Last September, we brought the Women in AI series to the city with the inaugural Women in AI Reception, providing the opportunity to hear from some of the leading female experts within the industry whilst networking amongst peers. In the lead up to the events, we seized the opportunity to look into some of the most exciting work within AI taking place in New York, and wanted to share with you some of the most influential women behind these progressions.
Here are 5 women that we think have particularly helped with the progression of the technology, whether it has been with helping to develop AI, apply AI for Good, or raise conversation around the technology.
Professor, 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.
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.
Co-director, 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.
Technical Program Manager, Facebook
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.
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. Tara joined RE•WORK back in 2016 when she spoke about her work at the Machine Intelligence Summit in New York.
Co-founder & CMO, TOPBOTS
TOPBOTS advises and helps businesses adopt machine learning and artificial intelligence techniques. TOPBOTS.com is a community where professionals come together to learn about applied machine learning and automation solutions. Adelyn is also a contributing writer to Forbes and Venturebeat, and has been recognised as one of the top 25 People to Follow in AI by IBM and Top 10 People in AI by Forbes. Adelyn is also the co-author of Amazon bestseller "Applied Artificial Intelligence," which is also one of CES's Notable Books of 2018.
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'.
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.
Machine Learning Engineer, Spotify
At Spotify Catie works on personalizing content on Home. Originally from Chicago, Catie received her BSE in Computer Science from the University of Michigan’s College of Engineering. Now living in New York, Catie is the Co-Founder of Code Squad, a non-profit organization dedicated to bringing computer science education to underrepresented middle schools across Washington, DC. Catie will be speaking about her work personalizing explainable recommendations, and some of the technical challenges this problem presents at the Women in AI Reception in September.
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.
Co-founder & Chief Operating Officer, Sigma Ratings
Gabrielle will be speaking at the AI in Finance Summit in New York in September. 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.
Chief Analytics Officer & Head of AI and MI, 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.
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.
Senior Software Engineer, Etsy
Jessica became a Senior Software Engineer at Etsy in May, since joining the company in 2016. Jessica has also 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.
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.
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). Kadija’s research includes the promise and potential pitfalls of data collection and analysis in precision medicine. Kadija spoke at the Machine Intelligence Summit in 2016.
Product Owner, 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.
Senior Vice President, Artificial Intelligence, Bank of America
Lyndsay joined Bank of America in 2011, and in 2017 became the Senior VP, Artificial Intelligence and Erica Project Manager. Erica is a chatbot that can help user check balances, send reminders about bills, answer your bank-related questions and help customers make smarter decisions.
Senior Data Scientist, BuzzFeed
Lucy’s work involves machine learning tools for optimizing audience reach and engagement. She holds an MS in Computer Science from Columbia University where she performed research on social networks and information diffusion. Lucy completed graduate work in machine learning with research on information diffusion. She is a full-stack data scientist and manager keen on solving emerging machine learning problems. Her interests in AI include social networks, NLP, and deep learning.
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.
Vice President in Analytics & Data, Morgan Stanley Wealth Management
Peggy is Vice President in the Analytics & Data department at Morgan Stanley Wealth Management. She is responsible for leading the adoption of Data Governance standards and processes across Wealth Management. She works closely with Technology, Business Stewards and Enterprise to improve data quality issues that impact the business. In addition, Peggy works on initiatives to leverage machine learning to improve the capture of data assets across the firm.
Director, Artificial Intelligence Accelerator, PWC
As co-lead of the Artificial Intelligence Accelerator, Pia’s responsibilities include overseeing internal AI research, leading partnerships with top research universities and advising clients on AI strategies. Alongside this, Pia is also currently 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 modeling, machine learning, optimization, natural language processing and decision sciences.
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.
VP, Machine Learning Engineering, Hearst
Rahel is the Director of Data Science at Hearst. She holds a MS in Mathematics from NYU and a PhD in Economics from Princeton. She has worked in finance for 20 some years as a quant, risk manager and trader. She has been working with machine learning algorithms at scale since 2010, building models and advising Fortune 100 companies. She joined Hearst in 2015 and leads their data science team. She works with content, clickstream, ad, audience, off-platform data using numerous machine learning algorithms including Natural Language Processing and Topic Modelling. Rahel spoke about her work at the Deep Learning Summit in San Francisco in 2017.
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.
Software Engineer, Pivotal Software
Sanhita completed her masters in Information Science at Cornell University in 2016. She is currently a Software engineer at Pivotal Software, a company that helps large companies adapt to change in order to deliver high standards of user experience. Prior to joining Pivotal software, Sanhita was a Software Engineer at BlackRock, where she Designed and developed a real time monitoring tool for all the applications and servers inside ALADDIN.
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.
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.
Principal Machine Learning Engineer, 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.
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 modeling, inference, computing, and graphics.Vivian is also the CTO and Chief Data Scientist of NYC Data Science Academy.
If you’d like to hear from leading women who are helping advance AI, be sure to subscribe to the RE•WORK Women in AI Podcast. Previous guests include experts from Facebook, McGill University, LinkedIn who have discussed a range of topics including psychologically aware AI, personalised healthcare and the commercialisation of deep learning.
If you would like to hear from some of these women , then join us at one of our Women in AI events. These events are open to both men and women for an evening of networking and discussions surrounding some of the key areas of the rapidly advancing technology, supporting women in the industry.
Don’t forget to sign up for the Deep Learning 2.0 Virtual Summit 2021!