Diversity in AI is non-negotiable. Not only from the perspective of providing equal opportunities to the workforce, but to help prevent skewed and biased machine learning algorithms from being rolled out to the general public. In the UK, the government has made AI and data science one of the four pillars of its Industrial Strategy, demonstrating the impact it’s going to have on building a Britain fit for the future. ’The office, working with the AI Council, will lead work to increase awareness of the advantages of advanced data analytic technologies and promote greater diversity in the AI workforce.‘ As a female led company, RE•WORK has been supporting women working in AI for several years through Dinners, networking events, the Women in AI Podcast and more. In advance of the Deep Learning Summit in London this September 19 - 20, we’re taking a look at some of the leading ladies transforming their industries with AI in the UK.
We also reached out to some of our network of AI experts who recommended some of their top picks for this list.
- 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. Raia has spoken at RE•WORK Summits and has also appeared as a guest on the Podcast discussing Deep Reinforcement Learning in Complex Environments, which you can listen to here.
- 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, Director of Research, Spotify
Mounia is a Director of Research at Spotify, and the 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. Mouina spoke at the Women in AI Dinner in London, and you can read the highlights here.
- Katja Hofmann, Senior Researcher, Microsoft
Katja is a Senior 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. Katja will be speaking at the Deep Learning Summit in London this September.
- 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. Verena is joining us at the AI Assistant Summit this September to speak on ‘Machine Learning for Conversational Assistants: How far can we get?’
If you’re interested to hear from some of the leading women in AI, register for any of RE•WORK’s upcoming Summits with the discount code SUMMER25 to save 25% on all passes. Buy your ticket before August 23 to guarantee your place at a discounted rate.
- Kriti Sharma, VP, AI, Sage
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. She is currently the vice president of artificial intelligence and ethics at Sage Group, one of the UK’s largest tech companies.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
Recommended by Noura Al Moubayed
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, Principal Data Scientist, Carlson Wagonlit Travel
Recommended by Anna Kwiatowski
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
Recommended by Elena Kochkina
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, Alan Turing Institute
Recommended by Elena Kochkina
Chanuki is a visiting data science 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, Research Scientist, NASA Frontier Development Lab
Recommended by Alison Lowndes
Valentina is a data scientist with commercial and research experience in machine learning. PhD in Physics with focus on Bayesian statistics and computational methods. She has been a member of the NASA/ESA team experiments for 5 years.
- 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 neighborhoods 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, Lead Software Engineer, Shell Energy
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 a lead software engineer in the R&D department of First Utility, the UK's largest independent energy provider, supplying gas and electricity to around one million UK homes.
- Kallirroi Dogani, Machine Learning Scientist, ASOS
Kallirroi’s recent work focuses on size recommendations in fashion e-commerce as well as improving the quality, novelty and diversity of product recommendations. She 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.
- Alice Piterova, Head of Privacy, Hazy
Alice has over 10 years of experience in business development and product management, digital marketing and communications, research and policy, sales strategy and account management, and a particular focus on such fields as artificial intelligence, innovation and digital transformation, big data and tech for good. Having worked in national and international public and private sector organisations, social enterprises and NGOs, Alice brings a proven track record in delivering growth and showcasing impact, as well as engaging with a wide range of stakeholders.
- Noor Shaker, Co-Founder & CEO, GTN
Before starting GTN, 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. At GTN, she is working with leading researchers on a novel, patent-pending, technology to drug discovery bringing ideas from quantum physics and machine learning.
- 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, Alan Turing Institute
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 here 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.
- Catherine Breslin, Director, Solutions Architect, Colbat Speech and Language
Catherine is a machine learning scientist and manager. 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 & Deputy Director, 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). She received the World Technology Award for Ethics acknowledging the originality and her research on the ethics of cyber conflicts, and the social impact of the work that she developed in this area. Since 2016, Taddeo serves as editor-in-chief of Minds & Machines (Springer) and of Philosophical Studies Series (Springer). She is also Fellow of the Council on the Future of Cybersecurity of the World Economic Forum.
- Caryn Tan, Analytics Strategist, 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, Co-Founder, Selerio
Flora is co-founder of the AR startup Selerio, and a recent Ph.D. graduate in Computer Vision at the University of Cambridge. Her publications in several top-tier venues cover topics at the intersection of Graphics, Vision, and NLP such as sketch-based modeling or joint analysis of images and text for 3D retrieval. She 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).