

Chanuki is a visiting researcher at the Alan Turing Institute, the UK's national institute for data science and artificial intelligence. She also works commercially, currently as the Lead Data Scientist at Popsa and previously a Senior Data Scientist at Channel4. Chanuki's research entails using big online datasets and deep learning to understand how the aesthetics of the environment influences human wellbeing. For example, how might we design our future cities to be conducive to our wellbeing? Her research has been featured in the press worldwide including the Economist, Wired, The Times, BBC, Spiegel Online, Guardian, Telegraph and Scientific American. She received her PhD from the Data Science Lab, Warwick Business School, University of Warwick.

Valentina Salvatelli, Senior Data Scientist, NASA Frontier Development Lab

Valentina is a data scientist with commercial and research experience in machine learning. PhD in Physics with focus on Bayesian statistics and computational methods. Velentina has been at IQVIA for nearly three years, honing her skills already collected in Python, Pyspark, SQL, Cloud Computing, Deep Learning ML and more. Valentina was also issues with a Deep Learning Specialisation credential from deeplearning.ai in April last year.

Marzieh Saeidi, Research Scientist, Facebook

Marzieh has a degree in software engineering from Ferdowsi University in Iran and then Kings College London. After working as a software engineer in finance sector for over 4 years, she did a PhD in Natural Language Processing under the supervision of Sebastian Riedel at UCL. Her PhD topic was on predicting attributes of city neighbourhoods using social media text. She then worked as a research scientist for Bloomsbury AI doing research on creating an AI assistant specifically to answer questions from text containing rules such as legislations and compliance. Currently, Marzieh works as a research scientist at Facebook on integrity issues with a focus on identifying false claims.

Natalia Konstantinova, Architecture Lead in AI, BP

Natalia is a great enthusiast with over 10 years' experience in the application of Natural Language Processing, Artificial Intelligence, IT and machine learning technologies to real world problems. She got her PhD from the University of Wolverhampton and worked in various fields such as machine translation, ontologies, information extraction and currently dialogue systems and chat bots. She is currently Architecture Lead in AI at BP, focussed on designing and managing AI solution patterns.

Kallirroi Dogani, Machine Learning Engineer, Facebook

Having moved to Facebook as a ML Engineer earlier this year, Karrirroi had previously spent nearly two years at ASOS and Tractable before that. Karrirroi holds a Master’s degree in Artificial Intelligence from the University of Leuven and has previously applied her skills as a Data Scientist in AI & tech startups.

Noor Shaker, Founder & CEO, Glamorous AI

Before founding Glamorous AI, Noor was an assistant professor at Aalborg University in Copenhagen working on different aspects of machine learning with special interest in generative models. She is the main author of the book “Procedural Content Generation in Games” which covers many of the generative methods. She has more than 50 publications and 1000+ citations. She serves as the chair of the IEEE games technical committee and she is an active member in the games research society participating in organizing conferences, workshops and tasks forces. She has won a number of awards for her research including the IEEE Transactions on Computational Intelligence and AI in Games Outstanding Paper Award.

Marta Garnelo, Research Scientist, DeepMind

Marta is a research scientist at DeepMind and completed her PhD at Imperial College London under the supervision of Prof Murray Shanahan. Her research interests include deep generative models and reinforcement learning, in particular finding meaningful representations using the former to improve the latter.

Feryal Behbahani, Research Scientist, DeepMind

Feryal has received her PhD from the Department of Computing at Imperial College London where she studied Computational Neuroscience and Machine Learning at the Brain and Behaviour Lab. Her main research focused on investigating the underlying algorithms employed by the human brain for object representation and inference. She has previously obtained her MSc in Artificial Intelligence with distinction at Imperial College London. She has also worked on projects building machine learning solutions as part of a technology consultancy start-up that she co-founded. Currently, she is a visiting postdoctoral researcher at Imperial College London where she works on transfer learning and deep reinforcement learning.

Antonia Creswell, PhD Candidate, Imperial College

Antonia is a PhD candidate at Imperial College London, in the Bio-Inspired Computer Vision Group. Her research focuses on unsupervised learning and generative models. She received her masters in Biomedical Engineering from Imperial College London with an exchange year at the University of California, Davis. Antonia has interned at DeepMind, Twitter (Magic Pony), Cortexica and UNMADE.

Elena Kochkina, PhD Candidate, University of Warwick

Elena’s research is focused on Rumour Stance and Veracity Classification in social media conversations. Veracity classification means a task of identifying whether a given conversation discusses a True, False or Unverified rumour. Stance classification implies determining the attitude of responses discussing a rumour towards its veracity as either Supporting, Denying, Questioning or Commenting. In her work Elena studies the relations between these tasks, as patterns of support and denial can be indicative of the final veracity label. As the input data is in the form of conversations discussing rumours, she utilises the conversation structure to enhance predictive models. Elena works with deep learning models as this approach allows flexible architectures and has benefits of representation learning. Recurrent and recursive neural networks allow to model time sequences and/or conversation tree-like structures.

Noura Al Moubayed, Assistant Professor, Computer Science, Durham University

Noura applied her expertise on a variety of applications domains including: anomaly detection in household energy consumption data, social media data analysis, documents classification and clustering, prediction of perceived personality traits from facial images, channel selection for brain computer interfaces, cancer chemotherapy optimisation and automatic testing of car braking systems.

Huma Lodhi, Data Scientist, BP

Huma is a meticulous and seasoned professional with over 15 years of experience in Artificial Intelligence and Machine Learning. Wide ranging expertise in Data Science and advanced analytics with valuable hands on full project life cycle experience for industries such as finance, insurance, health care, pharmaceutical, and publishing. In-depth knowledge of modern Machine Learning techniques including deep learning approaches, kernel methods, statistical relational learning algorithms and ensemble methods. Accomplished industry expert and academic researcher with proven skills in developing Artificial Intelligence methodologies and designing scalable systems.

Laura Douglas, CEO & Co-Founder, MyLevels

Laura founded myLevels to help people understand their bodies and see how different foods affect them. Using AI to process biometric data and really understand what food is doing to you. Previously, she was a Machine Learning Research Scientist at Babylon Health where she focused on probabilistic graphical models, approximate inference andBayesian learning. She presented a paper at the Advances in Approximate Bayesian Inference workshop at NIPS 2017. MyLevels use continuous glucose sensors to show people their real time sugar level responses, and then analyse this data to show people what the best food options are for them.

Catherine Breslin, Director, Solutions Architect, Colbat Speech and Language

Catherine is a Machine Learning Scientist and manager, advising companies and builds high performing voice and language technology for their specific problems, including Iprova and Omnibot. Since completing her PhD at the University of Cambridge, she has commercial and academic experience of automatic speech recognition, natural language understanding and human-computer dialogue systems. Catherine is excited by the application of research to real-world problems.

Betty Schirrmeister, Senior Data Scientist, Royal Mail

Betty is an enthusiastic, fast-learning, experienced scientist, with excellent communication skills. Following an exciting Academic career, she decided to move to professional Data Science, looking for ambitious challenges, eager to combine her experience in data munging, analytics and visualization with her entrepreneurial spirit, to help making data-driven actionable decisions for innovative businesses. (https://schirrmeister.wordpress.com/).She has led and supported several ambitious data science projects including several predictive analytics projects for Royal Mail.

Mariarosaria Taddeo, Research Fellow, Oxford Internet Institute & Digital Ethics Lab

Dr Mariarosaria Taddeo is Research Fellow at the at the Oxford Internet Institute, University of Oxford, where she is the Deputy Director of the Digital Ethics Lab, and is Faculty Fellow at the Alan Turing Institute. Her recent work focuses mainly on the ethical analysis of cyber security practices, cyber conflicts, and ethics of data science. Her area of expertise is Philosophy and Ethics of Information, although she has worked on issues concerning Epistemology, Logic, and Philosophy of AI. Dr Taddeo has been awarded The Simon Award for Outstanding Research in Computing and Philosophy in recognition of the scholarly significance of her two articles: An Information-Based Solution for the Puzzle of Testimony and Trust (Social Epistemology, Springer) and Modelling Trust in Artificial Agents, a First Step toward the Analysis of e- Trust (Minds & Machines, Springer).

Caryn Tan, Digital Strategy Manager, Accenture

Caryn is an Analytics Strategist operating at the intersection of applied analytics and law/ethics. She advises senior decision-makers on analytics strategy, target operating model and analytics business case and manages technical teams to operationalise and realise these strategies. She also manages Accenture’s Responsible AI practice in the UK where she helps clients confidently deploy responsible AI models with technical, organisational, governance and brand considerations. This involves working with multidisciplinary teams, industry experts and academic institutes. Caryn graduated from London Business School and holds a law degree from BPP University, both as a merit scholar.

Flora Tasse, Head of AI Research, Streem

Flora is Head of AI Research at Streem, Flora currently applies her research skills at Streem where we are making the phone's camera intelligent. Acquired by Streem, her founded start-up, Selerio, was building AI agents that could understand images/videos and augment them with relevant interactive objects. Flora also holds the 2014 Google European Doctoral Fellowship in Computer Graphics for her work on retrieving 3D models using images and sketches. Selerio, a Cambridge spin-out, builds on this work to provide developers with live 3D reconstruction and editing of real scenes, for more engaging AR experiences. Selerio is backed by investors such as Entrepreneur First and Betaworks.

Loubna Bouarfa, CEO & Founder, OKRA Technologies

In 2016, after several years in academia, Loubna founded her own artificial intelligence company: OKRA Technologies. OKRA is a data analysis platform, using deep machine learning algorithms to transform complex datasets into evidence-based predictions, in real time. The platform was designed to equip Healthcare and Life Sciences professionals with the foresight to improve patient outcomes.Before OKRA, Loubna spent over 10 years validating and implementing machine learning (ML) solutions for real-world applications, such as an autonomous ML system that tracks surgeons’ operating movements and prevents error in real time.

Silvia Chiappa, Staff Research Scientist, DeepMind

Silvia received a Diploma di Laurea in Mathematics from University of Bologna and a PhD in Machine Learning from École Polytechnique Fédérale de Lausanne (IDIAP Research Institute). Before joining DeepMind she worked in the Empirical Inference Department at the Max-Planck Institute for Intelligent Systems (Prof. Dr. Bernhard Schölkopf), in the Machine Intelligence and Perception Group at Microsoft Research Cambridge (Prof. Christopher Bishop) and the Statistical Laboratory, University of Cambridge (Prof. Philip Dawid).

Tegan Maharaj, PhD Student in Deep Learning, MILA

Tegan is a senior PhD student at the Montreal Institute for Learning Algorithms (MILA), supervised by Dr. Christopher Pal. Tegan's academic research has focused on understanding multimodal data with deep models, particularly for time-dependent data. At the practical end, Tegan has developed datasets and models for video and natural language understanding, and worked on using deep models for predicting extreme weather events. On the more theoretical side, her work examines how data influence learning dynamics in deep and recurrent models. Tegan is concerned and passionate about AI ethics, safety, and the application of ML to environmental management, health, and social welfare.

Sharon Yixuan Li, Postdoctoral Research Fellow, Stanford University

Yixuan (Sharon) Li is a Postdoctoral Research Fellow at Stanford University. Sharon obtained her PhD from Cornell University in 2017. Yixuan's research interests are in developing robust, scalable and efficient machine learning algorithms and their applications. She was selected as one of the "Rising Stars in EECS" by Stanford University in 2017. She is the recipient of ACM-Women Scholarship. Previously she spent two summers interning at Google Research Mountain View in 2015 and 2016.

Polina Mamoshina, Head of Biomarker Development, AI division, Insilico Medicine

Insilico Medicine is a a Baltimore-based bioinformatics and deep learning company focused on reinventing drug discovery and biomarker development and a part of the computational biology team of Oxford University Computer Science Department. Polina graduated from the Department of Genetics of the Moscow State University. She was one of the winners of GeneHack a Russian nationwide 48-hour hackathon on bioinformatics at the Moscow Institute of Physics and Technology attended by hundreds of young bioinformaticians. Polina is involved in multiple deep learning projects at the Pharmaceutical Artificial Intelligence division of Insilico Medicine working on biomarker development. She recently co-authored seven academic papers in peer-reviewed journals.

Maithra Raghu, Phd Candidate, Cornell University & Research Associate, Google Brain

Maithra Raghu is a PhD Candidate in Computer Science at Cornell University, and a Research Scientist at Google Brain. Her research interests are in developing principled tools to empirically study the representational properties of deep neural networks, and apply these insights to deep learning applications in healthcare. In her current work, Maithra is studying how one can develop and train AI models to predict an uncertainty score for a patient, identifying cases where large disagreements ensue, and flagging that patient for a medical second opinion. Methodologically, she then formalizes the importance of doing direct prediction of these uncertainty scores, instead of a two step process of diagnosis and postprocessing, evaluating on a gold-standard adjudicated dataset.

Nicole He, Creative Technologist, Google Creative Lab

Nicole is an artist and programmer who uses uses digital and physical mediums to explore the relationship between humans and computers with interactivity, playfulness, and humor. Day-to-day she is a freelance creative technologist at Google Creative Lab experimenting with creative uses of voice technology. She is currently working on how computers are able to understand human speech better than ever before, yet voice technology is still mostly used for practical (and boring!) purposes, here she dives into what else we can experience in the very weird, yet intuitive act of talking out loud to machines. “People like to yell at computers, so now is a good time to make creative work with voice technology!”

Yizel Vizcarra, Senior Data Scientist, Autodesk

Yizel’s varied background in maths and science led her to fall in love with the interdisciplinary field of cognitive science. After interning at Autodesk, she was offered the full time role as a conversation engineer, later taking roles as a data scientist, now working as a senior data scientist. One of her key focuses is transparency in AI and reliability of AI, ensuring it is used for positive social impact. Previously, Yizel worked at Sensory and Human Factors Research as an intern, so is growing in her career quickly and supporting her goal to create experiences through conversations.

Eunice Chendjou, COO, OpenTeams

Eunice is the COO at OpenTeams, a B2B marketplace that helps connect a company's need for open source services, training, and support with a network of partners who can meet those needs working with the community. Prior to this, Eunice founded DataGig,  and worked as a Product Consultant and Analyst for the Canadian Business Unit at Apple. She is also a Founder Institute graduate, a program that teaches all facets of start-up development and growth from concept, to fund-raising, to validation and expansion, all the way to exit.

Bianca Furtuna, Applied Machine Learning Scientist, Microsoft

Bianca is fascinated about the power of data and how we can use the data that is constantly being collected to learn more about the world and to improve our healthcare, education, business processes etc. In her work, Bianca has been involved in a wide variety of projects from building robots and autonomous drones, to building machine learning models to solve real-world problems.She is very interested in the principles of human-computer interactions and how humans react to robots and intelligent systems. “We need to find out more about the human brain to be able to design better, more powerful and more reliable learning algorithms that could one day lead to fulfilling the AI dream.”

Anusha Balakrishnan, Senior Researcher, Microsoft

Anusha is passionate about programming, natural language processing and machine learning. She loves to work on challenging problems and make significant contributions to interesting, high-impact projects. Anusha works as a senior researcher at Microsoft, working on conversational AI. Previously, she was a Master's student at Stanford University, where she studied Artificial Intelligence with a special focus on Natural Language Processing, and worked on research projects with Dr. Percy Liang at the Stanford NLP group. She also previously worked at Siri, where she built semantic parsing models for Siri and Spotlight Search.

Tasha Nagamine, Chief AI Officer, Droice Labs

Since graduating from Brown University in 2013, Tasha has completed her PhD in Electrical Engineering at Columbia University, where her research focused on the interpretability of deep learning models. After grad school, she founded Droice Labs, an AI company specializing in understanding real-world clinical data to help physicians provide better care to their patients. At Droice, Tasha heads the AI team to develop state of the art technology that understands a doctor’s thought process through natural language understanding.

Jasmine Hsu, Software Engineer, Google

Jasmine is working on ‘cool nerdy robots’ and advancing research in deep learning and robotics. Jasmine has contributed to several publications including ‘Time-Contrastive Networks: Self-Supervised Learning from Pixles’ and ‘Learning 6-DOF Grasping Interaction via Deep Geometry-aware Representations’. Prior to joining Google, she was working in analytics, modeling and simulation at Aptima Inc, a leading human-centered research development and engineering company that works primarily for military research labs, SARPA, and NASA. Her Bachelor’s at University of Virginia was in Cognitive science, where she first became interested in AI and went on to do a masters in Computer Science at NYU, working with their Women in Computing society.

Lucy Yu, Director of Public Policy, FiveAI

Lucy leads public policy at FiveAI, a British technology company building fully self-driving vehicles to deliver safe and convenient shared mobility services for cities, starting in London in 2019. Lucy’s background combines startup business with technology policy and regulation. She has held roles at the UK’s globally renowned Centre for Connected and Autonomous Vehicles (CCAV), Cabinet Office, the Department for Transport and the UN, along with award-winning British technology startups SwiftKey (AI software), Reconfigure.io, and GeoSpock (data analytics). She has been on the boards of TravelSpirit Foundation (mobility innovation), HackTrain, and Ada, the National College for Digital Skills.

Fanny Riols, Applied Research Scientist, Element AI

Fanny Riols is an Applied Research Scientist at Element AI, building AI products. Back in Paris, Fanny co-founded Women in Machine Learning and Data Science, who advertise that they are ‘open to everyone regardless of gender or background.’ The group hosts events managed by prominent researchers, engineers, statisticians, students, where we discuss machine learning and data science with the purpose of building a community around women in these fields. Previously she was at Criteo as a R&D Software Engineer on the Machine Learning team, where she focused on mathematics and plays with Spark, TensorFlow and so many other things, to improve the prediction models by applying state-of-the-art machine learning algorithms. She has a M.Sc. in Computer Science and Machine Learning from EPITA (Paris, France), and is a qualified graduate engineer. She loves promoting tech careers.

AJung Moon, Assistant Professor, McGill University

AJung is the Director of Open Roboethics Institute (ORI). Formerly known as the Open Roboethics initiative, ORI is an international roboethics think tank that investigates ways in which stakeholders of robotics technologies can work together to influence how robots should shape our future. AJung became a Vanier Scholar in 2013 and received her Ph.D. in Mechanical Engineering from the University of British Columbia with a specialization in the design of human-inspired interactive robot behaviours. AJung also serves on the Executive Committee of The IEEE Global Initiative for Ethical Considerations in AI and Autonomous Systems and served as a co-chair of the IEEE Global Initiative’s committee on embedding values into autonomous intelligent systems.

Rosanne Liu, Research Scientist & Founding member, Uber AI Labs

After graduating with a PhD in computer science Rosanne joined a research oriented AI startup, Geometric Intelligence, working with a small group of smart people on general AI algorithms. The company is afterwards acquired by Uber Technologies Inc. to become Uber AI Labs. Rosanne was supervised by Prof. Alok Choudhary, in the Department of Electrical Engineering and Computer Science (EECS) at Northwestern University during her PhD. Her research interests span in the areas of machine learning, deep learning, natural language processing, data mining in social and scientific applications, high performance computing, parallel algorithms, and big data analytics.

Ashley Edwards, Research Scientist, Uber AI Labs

Having just finished her Phd in reinforcement learning, Ashley has joined Uber AI Labs this week. To date, Ashley has worked as a Graduate Research Assistant at Georgia Institute of Technology alongside her supervisor, Dr. Charles Isbell in his Lab for Interactive Machine Learning. The paper ‘Transferring Agent Behaviors from Videos via Motion Gans’ that Ashley contributed to was accepted into the Deep Reinforcement Learning Symposium at NIPS (now NeurIPS) in 2017. Ashley’s proposal demonstrated how perceptual goal specifications may be used as alternative forms of task instantiations for reinforcement learning. The works outlined in this document aim to validate the following thesis statement: Rewards derived from perceptual goal specifications are: easier to specify than task-specific rewards functions; more easily generalizable across tasks; and equally enable task completion.

Merve Alanyali, Senior Data Scientist, LV=

Merve is enthusiastic about combining diverse set of machine learning methods to address complex data science problems. Merve is a senior data scientist drawing on an interdisciplinary background in computer science, complex systems and behavioural science. Her research focuses on analysing large open data sources with the cutting-edge concepts from image analysis to machine learning to understand and predict human behaviour at a global scale. The examples include identifying protest outbreaks using Flickr pictures, estimating household income with Instagram pictures and predicting non-emergency incidents in New York City. Her work has received more than 100 citations and featured by television and press worldwide including coverage in Financial Times and Bloomberg Business.

Anna Huang, AI Resident, Google (Magenta)

Anna is an AI resident working on the Magenta project. She works on generative models for music. Anna is interested in how to design these models so that they can be useful tools for musicians. Previously, Anna worked in Machine Learning, MCI and music composition at MILA, Marvard, MIT Media Lab and USC. Generating long pieces of music is a challenging problem, as music contains structure at multiple timescales, from millisecond timings to motifs to phrases to repetition of entire sections. Anna has presented Music Transformer, an attention-based neural network that can generate music with improved long-term coherence. Here are three piano performances generated by the model.

Lucy X Wang, Machine Learning Engineer, Twitter

Lucy is currently a ML Engineer at Twitter with management experience and completed graduate research on information diffusion. Interests include social networks, NLP, and deep learning. Lucy completed graduate work in machine learning with research on information diffusion. Interests include social networks, NLP, and deep learning. Previously at BuzzFeed, Lucy led a team in maximizing social media distribution and revenue.

Daniela Massiceti, Associate Researcher, Microsoft Research Cambridge

Daniela completed her Ph.D. in the Torr Vision Group at the University of Oxford under the supervision of Professor Philip Torr and Dr Stephen Hicks. Prior to this, she completed a M.Sc Neuroscience at the University of Oxford, and before that a B.Sc Electrical and Computer Engineering at the University of Cape Town, South Africa. She is interested in multi-modal representations of the world and how these can be used by AI systems, primarily exploring the combinations of vision and language in the context of vision-based dialogue models for human-computer interfaces. One of her central motivations for contextualising these dialogues in real-world visual scenarios is toward building AI-based assistive devices to help blind and visually-impaired people.

Jade Leung, Head of Research and Partnerships, Centre for Governance of Artificial Intelligence

Jade is a researcher with the Governance of Artificial Intelligence Program (GovAI) at the Future of Humanity Institute (University of Oxford). Her research focuses on the governance of emerging dual-use technologies, with a specific focus on firm-government relations in the US and China with respect to advanced artificial intelligence. Jade has a background in engineering, international law, and policy design and evaluation. As an entrepreneur, she have built three social ventures, a start-up incubator, and two impact funds. As a researcher, Jade works on structuring firm-government relations to ensure a safe future with transformative artificial intelligence. As a dispositional generalist, she am most at home straddling the fields of engineering and international politics, and blending entrepreneurship with institutionalism.

Alice Piterova, Senior Advisor, Hazy

Alice has extensive experience in policy, research, product management and marketing, and a particular focus on such fields as artificial intelligence, big data and tech for good. Having worked in national and international public and private sector organisations, social enterprises and NGOs, Alice has a proven track record in delivering the strategic vision and showcasing impact to a wide range of stakeholders. Currently working as a senior advisor and managing director of Hazy and AI for Good UK respectively, Alice is certainly busy!

Liz Asai, CEO, 3Derm

Liz Asai has served as CEO of 3Derm since 2013. 3Derm is a digital health company that has developed skin imaging systems paired with machine learning algorithms to triage dermatology concerns. Over the last few years, 3Derm has raised two rounds of funding, conducted three clinical trials, and obtained reimbursement for its dermatological services from several health plans. 3Derm now serves thousands of patients at health systems in the US. Liz holds a B.S. in Biomedical Engineering from Yale University and was featured in Forbes 30 Under 30.

Elena Kochkina, PhD Student, University of Warwick and Alan Turing Institute

Elena is a Computer Science PhD student at the University of Warwick supervised by Dr. Maria Liakata and Prof. Rob Procter. Currently she am based at the Alan Turing Institute in London. Her background is Applied mathematics and Complexity science. Elena works in the area of Natural Language Processing where her research is focused on Rumour Stance and Veracity Classification in Twitter conversations. Elena is studying the benefits of utilising the conversation structure in supervised learning models. She spoke at the AI Assistant Summit in London 2018 about Opinion Mining Using Heterogenous Online Data and how understanding public opinion is important in many applications such as improving company's product or service, marketing research, recommendation systems, decision and policy making and even predicting results of elections.

Layla El Asri, Research Team Lead, Borealis AI

Layla El Asri is currently the Research Team Lead at Borealis AI in Montreal, primarily focussing research on NLP, GANs, Deep Learning and Unsupervised Learning. Alongside her work at Borealis, Layla also holds a role at Microsoft as a research Manager. Since completing her PhD in Philosophy and Data Science at the Universite de Lorraine in 2016, Layla has gone on to author papers with Yoshua Bengio and advance RBC’s innovation strategy through fundamental scientific study and exploration in machine learning theory and applications. You can connect with Layla and keep up with her work here.

Yejin Choi, Associate Professor, University of Washington

Having completed a PhD in Computer Science at Cornell University, Yejin currently works as an Associate Professor at the University of Washington. It has been an incredibly busy year for Yejin, presenting at an 13 conferences in 2019, discussing her latest work, which includes that of her primary research interest areas of Natural Language Processing, Machine Learning & Artificial Intelligence, alongside her broader interest fields of Computer Vision and Digital Humanities. Alongside this, Yejin also works as a Senior Research Manager at the Allen Institute for AI in Seattle.

Tatsiana Maskalevich, Director of Data Science, Stitch Fix

Through her Masters and PhD, Tatsiana brings both a background in mathematics and statistics to industry, also boasting deep experience building products for predicting user behaviour and implementing solutions at scale throughout her career. Tatsiana's role at Stitch Fix, the AI powered style recommendation platform, sees the director of data science lead multiple teams, focussing on data science algorithms for customer experience, styling and fraud prevention, covering a full spectrum of work in Machine Learning and operations.

Maja Matarić, Interim VP Research, University of Southern California

Having graduated with a PhD in AI and Robotics from MIT, Maja has gone on to work as a professor at both Brandies University and the University of California on two occasions, whilst also working as the founder of Embodied Inc which pulls on over fifteen years of commercialization experience to create robots that will revolutionize care and wellness for humans. Having received $22M funding in 2018, this is certainly a company to watch going forward with the hope of endowing robots with the ability to help people, especially those with special needs.

Georgia Gkioxari, Research Scientist, Facebook AI

On completion of her PhD at UC Berkeley with mentorship from Jitendra Malik, Georgia went on to intern at Google in 2015, before moving to Facebook AI in 2016 as a Postdoctoral Researcher, then later adding the role of Research Scientist in January 2018.  Georgia also works as part of the African Master's of Machine Intelligence at AIMS, an incentive which provides brilliant young Africans with state-of-the-art training in machine learning and its applications.

Sara Hooker, Research Scholar, Google Brain

Sara Hooker is a research scholar at Google Brain, currently undertaking deep learning research on reliable explanations of model predictions for black-box models. Her main research interests gravitate towards interpretability, predictive uncertainty, model compression and security. In 2014, Sara founded Delta Analytics, a non-profit dedicated to bringing technical capacity to help non-profits across the world use machine learning for good. Sara has also contributed to four papers in 2019, ranging from the sense of sparsity in DNNs to Measuring the Disparate Impact of Model Pruning. Read more on Sara's work here.

Y-Lan Boureau, Research Scientist, Facebook AI

Y-Lan worked on Deep Learning, Machine Learning, and computer vision as part of the Computational and Biological Learning Lab during her PhD, during which time she was advised by Yann LeCun and Jean Ponce. Post-certification, Y-Lan went on to intern for Samy Bengio at Google Research in Mountain View prior to joining New York University as a postdoctoral researcher and later Facebook AI as a Research Scientist. Y-Lan has co-authored 9 papers in 2019, including grounded conversational agents and more.

Viola Cao, Dara Scientist, Zurich

Viola's academic background is in Data Science and Finance, having studied finance and statistics at MSc, further building on this with a Data Science MS qualification from New York University's Center for Data Science. Post graduation, Viola worked as a Data Science intern at the United Nations Headquarters, focussing intensively in the areas of Deep Neural Network based applications such as Recommendation Engine, Generative Adversarial Networks (GANs), Natural Language Processing (NLP) and Database Management with Python. After interning at Zurich in mid-2017, Viola was employed full-time to be part of their Data Science team.

Sarah Jarvis, Head of Data Science, PROWLER.io

Sarah is a computational modeller and engineer, with research and industry experience in biomedical & biotech sectors. The foundations for this experience were gained during Sarah's PhD in computational neuroscience and B.Eng. in biomedical engineering. Post-graduation, Sarah worked at both the Imperial College London as a postdoctoral IEF fellow and as a facilitator at Decoded. Sarah moved to PROWLER.io mid-2018 and hasn't looked back, being promoted to Head of Data Science at the start of this year. Sarah is certainly one to watch in 2020!

Himani Agrawal, Data Scientist, AT&T

Himani is one of the many women in our list who are advocates for diversity, promoting women in STEM fields through their work. In this instance, Himani actively participates in the Anita Borg Institute, Women in Machine Learning & Society of Women Engineers! Himani's Doctorate in Mechanical Engineering and Applied Mathematics, accompanied by internships at Microsoft, Simpatica Medicine, Augment Solutions and a fellowship at Galvanize, set Himani in good stead for a career in Data Science, later joining AT&T as a Data Scientist in Dallas. Interested in getting involved in the promote of women in STEM? You can be in touch with Himani here.

Yang Diyi, Assistant Professor, Georgia Tech

Yang's growing experience in the Data Science industry started when graduating from Shaghai Jiao Tong University with a Bachelors in Computer Science, later attending Carnegie Mellon  University for both a Masters and PhD in Computer Science, graduating in 2015. Internships at Microsoft and Facebook later, Yang found herself at Google working as a Postdoctoral Researcher. Only six months later, Yang joined Georgia Institute of Technology as an Assistant Professor, where she is currently working on building language technologies for social good. Keep an eye on Yang in 2020 and her work on accurately and efficiently modelling human communication to build better social systems.

Martha White, Assistant Professor, University of Alberta

Martha White is an Assistant Professor in the Department of Computing Sciences at the University of Alberta in the Science Faculty. Currently focussed on developing algorithms for representation learning in RL, Martha also leads the Reinforcement Learning and Artificial Intelligence Lab at the University of Alberta. Thus far, Martha has focused on principled optimization approaches for representation learning, particularly looking at sparse representations and recurrent architectures for partially observable domains. You can see more on Martha's work in DRL and more here.

Ahna Girshick, Senior Computational Research Scientist, AncestryDNA

Another fascinating addition to the list is Ahna Girshick. Prior to moving to Ancestry, Ahna led a team of Data Scientists in a project to make groundbreaking advancements in Radiology using ML, collaborating with those in Pathology and industry to make the processes faster, more accurate and cheaper. Linking to this somewhat, Ahna then moved to Ancestry, still working with DNA, but this time to lead for development of a three-part dataset including DNA, Family trees and historical records to shed light on family members of ages past. Alongside this, Ahna has a great number of published works in journals such as Nature Neuroscience and SIGGRAPH, which has received 2000+ citations over the last few years.

Bahar Sateli, Senior Data Scientist, PwC Canada

During her PhD in Computer Science, Bahar held several positions in various organisations including a role as Doctoral Researcher at Semantic Software lab & Visiting Scholar at Friedrich-Schiller University, whilst also finding time to become co-founder of Knowlet Networks, an AI-based personal research assistant tool which aids in scientific tasks. At the end of last year, Bahar joined PwC as a Senior Data Scientist in AI and Analytics and has most recently co-authored a publication on Flexible Generation of Linked Open Data Triples from NLP Frameworks for Automatic Knowledge Base Construction.

Shalini Ghosh, Principal Scientist and Leader of Machine Learning Research, Samsung AI

Dr. Shalini Ghosh has been the Director of AI Research at the Artificial Intelligence Center of Samsung Research America, where she led a group working on Situated AI. She is now a Principal Scientist and Leader of the Machine Learning Research Group in the Visual Display Intelligence unit of Samsung Research America, where she leads a team doing research in Multi-modal Learning (i.e., learning from computer vision, language, speech and other modalities). Shalini has extensive experience and expertise in Machine Learning (ML), especially Deep Learning, and has worked on multiple domain applications at Google Research and SRI. Dr. Ghosh has a Ph.D. in Computer Engineering from the University of Texas at Austin, and has, since graduating, won several grants and awards for her research, including a Best Paper award and a Best Student Paper Runner-up award for applications of ML to dependable computing.

Dr. Radhika Dirks, CEO & Co-founder, XLabs.ai

Since graduating in 2010 with a PhD in Quantum Computing, Dr Dirks has been involved in various AI projects, as both CEO at Seldn.ai and as an AI advisor at Katapult accelerator, alderan and dashboard.earth. Whilst building moonshot companies for the Intelligent Age powered by artificial intelligence, quantum computing & neurotech, Radhika also finds time to guest lecture in AI and Quantum Computing for Singularity University, a benefit corporation headquartered at NASA Research Park in Silicon Valley.

Dorsa Sadigh, Assistant Professor, Stanford University

Dorsa is an Assistant Professor in the Computer Science & Engineering Department at Stanford University, primarily focussing on algorithm design for autonomous systems to ensure safe interactions with humans. Prior to working at Stanford, Dorsa had been part of the Berkeley EECS undergraduate program working with Prof. Sanjit Seshia on LTL synthesis and quantitative analysis of programs, later obtaining her PhD in Electrical Engineering and Computer Science. 2019 was a busy year for Dorsa who has co-authored 19 papers which you can read more on here. Make sure to keep up with Dorsa's work in 2020 and beyond!

Adriana Romero Soriano, Research Scientist, Facebook AI Research

Adriana currently works at Facebook AI as a Research Scientist whilst also acting as an adjunct professor at McGill University. Prior to this, Adriana worked as a post-doctoral researcher at Montreal University under the mentorship of Professor Yoshua Bengio. Adriana completed her PhD in 2015, with a thesis on assisting the training of deep neural networks with applications to computer vision, advised by Dr. Carlo Gatta. Adriana's Ph.D. included contributions in the fields of representation learning and model compression, with applications to image classification, image segmentation and remote sensing.

Alexia Jolicoeur-Martineau, PhD Student, MILA

Alexia is a research scientist in statistics and artificial intelligence (AI). Her main research interests are Generative Adversarial Networks (GANs), deep learning, and large-scale gene-by-environment models. Her academic and professional background is in statistics. In 2017, Alexia released the Meow Generator, a model that generates pictures of cats which you can read more on here. In 2019, Alexia entered the highly competitive PhD program at MILA, and received the Borealis AI Fellowship. Her ultimate goal is to push GANs beyond their current capabilities so that one day we can generate media content (such as movies, music, video games, and comics) through AI.

Dilek Hakkani-Tur, Senior Principal Scientist, Amazon Alexa AI

Dilek has gathered great experience in AI working at some of the largest companies in Silicone Valley including Microsoft, Google and Amazon, during which time Dilek was granted over 70 patents and co-authored more than 200 papers in natural language and speech processing including 19 this year alone. Dilek has also been the recipient of three best paper awards for her work on active learning for dialogue systems and her contributions to AI development. Dilek also finds time to be Editor-in-Chief of the IEEE/ACM Transactions on Audio, Speech and Language Processing publications. See more on Dilek's work here.

Been Kim, Senior Research Scientist, Google Brain

Formerly a research scientist at the Allen Institute and an affiliate professor in computer science at University of Washington, Been now works as a senior research scientist, primarily focussing on building interpretability, that is, to build methods for already-trained models, with particular focus on the language of explanations. Been has also been busy in 2019, co-authoring 4 papers which included research on the exploration of the Law of Closure and Testing Visual Concepts learned by Neural Networks.

Anima Anandkumar, Director of ML, NVIDIA

It has been a busy year for Anima, acting as Director of Machine Learning at NVIDIA, a member of the board at NORC, University of Chicago and Bren Professor at CalTech, also acting as co-director of the Department of Computing and Mathematical Sciences. In her roles, Anima has spearheaded research on tensor-algebraic methods, non-convex optimization, probabilistic models and deep learning, whilst also playing a large part in the enabling of machine learning on the cloud infrastructure at Amazon Web Services. Anima has also been involved in 22 collaborative papers in 2019, ranging from Tensor Learning in Python to Angular Visual Hardness.

Rachel Thomas, Founder, fast.ai

Alongside her position as founding director of the USF Center for Applied Data Ethics, which aims to address harms such as disinformation, surveillance, algorithmic bias, and other misuses of data, Rachel is also the co-founder of fast.ai, an incentive created to provide practical Deep Learning for coders which has seen over 200,00 students take part. Rachel has also spent her career advocating for Women in STEM, sitting on the board of Women in Machine Learning. Rachel is also seen to be leading from the front, herself being recognised by Forbes as one of 20 Incredible Women in AI - very well deserved.

Sandra Wachter, Associate Professor, University of Oxford

Like many of the amazingly inspirational women on this list, Sandra also has two roles at current, working as both an associate professor at the University of Oxford and also as a Turing Research Fellow in Data Ethics at the Alan Turing institute, focussing on the legal and ethical aspects of Data Science. Sandra's research areas also include algorithms, Machine Learning, Artificial Intelligence, robotics, autonomous systems and Big Data as well as Internet regulation, data protection, human rights online and cyber security.  Sandra has also co-authored three papers on the subjects listed above in 2019.

Erin Gustafson, Senior Data Scientist, Duolingo

Erin gained her PhD in Linguistics with a specialisation in Cognitive Science from Northwestern University, Illinois, in 2016, during which time Erin held several roles at the University, including working as a Graduate Teaching Assistant, an English Tutor, interning in the NLP department and more. Since graduating Erin has worked as a Data Scientist at Duolingo, being promoted in September to a Senior Data Scientist. Erin's role mainly focusses on developing metrics, data-driven decision making and forecasting user and revenue growth.

Myriam Côté, Director, AI for Humanity

Myriam joined Mila in 2009, and was appointed as Executive Director from 2015 to June 2018. She also became Director of the Mila R&D and Tech Transfer team from 2017 to September 2018, she is now Director of AI for Humanity. Myriam has over 15 years of professional experience in artificial intelligence, project management and software development, in both academic and industrial research environments. As Director of AI for Humanity, Myriam is aiming to action Mila’s humanitarian mission in collaboration with both local ecosystem partners and international allies, by promoting an ethical and socially responsible usage of AI.

Doina Precup, Research Team Lead, DeepMind

Doina holds a Canada Research Chair, Tier I in Machine Learning at McGill University, and currently co-directs the Reasoning and Learning Lab in the School of Computer Science. Alongside this, Doina also serves as an Associate Dean for the Faculty of Science as well as acting as the Associate Scientific Director of the Healthy Brains for Healthy Lives CFREF-funded research program at McGill. Doina's research interests include reinforcement learning, deep learning, time series analysis, and various applications of these methods. She is a Senior Member of the American Association for Artificial Intelligence.

Joelle Pineau, Associate Professor, McGill University & Co-MD, Facebook AI Research Lab

Joelle Pineau is an Associate Professor and William Dawson Scholar at McGill University where she co-directs the Reasoning and Learning Lab. As a member of Mila’s faculty corp, Joelle also leads the Facebook AI Research lab in Montreal, Canada. Currently focussed on researching the development of new models and algorithms for planning and learning in complex partially-observable domains, Joelle's plans to apply these algorithms to complex problems in robotics, health care, games and conversational agents. Joelle chaired a panel session with AI pioneers Geoffrey Hinton, Yoshua Bengio and Yann LeCun at the inaugural Montreal edition of the Deep Learning Summit. You can watch a summary here.

Natacha Mainville, Sr Research Program Manager, Google AI

Natacha graduated from Polytechnique Montreal in Computer Engineering and is a seasoned engineering executive with previous roles as a Chief Innovation Officer at TandemLaunch and as VP of Software Engineering at Intact. Natacha believes in a world with more young women in STEM and leadership positions, actively seeking opportunities to champion this cause through mentorship, discussion and outreach. We were lucky enough to have Natacha attend our summit in Toronto last year and record a fireside chat with fellow Google Brain AI Resident, Sara Hooker. See the full talk here.

Valerie Becaert, Director of Research and Scientific Programs, Element AI

Before joining Element AI, Valerie was director of partnerships at the Institute for data valorisation (IVADO), which brings together more than 900 scientists working to extract economical and societal value from data. She holds a PhD in Chemical Engineering from the Polytechnique Montréal in environmental modelization. Her career began as a researcher in the field of life cycle analysis, a powerful tool employed to evaluate the potential impact of human activities on the environment. It is by working with optimization and mathematics researchers to solve environmental problems that Valerie became convinced that our ability to generate, analyze and value big data would change the world.

Valerie Pisano, President and CEO, Mila

Valerie is dedicated to ensuring that there is diversity and equality in the workplace and is a proud mother of three girls. She was previously Chief Talent Officer at Cirque du Soleil and cofounded The Mobïus Bias Project, an initiative focused accelerating the dialogue on female leadership roles by exploring unconscious bias. Valerie holds a Masters Degree in Applied Economics, and has experience in strategy, leadership, talent management and corporate culture which have all contributed to her passion of fulfilling human potential to make the world a better place. Valerie is currently the president and CEO of MILA - the Quebec Artificial Intelligence Institute.

Caroline Pernelle, Director Strategy Innovation, Larochelle Groupe Counseil

Caroline defines herself as a data-techno-geek who loves to make the data speak and also advance the potential of humans. She holds a bachelor's degree in mechanical engineering with a specialisation in aeronautics from Polytechnique Montréal and a journalism certificate from the Université de Montréal. Having worked in a variety of industries, Caroline believes that the key to making companies become more efficient and spark innovation is through the use of data and picking out the important information to prepare us for ‘the world of tomorrow’.

Margaret Magdesian, CEO & Founder, ANANDA Devices

As CEO & Founder of the startup Ananda Devices, Margaret works with advanced technologies for drug development. Using her 8 years of research from McGill University, Margaret created Ananda Devices and heads a team whose expertise in stem cells, microfluidics and nanotechnology has produced a micro device for growing human mini-brains, mini-spinal-cords and innervated tissues to form a Human Organ-on-a-Chip Platform (HOCP).

Sarah Jenna, Co-founder and CEO, My Intelligent Machines

Sarah is Co-Founder & CEO of My Intelligent Machines and obtained her PhD in cell biology and microbiology at University Aix-Marseille in France, 1988. As the Co-Founder and CEO of MIMs Inc, she translates the expertise to provide MIMs with the state-of-the-art integrative genomics abilities and attention to specific needs of biologist users. MIMs Inc's mission is to help life-science companies use their big data and AI to maximize food and drug production.

Marina Pavlovic Rivas, Co-Founder & CEO, Eli

Marina, Co-Founder & CEO at Eli believes that entrepreneurship, data science and information as tools can help shape the future in a good way. She uses these tools to tackle challenges in the creative industries and is working with these to develop a new type a medical technology in the fertility space that puts the need of women first.  Marina wants to make tech more inclusive, both for people who make it and for those who use it. You can read more about how Eli is providing women with a new type of solution to manage reproductive health here.

Claudia Pérez-Levesque, Consultant, Badgerly

Previously the founder of exVentus, Claudia, is an energetic renewable energy enthusiast with an engineering background based in Montreal. She is a CleanTech & STEMinist striving to make the world more diverse and sustainable with algorithms. Claudia aims to use her problem deconstruction skills and capacity to connect to make the world a more inclusive and sustainable place. Claudia is now working as a consultant for Badgerly in Montreal.  

Alexandrine Allard, Senior Product Designer, Moment Factory

As a Senior Product Designer at Moment Factory, Alexandrine believes that great design is 'complexity communicated into simplicity'. Moment Factory is a multimedia entertainment studio specializing in immersive environments and experiences. Alexandrine's passion for behaviour psychology is what helps her create human-centered functional experiences. She wants to design products that ultimately make people happy and design these experiences by leveraging empathy, goodness and impact around her.

Elodie Micoulet, Project Facilitator, Unity Technologies

Elodie is a Project Facilitator at Unity Technologies having also previously been the Scrum Master at Nuglif with expertise in executive dashboard development. Elodie collected her Ph.D. from SUPINFO back in 2012. Since then, Elodie has worked as a BI Developer and Scrum Master at various organisations.

Caitrin Armstrong, CTO, Aifred Health

Caitrin has just been promoted to CTO at Aifred Health and is an advocate for the careful consideration of data preprocessing in ethics group discussions. She finds joy in retrieving, processing and synthesizing information. Caitrin holds and MSc in computer science from McGill University and is interested in personalized medicine, AI ethics and computational social science.

Johanna Hansen, PhD Researcher & Research Intern, McGill & NASA

Johanna is a PhD Researcher looking into model-based planning and reinforcement learning with generative models for mobile agents. She enjoys working on projects which seek to improve our understanding of the natural world through autonomous data collection and modeling. She is  currently working at NASA Jet Propulsion Laboratory taking part in a research internship working on machine vision aspects of the Mars Sample Return Project.

Wendy Tay, Product Manager, Borealis AI

Wendy's product manager role at Borealis AI, which is the applied AI team at RBC, leverages product strategy, analytical and customer research skills to deliver significant results. She is interested in using technology and design to creatively solve customers problems. Wendy's work mainly focuses on Product Discovery, Product Roadmaps, Vision, & Strategy, Data Analysis, Agile Processes, Marketing, Artificial Intelligence (AI)

Yosra Kazemi, Co-founder, Sunia Technology

Co-Organizer of WiMLDS Montreal Chapter, Yosra is passionate about impact-full innovation, entrepreneurship, and promoting inclusion and diversity which you can find out more about on WiMLDS Montreal.

Annie Veillet, Partner - Responsible AI, PwC Canada

Leading the Intelligent Automation offering at PwC, Annie works with various organizations and helps them to build trust into their AI, focusing on responsible AI, leveraging AI techniques to automate, and Robot Process Automation (RPA). Annie has a Masters degree in Information Technologies from the University of Montreal and a Bachelor of Commerce from HEC Montreal.

Carolina Bessega, Chief Scientific Officer & Co-Founder, Stradigi AI

Caroline began her career by obtaining her PhD in fundamental physics, eventually becoming an award-winning professor and researcher and was also appointed by the Venezuelan Science and Technology Ministry as the coordinator of the national program for graduate students in her field. Her meteoric rise as Chief Scientific Officer and her extensive experience working in machine learning now allows her to work alongside renowned advisors and business pioneers in the industry to continuously create, innovate, and develop new technologies that solve real world problems.

Simona Gandrabur, Sr. Director - AI Lead, National Bank of Canada

Currently, Simona is working as the AI strategy lead at the National Bank of Canada, in charge of identifying and executing upon AI investment opportunities within the bank's Wealth Division. She has been working in the general field of AI for close to 20 years, most notably in areas related to processing of human languages – such as automatic speech recognition, natural language understanding, machine translation and conversational reasoning. You can read up on 'The Future of Advanced Dialogues Applications' here.

Margarita Mayoral Villa,  Physicist - Data Scientist

Margarita holds a masters degree in Physics and seven years of experience in IT and forecasting industries. She is passionate about predictive methods, the statistical and quantitative analysis, the complex systems and the physics and computational models. "This complicity helps to drive decision making. Margarita is currently working as a Data Scientist at Adviso and as an AI Consultant at ENERXICO Project.

Mona Hajimomeni, Research Scientist, Stradigi AI

Mona is a researcher in artificial intelligence, data analysis and machine learning at Stradigi AI. Her background is in statistical signal processing, pattern recognition, and Bayesian learning and she has always had a passion for making things. Her PhD was in the area of physical layer security for wireless channels during which she gained a solid knowledge of linear algebra, advanced calculus, optimization theory, neural networks, and in a more restricted extent information theory.

Laura Cristescu, Director of Product - Conversational Experience (AI), National Bank of Canada

Laura has a background in strategic marketing communications, with experience providing counsel to senior level decision makers, relates to using all research and knowledge base. Read Laura's LinkedIn article 'How header bidding is shaping the programmatic landscape' here. Laura has 12+ years experience in the media industry, from magazines, to online, to apps, experience in online advertising technologies, e-com and services, expertise in mobile solutions.

Doaa Mansour, Advancement, McGill University

With a global experience in the development of programs, businesses, and strategic partnerships in the private and nonprofit sectors, Doaa has a commitment to leveraging cross-sectoral collaborations and technologies in advancing the human condition. Doaa is currently aiding the McGill University in their AI Advancement techniques.

Lisa Ebert, Lead Solutions Strategist, Element AI

Lisa grew up in Germany and then moved to Canada, where the diversity of different cultures and languages inspired her. She is passionate about tech startups and pushing the boundaries of artificial intelligence and this is why she joined Element AI 'the company that's at the forefront of it all'. She also believes that the best ideas emerge when people of diverse backgrounds come together.

Isabelle Bégin, Senior Research Scientist, AITY3D

Isabelle is most interested in applying state-of-the-art computer vision research to real-world applications. Currently at AITY3D, Isabelle is focussed on 3D computer vision and image processing R&D using deep learning and classical approaches. Isabelle also has great experience with various types of images and applications. Python, C/C++, Tensorflow, Pytorch, openCV, Matlab programming. Interested in applying state-of-the-art computer vision research to real-world applications.

Rebecca Simpson, Machine Learning Developer, Imagia

Becks is a multi-disciplinary deep learning specialist with experience across research, product development and mentoring in medical imaging, robotics, agricultural applications and computational linguistics. She has a keen interest in applying cutting edge research in machine learning and deep learning to solving real problems in industry as well as mentoring companies in data strategy, new and traditional methods for incorporating ‘AI’ into their product and best practices for doing so.

Narjes Boufaden, Founder & CEO, Keatext

Last but by no means least, Narjes Boufaden! Narjes is passionate about solving technical challenges involving natural language understanding, and is among the first researchers who specialized in text mining technologies for conversational text, such as dialogues and telephone conversations. She has contributed in the field with more than 15 scientific publications and several conference talks. In 2010 she founded KeaText with the mission of helping organizations make sense of massive volume of information for better decisions and productivity. She is also a mentor at Techstars MTL AI, helping early-stage startups with their AI technology and business model.

Sanja Fidler, Assistant Professor & Director of AI, University of Toronto & NVIDIA

Sanja is Assistant Professor at the Department of Computer Science, University of Toronto. Previously she was a Research Assistant Professor at TTI-Chicago, a philanthropically endowed academic institute located in the campus of the University of Chicago. She completed her PhD in computer science at the University of Ljubljana in 2010, and was a postdoctoral fellow at University of Toronto during 2011-2012. Sanja was appointed as Director of AI at the new NVIDIA lab in Toronto back in May 2018.

Raquel Urtasun, Head of Uber ATG Toronto, Uber

‘Self-driving technology has the potential to fundamentally change the way we live in a very positive way. I find this truly inspiring.’ As well as heading up Uber ATG, Raquel is an Associate Professor in the Department of Computer Science at the University of Toronto, a Canada Research Chair in Machine Learning and Computer Vision and a co-founder of the Vector Institute for AI. Raquel’s research interests include machine learning, computer vision, robotics and remote sensing. Having a woman at the helm of making Uber’s self-driving cars smarter is a great representation of strong female role models for aspiring AI professionals to look up to.

Sandy Penn Whitehouse, Co-Founder and CEO, Ticket Health

Sandy believes that technology needs to work for the people, not the other way round. Her work centres around improving healthcare and giving people a voice to talk about what they’re feeling without there being a stigma around it. As a strong advocate for young people she is using technology as a tool to make these changes happen, in 2012 she Co-Founded Tickit Health, with the goal to end medical miscommunication and build a healthcare system that listens.

Saadia Muzaffar, Founder, Tech Girls Canada

Saadia has done a vast amount of work towards creating an environment in the AI industry that includes diversity. She is part of Canada Beyond 150: Policy for a diverse and inclusive future‘s Feminist Government initiative, and an advisor to Government of Canada’s Economic Strategy tables for the Access to Skilled Talent working group. Her work is focused on maximising the ‘public good’ and she has built up the hub for Canadian women in science, technology, engineering, and math.

Natalie Cartwright, Co-Founder & COO, Finn.ai

Finn.ai is a white-labelled virtual banking assistant, powered by artificial intelligence. Natalie and the team put a personal banker in every customer's pocket, helping them to manage their money wherever they are, whatever they need via a simple, natural conversation. Our secure, easy to integrate platform is used by leading financial institutions and banks to delight their digital savvy customers, improve loyalty and reduce call centre and IVR volume and cost. Before co-founding Finn.ai, Natalie studied at IE Business School in Madrid.

Maithili Mavinkurve, Founder & COO, Sightline Innovation

At Sightline Innovation, Maithili's goal is to make this technology accessible to industry and immediately applicable without the need for Data Scientists or Ph.D. Sightline Innovation has designed a machine learning as a service platform designed to address problems facing industry today. As Founder and COO at Sightline Innovation, Maithili is in charge of ensuring smooth delivery of their solutions into a customer’s organization. Maithili is a long time entrepreneur and leverages decades of engineering management experience to ensure customers can harness the power of deep learning and achieve immediate gains.

Jennifer Gibbs, Global Chief Data Officer, TD Bank

Jennifer Gibbs is the Vice President & Global Chief Data Officer, Enterprise Data & Analytics, TD Bank Group. Her mandate includes developing and implementing strategies, programs, and policies to improve and sustain the governance, management, protection, and value of TD's data assets. Jennifer provides guidance and oversight across TD's lines of business to support strategic data initiatives and regulatory and compliance expectations related to data.

Inmar Givoni, Director of Engineering, Uber ATG

Inmar recently became Director of Engineering at Uber ATG Toronto, currently building self-driving vehicles using cutting-edge deep-learning models. Inmar also participates in various career panels and career mentoring events. As a technical woman, Inmar is particularly interested in outreach activities for young women, encouraging them to choose technical career paths. For her volunteering and mentoring work, Inmar received the University of Toronto’s 2017 Arbor Award, and was recognized as one of the 2018 inaugural cohort of 50 inspiring Canadian women in STEM.

Foteini Agrafioti, Chief Science Officer, Royal Bank of Canada; Borealis AI

Foteini is Head of Borealis AI, an RBC Institute for Research in the field of Artificial Intelligence. Borealis perform fundamental and applied research in deep learning and reinforcement learning with applications in the financial industry and beyond. Prior to this, Foteini had been CIO and CTO at Architech and Nymi respectively. Foteini completed her Ph.D. at the University of Toronto in Electrical and Computer Engineering.

Dr. Helia Mohammadi, Chief Data Scientist, Microsoft Canada

Dr. Helia Mohammadi is the National Healthcare Chief Data Scientist for Microsoft Canada. With over 14 years’ experience in research and applied Artificial Intelligence, her work leverages and extends Machine Learning and cloud solutions to process data into actionable insights, and aid with digital transformation in the healthcare domain from predictive analytics to genomics research and precision medicine.

Valérie Bécaert, Director/Research Group, Element AI

Valélrie defines herself as a ‘tech-eco-geek’ and ‘looks to the future with optimism and wonder’. Her career started as a researcher in the field of life cycle analysis looking into the effect that human activities are having on our environment, she then moved on to become the Director of CIRAIG and CIRODD. Her work revolves around actioning work that can be done to solve environmental problems and Valélrie fully believes that we have the capability to change the world through generating, analysing and enhancing our data.

Marise Bonenfant, Co-Founder, Myelin

Marise is the Co-Founder of Myelinana online platform that provides information about Autism. Having waited 2 years to have a diagnosis for her chronic illness she wanted to create a space where there’s easy access to scientific information; she wants users to be able to ask a simple question and receive an answer through an algorithm made with AI. The aim is to eventually have the entire psychosocial domain to be referenced: ADHD, anxiety, depression, homelessness, school dropout, etc.

Angelica Lim, Assistant Professor, Simon Fraser University

During her masters and PhD at Kyoto University, Lim combined computer science with neuroscience and cultural development psychology to build a robot that “feels”. As a pioneer in “developmental robotics”, which models human-style learning in machines, Lim explains that toddlers link names of emotions to specific sets of physiological and psychological states as well as physical expressions. Learning for both humans and robots is heavily influenced by caregivers and culture. Angelica has also given a number of TED talks on designing and co-existing with emotional and empathetic robots.

Kathryn Hume, Senior Director, Borealis AI

Prior to working at Borealis AI, Kathryn was the director of sales and marketing at Fast Forward Labs (Cloudera), where she helped Fortune 500 companies accelerate their machine learning and data science capabilities, and a principal consultant in Intapp’s Risk practice focused on data privacy, security, and compliance. A widely respected speaker and writer on AI, Kathryn excels at communicating how AI and machine learning technologies work in plain language. She has given lectures and taught courses on the intersections of technology, ethics, law, and society at Harvard Business School, Stanford, the MIT Media Lab, and the University of Calgary Faculty of Law.

Afsaneh Fazly, Director of Research, Samsung Research America

Afsaneh Fazly is a researcher with over 20 years of experience in the areas of Computational Linguistics and Cognitive Science. Afsaneh has an outstanding publication record, with over 50 articles in prestigious journals, conferences, and workshops in various areas of AI, including a paper that won the Google best paper award in 2013, and one that won the best Language Modeling paper award from the Cognitive Science Society in 2008.

Jodie Wallis, Managing Director, Accenture

During her 24 years at Accenture, Jodie has developed deep expertise in management consulting and technology consulting. She has served clients in several industries including, most recently, personal and commercial banking as well as life and health insurance. She actively volunteers in the Toronto community, serving on the organizing committee of the Covenant House Guts + Glory Corporate Challenge, which raises funds for Canada’s largest agency serving at-risk, homeless and trafficked youth.

Leila Boujnane, CEO, Tineye

Originally from France, Leila moved to Canada where she started working for a software company and discovered her passion for it, using technology to solve complex problems. From this she built her own company Tineye which is an image recognition app. Once you submit an image into the tool it will tell you where that image has been published on the Web, even if the image has been altered - a great tool for photographer to see if their photos have been used/where. Having worked in Canada for a considerable amount of time Leila has been able to see the impact women have had in the industry and she is now setting her sights on mentoring and helping women in developing countries where girls don't have easy access to education.

Neda Ghazi, Co-Founder & CEO, Comfable

Neda is the Co‐founder and CEO of Comfable, a tech startup that uses innovative solutions to empower people to live healthier in a greener environment. She is using her experience and extensive knowledge in sustainable design to grow the business and create smart, healthy and resource-efficient products. She has extensive experience as a research scientist at the Technical University of Berlin and as a project manager at Comfable and Manzar. She involved in design and construction of award-winning projects in Iran and Canada.

Sarah Villeneuve, Policy Analyst, AI + Society, Brookfield Institute

Sarah is particularly interested in emerging technology’s impact on public policy, human well-being, and the economy. Motivated by both the potential benefits technology offers to governments and civil society, and concerns of fairness, accountability and inclusivity, she seeks to contribute to critical conversations surrounding the development and adoption of technology in public life.  She has previously conducted research on algorithmic discrimination, smart-city marginalization, and predictive analytics for governance. On top of this Sarah is a contributor to the IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems, as well as the IEEE Standards Association Working Group on Wellbeing Metrics for Artificial Intelligence and Autonomous Systems.

Negar Ghourchian, Director of AI, Aerial Technologies

Whilst studying for her PhD in Machine Learning and Activity Recognition, Negar joined the Tandem Launch’s offices as part of their portfolio company Aerial Technologies. She has since gone on to become the Senior Research Scientist and continues to use artificial intelligence to make smart and safe homes, focusing particularly on the elder who live alone. Following from this Negar was listed in Mitacs’ Next 150! The list presents the 150 innovators in Canada whose work will have a positive impact on Canada for the next 150 years.

Jekaterina Novikova, Director of Machine Learning, WinterLight Labs

Winterlight Labs is a Toronto-based Canadian company that is developing a novel AI-based diagnostic platform that can objectively assess and monitor cognitive health. Jekaterina's work explores AI in the context of language understanding, characterising speaker's cognitive, acoustic and linguistic state, as well as in the context of human-machine interaction. Jekaterina received a PhD in Computer Science in 2015 from the University of Bath, UK.

Adelyn Zhou, Advisor, Signal Fire

Adelyn Zhou is a business leader and bestselling author who is passionate about the intersection of marketing, automation, and the future of work. She has worked with some of the world's top companies and fastest growing startups on growth, blockchain applications, and applied artificial intelligence. She is recognized as a top influencer by Forbes, Entrepreneur, Inc., Wired, Hubspot and many others. She started her career at the Boston Consulting Group and later led growth efforts at Amazon (Quidsi), Nextdoor, and Eventbrite. She is an internationally recognized speaker at conferences such as SXSW, CES, Inbound, and DLD.

Anna Choromanska, Assistant Professor, NYU Tandon School of Engineering

Anna’s main focus is machine learning, looking at both the theory and its application to real life problems. Her work includes applying machine learning to analyze neural circuits, particularly 3D reconstruction of neurons from confocal microscopy images and classification of neurons. Anna has won numerous awards during her studies, including the Student Best Paper Award in 2012, for her contribution to the paper 'Majorization for CRFs and Latent Likelihoods'.

Bouchra Bouqata, Senior Data Scientist and Machine Learning Product Manager, GE Renewable Digital

Bouchra leads programs in the area of large-scale automated-intelligent Machine Learning solutions and products emphasizing on solving GE’s Wind and Energy Industrial Internet Big Data problems in the areas of Prognostics and Health Management, Remote and Online Monitoring and Diagnostics. Bouchra first joined GE in 2006 as a Senior Data Scientist, where she lead GE’s efforts on artificial general intelligence and general autonomous intelligent systems.

Catherine Edwards, Machine Learning Engineer, Spotify

At Spotify Catherine works on personalizing content on Home. Originally from Chicago, Catherine received her BSE in Computer Science from the University of Michigan’s College of Engineering. Now living in New York, Catherine is the Co-Founder of Code Squad, a non-profit organization dedicated to bringing computer science education to underrepresented middle schools across Washington, DC.

Claire Cardie, Professor, Cornell University

Claire’s primary research is in the area of natural language processing with the goal to develop algorithms and systems that will vastly improve a user's ability to find and extract information from online text. Claire’s group’s current work encompasses a number of related areas, including noun phrase coreference resolution and NLP for e-rulemaking. In 2015 Claire was selected as a Fellow of the Association for Computational Linguistics for foundational contributions to co-reference resolution, information and opinion extraction, and to machine learning methods in natural language processing. She has a B.S. in Computer Science from Yale, and M.S. and PhD. degrees in Computer Science from the University of Massachusetts.

Gabrielle Haddad, Co-founder & Chief Operating Officer, Sigma Ratings

Gabrielle began her career as an M&A attorney at Milbank, Tweed, Hadley & McCloy in NYC. She subsequently spent several years as an executive at The Global Fund, a Geneva, Switzerland based international financing institution, where she worked on risk and governance issues in over 30 country portfolios across Africa, Asia and the Middle East. She later returned to the US and to spend a year studying at MIT, where she met her co-founder and launched Sigma.

Heather Wilson, Executive Vice President, Chief Analytics & Artificial Intelligence Officer, LBrands

Prior to joining LBrands in 2016, Heather was the Chief Data Officer of AIG and Chief Data Officer and Global Head of Analytics for Citigroup. Heather launched the Kaiser Permanente Women in Technology group focused on mentoring, innovation and retention for women in math, technology and science. She was an executive member of Citi4Women.

Jalak Jobanputra, Founder & Managing Partner, Future\Perfect Ventures

Future\Perfect Ventures is a venture capital fund focused on early stage investments in next generation technology including blockchain and machine learning. Before founding Future\Perfect Ventures in 2013, Jobanputra was the Director of Mobile Investments in Emerging Markets at Omidyar Network. She has 20 years experience in venture capital, impact investing, media and technology. She was previously Senior Vice President at the New York City Investment Fund, a private economic development fund, where she managed the fund’s technology and digital media venture investments. While there, Jobanputra spearheaded the formation NYCSeed in 2008, and helped launch the FinTech Innovation Lab, which has since been replicated in London and Hong Kong.

Jessica Chen Fan, Principal Software Engineer, Curology

Jessica has held internships as a Software Engineer at Amazon Web services and Microsoft. Jessica completed her B.A. in Computer Science at Columbia University in 2016. Jessica’s interests in AI include Machine Learning, robotics, hardware and computer vision.Jessica recently moved to Curology in New York, a dermatology company focussed on clearing the skin.

Joanne Wright, Vice President Enterprise Operations & Services, IBM

In her role at IBM, Joanne is responsible for the strategy, execution and business results for IBM’s manufacturing, fulfillment and client solutions across more than 170 countries. She is leading her teams through the transformation of the first AI-enabled supply chain, creating a supply network leveraging cognitive supply chain, advanced analytics and advancing blockchain to revolutionize IBM’s supply chain. Joanne is a member of the Women in Technology International, and was recognised as one of Fortune’s Most powerful Women Next Gen in 2016 and 2017.

Kadija Ferryman, Postdoctoral Scholar, Data & Society Research Institute

Kadija is a cultural anthropologist whose research centers on the ethics of emerging technologies in biomedical research and health care. Specifically, her work examines the ethical dimensions of biomedical research that uses genomics to address racial disparities in health. Using ethnographic methods, she examines how values shape efforts to use genomic data to improve health outcomes and reduce chronic disease risk. Dr. Ferryman holds degrees in anthropology from Yale (BA) and the New School for Social Research (PhD).

Laura McKiernan Boylan, Head of Underwriting Solutions, Haven Life

Haven Life is MassMutual’s in-house startup that uses algorithms and machine learning models to streamline the customer experience for policy purchases. Laura works with a team of software engineers to build technology that supports direct-to-consumer life insurance sales and underwriting. Prior to joining Haven Life, Laura was an actuary at AXA US. She worked on predictive underwriting, financial advisor analytics, hedging, and reinsurance. Laura received an A.B. in Applied Mathematics from Harvard College.

Lindsay Payne, Business Development Manager, Artificial Intelligence, HSBC

Lindsay is an inquisitive digital banking professional with a collaborative nature and motivated by complex business problems, relishing piecing together data, industry trends, and competitive insights to deliver tactical and innovative solutions.

Maryam Farooq, Founder & Director, New York Artificial Intelligence

Maryam leads the team at NYAI, a “community of researchers, developers, educators, data scientists, investors, and general enthusiasts that gather to network, learn, and discuss emerging trends in AI.” Maryam is also the Global Director of Client Experience at Machine Colony. Machine Colony is an AI startup that works with governments and large enterprises to help them adopt artificial intelligence at scale.

Peggy Tsai, VP of Data Solutions, BigID

Previously Vice President in the Analytics & Data department at Morgan Stanley Wealth Management, Peggy has now moved to BigID, a New York based company using advanced machine learning and identity intelligence to help enterprises better protect their customer and employee data at petabyte scale. Peggy is also passionate about sharing my innovative technology ideas by mentoring, speaking at student clubs and organizing events through Women in Technology groups.

Pia Ramchandani, Responsible AI Researcher, PwC

The former co-lead of the Artificial Intelligence Accelerator is now working on responsible AI at PwC, as well as studying for her PhD in operations and management science. Over her career, Pia has built over 10 years of modelling experience in  AI with a focus on simulation, stochastic modelling, machine learning, optimization, natural language processing and decision sciences.

Priyanka Mohandas, Machine Learning Research Assistant, New York University

In 2015 Priyanka graduated from New York with a Master of Science degree in Electrical Engineering with a concentration in Signal Processing and Machine Learning. Priyanka lists her passions as Deep Learning and Analytics. Currently a Machine learning Research Assistant in NYU school of medicine, Priyanka  is using Machine Learning and signal processing techniques to work on decoding the effect of specific stimuli on the high frequency and event-related potential ECoG activity of the brain.

Rebecca Peyser, Research Software Engineer, MIT CSAIL

At CSAIL, Rebecca is a Data Scientist and Research Software engineer in Prof. David Sontag's Clinical Machine Learning Group.In her work Rebecca’s passions as science, technology and healthcare. From 2016-2018 Rebecca was a bioinformatics analyst at Regeneron Pharmaceuticals, and in 2015 she co-founded Neopenda, a technology start up that engineers innovative healthcare solutions to give newborns in low - resource settings healthier lives.

Sanhita Mukherji, Software Engineer, VMware

Sanhita completed her masters in Information Science at Cornell University in 2016. She is currently a Software engineer at VMware. Prior to joining VMware, Sanhita worked at Pivotal Software and as a Software Engineer at BlackRock, where she Designed and developed a real time monitoring tool for all the applications and servers inside ALADDIN.

Saskia Steinacker, Global Head Digital Transformation, Bayer

In 2004 Saskia joined Bayer, a global enterprise with core competencies in the Life Science fields of healthcare and agriculture. In 2017, Saskia was named Head of Digital Excellence, where she leads Bayer’s digital transformation in close collaboration with the Board of Management. Saskia is also an appointed member of high level Expert Group on AI by the European Commission. Together, the group make recommendations on how to address mid-and long-term challenges and opportunities related to artificial intelligence.

Tanzeem Choudhury, Associate Professor, Cornell University

Tanzeem directs the People-Aware Computing group at Cornell University, where she works with her team to invent the future of technology-assisted wellbeing. Tanzeem’s primary interests include building novel wearables and mobile systems for capturing and influencing everyday human behaviors. Tanzeem is also the cofounder and CEO of HealthRhythms, which uses Deep Learning and predictive analysis to create novel health assessments and  just-in-time personalized interventions. Tanzeem is the recipient of numerous awards for her work, including the MIT Technology Review TR35 award and an NSF Career Award.

Tobi Bosede, ML Lead, Capital One

Tobi holds a bachelor’s degree in mathematics from the University of Pennsylvania and a master’s in applied mathematics and statistics from Johns Hopkins University. Throughout her career Tobi has applied her work in AI across multiple industries, working in credit risk at JP Morgan Chase and in telecoms as a Data Scientist at Sprint. Now at Capital One, Tobi’s work includes creating algorithm for segmenting risky credit card customers to improve monitoring for business analysts and generating ML based forecasts.

Vivian S. Zhang, CTO & Chief Data Scientist, NYC Data Science Academy

Vivian is an experienced data scientist who has applied her knowledge and expertise has been devoted to the analytics industry and the development and use of data technologies for several years. SupStat Consulting is a data analytics company specializing in predictive modelling, inference, computing, and graphics.Vivian is also the CTO and Chief Data Scientist of NYC Data Science Academy.

Tian Su, Director of Machine Learning, Walmart

Tian is an experienced Data Scientist, currently working as Director of ML at Walmart in Plano, Texas. Having previously worked as both a Senior Data Scientist & Head of AI/ML at 7-Eleven, Tian has been heavily focussed on personalization and delivery for customers in the CPG market. Dr Tian holds considerable experience and skill in Advanced Analytics, Data Mining, Statistical Modeling, Machine Learning, Databases and Artificial Intelligence. She also boasts a strong research background with a Ph.D. from Yale University and Master’s Degree focused on Computer Science from Georgia Institute of Technology.

Kristen Grauman, Professor, University of Texas

Kristen is a Professor in the Department of Computer Science at the University of Texas and a Research Scientist at Facebook AI Research (FAIR).  Prior to joining UT-Austin, Kristen received her Ph.D. from MIT and was later recognised as an AAAI Fellow, Sloan Fellow, a Microsoft Research New Faculty Fellow with a broad range of accolades to her name which can be seen here. Kristen boasts over twenty-thousand citations on authored and co-authored papers, with five published this year alone. Kristen's current research interests include computer vision and machine learning with the goal of developing the algorithms and representations that will allow a computer to autonomously analyze visual information.

Kay Firth-Butterfield, Head of AI/ML, World Economic Forum

Kay Firth-Butterfield LL.M., currently heads the Artificial Intelligence and Machine Learning division of the World Economic Forum in San Francisco, working out of Austin, Texas. Alongside her current work at the WEC, Kay co-founded the Consortium for Law and Policy of Artificial Intelligence and Robotics at the Robert E. Strauss Center, whilst also working as an expert advisor for the All Party Parliamentary Group on AI. Kay is also one of the leading consultants on the impact of AI with an emphasis on Law, Ethics and International Relations for various companies and publications. You can read further musings from Kay on her social media here.

Priya Sundararaman, Principal Data Scientist, State Farm

Currently working at State Farm, Priya's recent work has been focussed on both identifying data science solutions and leading data scientist teams with the target of aiding businesses claims area achieve value through measurable and sustainable ROI. Following her Bachelor's Degree in Computer Science, Priya continued her studies at Northwestern University, with particular focus on Predictive Analysis. Prior to her work at State Farm, Priya worked as a Data Science Consultant whilst developing Umachi books, a company dedicated to Indian heritage and mythology to young children. You can see further information on Priya's work and featured keynote presentation videos here.

Subhashini Tripuraneni, Executive Director - Machine Learning, J.P. Morgan

Subhashini's business background in both public & private sectors (including banking), alongside extensive experience in Artificial Intelligence, Data Science, Software Development, & Development Operations has seen her hold the roles of Head of AI & Director of Machine Learning at 7Eleven and JPMorgan Chase respectively. Currently playing the role of play the role of “IT strategist”, Priya's role mainly focuses on the implementation of customer-centric & automation via Machine Learning use. Alongisde her current role ay JPM, Subhashini also consults as an Analytics advisory board member of Southern Methodist University, and has also found time to author a book via the Packt platform. Keep up with Subhashini's work going forward here.

Jostine Fei Ho, Senior Data Scientist, Sailpoint

Jostine Ho is a Senior Data Scientist at SailPoint. With a master’s degree in petroleum engineering and background in computational fluid dynamics, she has a passion for optimizing quantitative models and automating data-driven processes. Realizing that she could combine her deep interest in math and graphics, she transitioned to Data Science to be on the forefront of next-generation AI. Jostine joined SailPoint in the early stages of IdentityAI, a SaaS identity analytics solution, and has been focusing on applying machine learning to solve emerging challenges and refine existing processes in the field of IGA. She has successfully brought several innovations from concept to working prototypes for use-cases in peer group analysis and role mining.

Noa Ruschin-Rimini, Founder & CEO, Grid4C

Noa holds a Ph.D. in Artificial Intelligence and Machine-Learning, specializing in anomaly detection and predictive analytics of time series. Roa's current company, Grid4C, was founded in 2013 with the vision of using Artificial Intelligence in order to extract maximum value out of smart meter and IoT data, for the purpose of optimizing the energy supply chain. Alongside running one of the industries leading AI solutions providers, Noa has also published patents in the field as well as publishing various prestigious papers on Fractal Geometry whilst also working as a research member for LAMBDA in Tel Aviv, a city recognised as one of our AI Cities to watch in 2020!

Narmada Parthasarathy, Data Engineering & Analytics, All State

Having held managerial positions in engineering at Santander, Bank of America and Allstate, Narmada has significant experience in the financial industry leading teams of data technologists toward the next generation of 'big data'. Prior to working in industry, Narmada received her Bachelor of Engineering in Computer Software Engineering from Madurai Kamaraj University. With interests in Data Engineering, Data Science, Artificial Intelligence and building Self-service Analytics Platforms, Narmada is someone we believe you should be following if interested in the engineering side of Fintech!

Natalie Berestovsky, Director of Data Science, Bill.com

Natalie received her PhD in Computer Science from Rice University in 2013 before embarking on a a career in AI, first working at ExxonMobil in the developer team as an intern before holding Data Science positions at Chevron, Anadarko & Bill.com. Whilst most of Natalie's early research focussed on supporting the medical field, Natalie later moved toward the Oil & Gas industry, which she had previously suggested to be a natural transition to another empirical field (oil & gas) in need of computational analysis and modeling in a previous interview. Interested to hear more? Some of Natalie's previous summit presentations are available to watch on YouTube and many research journals can also be found on ResearchGate here.

Anisha Kaul, ML/AI Eureka Special Interest Group Leader, Schlumberger

With one of the more interesting job titles on the list, Anisha currently works in the Machine Learning department of Schlumberger, the leading provider of technology and services to the energy industry across the world. As with many on this list, Anisha finds herself in the thriving Oil & Gas industry, having also previously worked at  the Society of Petroleum Engineers as Vice Chair. Anisha's current role mainly focusses on building Machine Learning models and harness the big data infrastructure to solve problems.

Priya Aswani, Data Science Architect, Microsoft

With over 13 years industry experience, Priya works predominantly in information security analytics, developing insights on consumer and market trends through data-driven intelligence. Currently working as a AI and IoT Technical Strategy Leader at Microsoft, Priya leads the global Data Engineering, AI and IoT technical strategy and the technical specialists in each region of the world from both the product and commercial standpoint remotely from Houston. This role gains the experience of Priya's previous role at IBM as DevOps and Analytics Technical Product Manager. Priya's technical expertise is hard to ignore when her key skills include proficiency in Jenkins, JIRA, Ant, Grunt, Maven, ELK stack, Docker containers, Cloud Foundry Containers, TFS, Git and more, meaning that we couldn't ignore Priya's technical expertise.

Amy Gross, Founder & CEO, Vinesleuth

Founder and CEO of VineSleuth, Amy Gross created a platform which uses sensory science, cognitive computing and excruciatingly accurate wine data to assist wine retailers in growing basket size and selling more wine to the right shoppers. The platform offers truly personalized shopping experiences in store and online. From sheer passion alone, Amy sourced a team that were able to turn a passion for customer service and a good bottle of red into a platform which saw a new use for AI! You can see Amy discuss her business model and the development of Vinesleuth here.

Kelly Zaleski, Chief Engineer of Intelligence, Raytheon

Having worked at Raytheon for over 25 years, Kelly has undertaken roles varying from Rapid Equipment Deployment Manager to Chief Engineer for Advanced Technology. Having completed her BSc at the University of Rochester in Electrical Engineering, Kelly went straight to work for the cybersecurity company. The variation of roles has seen Kelly spend her fair share of time in the classroom, transitioning from spending the first 10 years of her career in the lab, to later heading up the problem solving management role she currently finds herself in.

Julia Badger, Autonomous Systems Technology Discipline Lead, NASA

The current Autonomous Systems Technology Discipline Lead at NASA has held a variety of roles in her 11 years working there. Having received a Bachelor's of Science in Mechanical Engineering from Perdue University and PhD in the same subject from CalTech, Julia joined NASA, beginning her career at the Johnson Space Center. With roles from Robonaut Project Manager to Autonomous Systems Lead, Julia manages a diverse portfolio of projects, including flight projects, research and development, and spacecraft program systems engineering. Julia's career at NASA has gone from strength to strength, stemming from a mere interest in problem solving to programming the first humanoid robot in space.

Jean-leah Njoroge Ph.D, Senior Data Scientist, DELL

With a PhD in Computational Material Science and Engineering, Jean-leah studied combined physics, chemistry, and mathematics prior to becoming a Data Science Fellow at Insight Data Science in New York. It wasn't until 2018 that Jean-leah moved to Texas to join Dell EMC as a Senior Data Scientist, during which time she has utilised and built on skills in various programmes including Python, R, SQL and a variety of Machine learning techniques. Jean-leah is a firm believer in improving the world through science & documents many of her thoughts on her blog.

Nanthini Balasubramanian, Data Scientist, NVIDIA

Graduating with a Degree in Computer Science from the University of Pennsylvania, Nanthini started her career teaching Data Science, leading both Biological Data Sciences and Big Data Analytics units at the UPenn. During this time, Nanthini was also the Vice-President of the Penn Data Science Group, which focused on conducting workshops and talks to encourage the interest in Data Science. Now at NVIDIA, Nanthini is part of the RAPIDS team accelerating Machine Learning algorithms on GPU to develop the Data Science process. Current works including the acceleration of ML algorithms on GPU, profiling existing workflows and identifying areas of improvements in cuDF take up much of her time as well as being involved in the bench-marking process to spot improvements/reduction in performance.

Catalina Herrera, Senior Data Scientist, TIBCO

Equipped with a passion for data and analytics, Catalina completed her MSEE in Advanced Electronic Engineering at Texas University, going on to begin her career as Product Engineer at Texas Instruments. In her entire career, Catalina has been exposed to state-of-the-art technology solutions across multiple industry verticals, becoming a Product Evangelist & Data Scientist in the SaaS industry. With both educational and technical roles to her name, Catalina now works full-time as a Senior Data Scientist at TIBCO, the Connected Intelligence Cloud service provider.

Hediyeh B Ledbetter, Data Scientist, Dell

As the owner of two M.S. degrees in computer science of data mining & management information systems alongside 6 years of industrial software engineering experience, Hediyeh has held several roles based around the use of data, including being a research assistant at Lamar University, Software Developer at ATR & Data Science Fellow at Springboard before joining Dell in May of 2018. With a passion for continuous development and problem solving, Hediyeh has invested considerable time in select areas of Data Science, including, but not limited to Data Mining, Python (Pandas, Numpy, Matplotlib, Seaborn, Scikit-learn, Scipy), Spark, Hadoop, C#, JavaScript, Oracle. See more on her Github here.

Ji (Sylvia) Qi, PhD, Senior Data Scientist, USAA

The former Teacher & Physicist currently holds a Senior Data Science position at USAA, the company responsible for providing insurance, banking, investments, retirement products and advice to more than 12 million current and former members of the U.S. military and their families. Since achieving her Ph.D. in Electrical and Computer Engineering, Sylvia has gone on develop industry experience in Machine Learning (clustering, classification, regression, neural network, ensemble methods, feature engineering), Python (scikit-learn, numpy, scipy, pandas), statistical analysis, data visualization. This development had been facilitated by previous research experience gained at the University of Arizona & TOTAl including Raman spectroscopy,SERS, optical imaging, Raman sensor, optical sensor, image processing.

Xiao (Rita) Tian, Staff Data Scientist, Visa

Formerly a teaching assistant at the University of Texas, Rita re-joined Visa as Staff Data Scientist at the end of last year having previously interned in mid-2018. The Petrophysicist has a passion for developing problem-solving skills for real-world problems & holds proficiency in a range of programming languages (scikit-learn, Pandas, Numpy,Scipy, Seaborn, MATLAB, R, Scala. Rita also has a strong statistics background, experienced with Hypothesis Testing, T-tests, F-tests, ANOVA, Chi-square test. Alongside her technical work, Rita has co-authored a variety of papers on range of topics from clustering algorithms applied to fluid characterization to detection for digital images using machine learning algorithms and image processing.

Shuling Liu, Data Scientist, Apple

With extensive modeling and data manipulation experience in Python and R, and hands-on training experience in Spark and Scala. SAS and SQL, Shuling is passionate in seeking insights the right way - by leveraging the statistical inference and machine learning algorithms. Shuling considers herself to be curious and innovative, with the goal of never stopping learning. This passion has seen Shuling take both Senior Data Scientist & Data Scientist positions at Capital One and Apple Respectively. With proficiency in Gradient Boosting, Survival Data Analysis, Regularized Logistic Regression as well as Text mining, Experiment Design and sampling, Principle Component Analysis (PCA) and Clustering, Shuling's work is definitely something to keep up with.

Amy Daali, Founder & CEO, Lucea AI & Deep Learning

Having completed her Ph.D. in Electrical Engineering, Amy transitioned between Research and Engineering positions before moving into a Data Scientist role at USAA back in 2017. Since then, Amy has taken on three roles, primarily as Founder and CEO of Lucea AI, but also organising the Women in Machine Learning and Data Science collective of San Antonio & acting as chair for the IEEE Engineering Medicine and Biology Society.  Using her experience in Predictive analysis, applied Mathematics, Machine Learning and Engineering, Amy aims to make healthcare more human, empowering healthcare providers and organizations to make better life-changing decisions through AI.

Anna Chaney, Engineering Director - Machine Learning, Resideo

After received her BS in Mathematics and a MS in Computer Science from the University of Colorado & University of Arizona respectively, Anna pursued a career in engineering which began at the National Optical Astronomy Observatory.  In the following ten years, Anna held Engineering and Data Science positions at Raytheon, ARL:UT and IBM, where she took her breadth of machine learning knowledge in applied research to the IBM Watson group. After just over five years at IBM, Anna moved to Resideo at the end of 2019 where she currently works as the Engineering lead for software development of the Buoy Whole Home Water Controller.

Huihui Yang, Data Scientist, Shell

Having interned at Insite360 as Bi Data Science Python Developer following her graduation from the University of Houston, Huihui moved to Shell, initially as a Data Analyst, later switching over to Shell's Data Scientist team having honed her skills in Drilling data analyzing, cleaning and processing (with numpy, pandas, matplotlib, etc.). Alongside her current work, Huihui has found time to co-author four papers in the last two years, covering CNNs, Quasi-sychronization, Mobile Sensing and more.

Michele Saad, Data Scientist/Machine learning Researcher, Adobe

Research internships at the University of Sherbrooke, Telefonica, Apple and Intel Corporation aided Michele in developing skills learnt during her Electrical and Computer Engineering PhD. Data Scientist/Machine Learning Researcher positions followed at CoginitiveScale & Adobe respectively, seeing her move between the US and UK before finally settling in Austin once more. Michele's lists her main areas of focus as Machine learning, Data mining, Computer Vision, Perceptual algorithms and Image and video quality assessment, on which she has collaborated on over 40 articles, all of which are available here.

Smita Menon, DevOps Engineer, Shell

The MS Computer Science graduate from University of Texas has held lead/senior positions in Software & DevOps Engineering at Texas Instruments, Cisco & Shell. To date, Smita has managed and executed the testing of Cisco’s automation software initiatives such as Cisco Intelligent Automation for the cloud, designed and implemented the deployment infrastructure for various teams within Cisco cable, video and mobility, actively participated in the complete QA life cycle from Conception to Release of the Desktop Software using Agile development methodology and more. You can keep up with Smita and her work here.

Qiuhua Liu, Senior Artificial Intelligence Engineer, Schlumberger

The Duke University graduate, Qiuhua, has held various industry positions including as a Researcher, Machine Learning Scientist & Senior AI Engineer. Her current role at Schlumberger has seen projects spanning Drilling Automation, Deep Neural Network, Applied Signal Processing Algorithm and more. During this time Qiuhua developed her varied skillset which includes Deep Reinforcement Learning, Computer Vision, semi-supervised learning, Support Vector Machines, Bayesian Networks, Kalman/Particle Filter, Neural Networks. Qiuhua also boasts a plethora of programming languages knowledge, including, but not limited to Python, MATLAB, PDDL, C/C++, SAS, R.

Coraly Romero-Principe, DevOps Engineer, Blackboard

The current DevOps Engineer has also held Senior Test Engineer and Software QA Engineer positions in Texas and had also held a Staff Software Engineer position at IBM for nine years covering Functional Verification, System Verification and Software testing. Coraly's current role at Blackboard, the original player in the higher education software space with many innovations for storage, communication and coursework planning, aims to enhance user experience through data. Keep up with Corlay's work here.

Mubassira Khan, Artificial Intelligence/Machine Learning Scientist, General Motors

The current AI/ML lead at General Motors has previously held positions as a Lecturer, Research Assistant and Project Engineer having graduated from the University of Texas with a Ph.D. in Transportation Engineering. Mubassira has also been publishing papers since 2010, most recently covering the topic of tour chaining patterns of urban commercial vehicles. Other papers of note include Application of choice modeling methods to describe commercial vehicle travel behavior in urban areas & Potential Crash Reduction Benefits of Shoulder Rumble Strips on Rural Highways in Idaho.

Tianxia Zhao, Machine Learning Lead, Shell

Having previously held Data Scientist positions at Schlumberger, Accenture & Apex Systems, Tianxia currently works as Machine Learning Lead at Shell, utilising her skills in Data Analytics, Machine Learning, Deep Learning, Big Data, Petroleum, Antennas, Data Analysis, Multiphysics Modeling, ML, numerical analysis, Physics Modeling, PHM and more. Publication wise, Tianxia has papers on topics from electromagnetic propagation measurements to the Effects of Manufacturing Artifacts on Infrared Filter Performance. You can keep up with Tianxia's work here.

Carol Reiley, Co-founder, drive.ai

Formed out of Stanford’s AI Lab, drive.ai builds Deep Learning software for self-driving cars. As co-founder and president, Carol led the product team, built investor relationships to raise over $70 million and led the company strategy. Carol has eight technical patents, and is the author of more than a dozen papers published in various scientific conference proceedings, refereed journals and conferences, with a research focus on ‘intelligent robotic systems that can aid humans in performing skillful tasks more effectively.’

Alicia Kavelaars, CTO & Co-founder, OffWorld

Alicia has over 15 years of experience in the aerospace industry, developing and successfully launching systems for NASA, NOAA and the Telecommunications industry. In 2015, Alicia made the jump to New Space to work on cutting edge innovation programs. At OffWorld, Alicia has led the development of AI based rugged robots that will be deployed in one of the most extreme environments on Earth as a precursor to swarm robotic space operations: deep underground mines.

Amy Gershkoff, Chief Data Officer, Bitly

Amy was named one of America’s “40 Under 40” leading entrepreneurs, one of the Top 50 Women to Watch in Tech, and one of San Francisco's Most Influential Women in Business. Amy and her team leverage robust global data and advanced analytics and machine learning capabilities, we provide companies with unparalleled insights into the market landscape.

Angela Sy, Head of AI & Strategy, Focus Global

Angela graduated from Stanford University with a B.S. in Computer Science & Artificial Intelligence, and a M.S. in Management Science & Engineering. Whilst studying for her degrees Angela built up a breadth of experience, including internships at Salesforce and Indiegogo, as well taking part in the Design for Extreme Affordability cohort, designing products to aid some of the world’s poorest citizens. Angela joined Focus Global in August 2018 and is currently leading the data-driven accounts team.

Ayse Naz Erkan, ML Engineer Manager, Twitter

During her PhD studies in computer science in New York, Ayse worked on a range of robot vision problems under the supervision of AI pioneer Professor Yann LeCunn. In 2011 Ayse joined twitter as a Software Engineer, and is now the ML Engineering Manager. Ayse has also expressed her interest in the issue of ethics in Machine Learning, having initiated the ML Ethics effort at Twitter, which she also leads.

Catherine Lu, Managing Partner, Alumni Ventures Group

Catherine is an entrepreneur-turned-investor. She is currently a Managing Partner at Alumni Ventures Group and Principal at Spike Ventures, a VC firm that invests in Stanford alum-led companies. Previously, she was Director of Product at NEA-backed Datavisor, an enterprise company offering an unsupervised machine learning fraud solution. Prior to Datavisor, she co-founded the retail analytics company Fancy That, which was acquired by Palantir in 2015. Catherine graduated from Stanford with a BS and MS in Computer Science, focusing on artificial intelligence.

Cathy Pearl, Head of Conversation Design Outreach, Google

Before joining Google, Cathy was the VP of user experience at Sensely, whose virtual nurse avatar, Molly, helps people engage with their health. Cathy is the author of the O’Reilly book “Designing Voice User Interfaces”. Throughout her career, Cathy has applied her knowledge to a range of projects, and has worked on everything from helicopter pilot simulators at NASA to a conversational iPad app in which Esquire magazine’s style columnist tells you what you should wear on a first date. During her time at Nuance and Microsoft, Cathy designed VUIs for banks, airlines, and Ford SYNC. Cathy holds a BS in cognitive science from UCSD and an MS in computer science from Indiana University.

Cindi Thompson, Co-Founder & CEO, Climate Companion

Since completing her PhD in Computer Sciences at The Uni of Texas in 1998, Cindi has built a wide range of academic and industry experience in artificial Intelligence, including Machine Learning and Natural Language Processing. She has produced many publications including and is the co-inventor of three patents, including the System and Method for Comparing and Reviewing Documents. Cindi also founded Climate Companion, a technical platform for the development, discovery, and defense of solutions to climate change, in September 2019.

Emma Brunskill, Assistant Professor, Computer Science, Stanford

Emma is a faculty member of the Stanford Statistical Machine Learning group and the AI Lab, having joined the Computer Science department in 2017. Prior to Stanford, Emma was the Associate Professor of computer science at Carnegie Mellon University. Over her career, Emma has written and co-written many papers, which have received numerous nominations and awards, including the Best Paper Award at the Uncertainty of Artificial Intelligence in 2017.

Fiona McEvoy, Tech Ethics Researcher and Founder, YouTheData.com

With the topic of ethics being such a key area in Artificial Intelligence, Fiona’s work plays an important role in exploring the relationship between technology and society. Fiona holds a graduate degree in Philosophy, with a special focus on ethics and technology. Fiona also runs YouTheData.com, a website that attempts to translate topical tech ethics conundrums for "non-techie" audiences. She also writes in the media for publications including Slate, VentureBeat, and a selection of popular Medium blogs.

Jia Li, Adjunct Professor, Stanford University

In 2011 Jia received her PhD in Computer Science at Stanford University, and in February she returned as an Adjunct Professor in the School of Medicine, exploring how AI can be used to improve the outcomes of patients and hospitals. Jia is also the Head of R&D at Google Cloud AI, where the focus is to use aI to solve real world problems. Prior to joining Google, Jia was the Head of Research at Snap and between 2011 and 2015 Jia led the Visual Computing and Learning Group at Yahoo! Labs, where she was the recipient of numerous awards, including the 2014 Mater Inventor Award, for contribution of innovation in Computer Vision, Machine Learning and Image Search.

Katie Driggs-Campbell, Assistant Professor, University of Illinois

Katie is currently a Assistant Professor at the University of Illinois having previously worked as a postdoctoral Research Scholar at Stanford University. Prior to that, she was a PhD Candidate in Electrical Engineering and Computer Science at the University of California, Berkeley, advised by engineer and computer scientist, Professor Ruzena Bajcsy.  Prior to that, she received a B.S.E. from Arizona State University in 2012 and a M.S. from UC Berkeley in 2015. Katie's current career goals involve developing new methods for human-robot interaction, specifically focusing on predicting and modeling behaviors for control of smart cars.

Mariya Yao, CTO and Head of R&D, Metamaven

Mariya is the CTO and Head of Research & Design at Metamaven, an AI strategy & development company building machine learning solutions for Fortune 500 customers and leading brands like L'Oreal, LinkedIn, and Paypal. She also splits her time as the Editor in Chief at TOPBOTS, a publication and community for enterprise AI executives and professionals. Mariya also co-authored the book Applied Artificial Intelligence: A Handbook For Business Leaders and writes for Forbes about enterprise AI.

Negin Nejati, Software Engineer, Google

Negin Nejati received her PhD in Electrical Engineering from Stanford University, where her thesis focused on Machine Learning and Cognitive Sciences. She joined Apple Maps in 2013 where she led the geosearch effort building a query understanding Machine Learning model and geo search backend. Negin then moved to Airbnb in 2016 and later Google in September 2019 as a Software Engineer. Negin enjoys building end to end products and her focus is on Natural Language Understanding.

Rekha Joshi, Principal Software Engineer, Microsoft

Before joining Microsoft in 2018, Rekha was a Principal Software Engineer at Intuit, where she worked in the central technology group. Along with creating numerous publications, Rekha has also invented 5 patents, including Dynamic Reputation Score For a Digital Identity in 2017. Over her career, Rekha has worked in various domains of finance, supply chain and AI research.

Rosanne Liu, Senior Research Scientist, Uber AI Labs

Rosanne is a Senior Research Scientist and a founding member of Uber AI Labs. She received her PhD degree in Computer Science from Northwestern University. After graduating, Rosanne joined a research oriented AI startup, Geometric Intelligence. This involved working with a small groups of people on general AI algorithms. The company was later acquired by Uber Technologies Inc. to become Uber AI Labs. Her research interests include neural network interpretability, object recognition and detection, generative models, and adversarial attacks and defence in neural networks.

Shelley Zhuang, Founder and Managing Partner, 11.2 Capital

Shelley has over ten years of experience in technology as a software engineer, research scientist, business executive, and venture capitalist. She holds a BS in Computer Science and Computer Engineering from the University of Missouri, and a PhD in Computer Science from the University of California, Berkeley. Previously, Shelley was a Principal at DFJ, where she was actively involved in a number of investments including Ecoplast Technologies, FeedBurner (acquired by Google for $100M) and Flurry (acquired by Yahoo for $240M). Shelly is currently a G7 Fellow at Creative Destruction Lab, and serves on Enigma 2016's program committee.

Shivani Rao, Senior Applied Researcher, LinkedIn

Shivani currently works in the Learning Relevance Group at LinkedIn, which integrates online learning into the platform, ensuring members gain the skills they need for their career. Shivani has accrued research experience in Industry and academia in areas of Machine Learning, Data Mining and Computer Vision. Outside of R&D work, Shivani also engages with the larger technical community, by writing and speaking and serving on the organizing committee of workshops and conferences. Shivani is also passionate about mentoring and supporting women in tech.

Sowmiya Chocka Narayanan, Co-founder and CTO, Lily AI

Lily AI is an emotional intelligence powered shopping experience that helps women discover clothes. At Lily, she has built the key engines using deep learning and machine learning algorithms. Prior to Lily, she worked at different levels of the tech stack at Box leading initiatives in - building SDKs, applications for industry verticals & MDM solutions. She was also an early engineer at Pocket Gems where she worked on the core game engine and built acquisition and retention strategies for #1 & #4 top grossing gaming apps. Sowmiya is a UT Austin grad with Masters in Electrical and Computer Engineering.

Stacey Svetlichnaya, Deep Learning Engineer, Weights & Biases

Previously at Flickr & focused on improving image search and discovery via deep learning, Stacey now works on Building flexible developer tools and visualizations to improve accessibility, transparency, and collaboration in deep learning at Weights & Biases. Prior to Flickr, Stacey helped develop a visual similarity search engine with LookFlow, which Yahoo acquired in 2013. Stacey holds a BS and MS in Symbolic Systems from Stanford University.

Terah Lyons, Executive director, The Partnership on AI

The Partnership on AI aims to establish the best practices on AI technologies, and to serve as an open platform to discuss the technology, and its influence on people and society. Since May 2017, Terah has been a Technology Policy Fellow at the Mozilla Foundation, and is also a member of the Board of Directors at the Harvard Alumni Association. She previously served as Policy Advisor to the U.S. Chief Technology Officer at the White House Office of Science and Technology Policy. While serving as Policy Advisor Terah led a policy portfolio in the Obama Administration White House focused on emergent technology related to Machine Intelligence, including Artificial Intelligence, robotics and more.

Tessa Lau, Founder/CEO, Dusty Robotics

Tessa has a breadth of experience covering a range of areas, including robotics, computer science, Machine Learning and data analytics. In April 2018, Tessa founded Dusty Robotics, a company which builds high-precision robotic tools to automate valuable tasks on construction sites.

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