See our Women in AI Directory for 2020 here!

With 2019 coming to a close, we're back with the last instalment of our Women in AI lists of this year, this time focussing on Women that we believe have spearheaded or taken part in some great research in 2019 and therefore deserve recognition. It was a near impossible task to only pick 30 inspirational women, but we hope you find some new women in STEM to follow on the below blog! Not seen our previous lists? You can see our Top Women in AI lists for the UK, 30 under 30, USA, Canada, Montreal, New York, San Francisco, Boston and more here.

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1. 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.

2. 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.

3. 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.

4. Noor Shaker, CEO/Founder, Phenogeneca

Having previously worked as a Professor of AI and Machine Learning at Aalborg University in Denmark, Noor moved back to industry as founder of Phenogeneca, a company set to disrupt health tech and life sciences. With over fifteen years experience in AI and Machine Learning, Noor holds a real passion for changing the world through interdisciplinary technological innovations, believing that data is the future of Healthcare development, not only in the UK, but around the world. Whilst working full-time, Noor has also managed to secure a number of patents across industry and complete over 50+ publications leading her to be named as one of the leaders in the healthcare field by Forbes.

5. Maja Matarić, Distinguished Professor and Vice Dean for 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.

6. 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. Also co-authoring three papers in 2019, it has been a busy one for Georgia!

7. 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.

8. 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.

9. Fei-Fei Li, Inaugural Sequoia Professor, Stanford University

Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, Co-Director of Stanford’s Human-Centered AI Institute and co-founder of AI4ALL, a national nonprofit organisation dedicated to educating a diverse group for the next generation of AI technologists, thinkers and leaders. Fei-Fei has had a busy 2019, authoring and co-authoring over thirty papers, a majority of which cover her main research areas which include Machine Learning, Deep Learning, Computer Vision and Cognitive and Computational Neuroscience.

10. 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.

11. Sarah Jarvis, Head of Data Science,

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 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!

12. 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.

13. 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.

14. 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.

15. 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.  

16. 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.

17. 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.

18. Dr. Radhika Dirks, CEO & Co-founder,

Since graduating in 2010 with a PhD in Quantum Computing, Dr Dirks has been involved in various AI projects, as both CEO at and as an AI advisor at Katapult accelerator, alderan and 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.

19. 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. It has been a busy year for Dorsa who has co-authored 19 papers in 2019 which you can read more on here.

20. 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.  

21. 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.

22. 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.

23. Hanna Wallach, Senior Principal Researcher, Microsoft  

As a leading mind in her field, Hanna develops machine learning methods for studying the structure, content, and dynamics of social processes using digitized information. Hanna's cross-collaborative approach to research has seen her work with political scientists, sociologists, journalists, and lawyers as well as the US Government. Aligning greatly with our values, Hanna is also a huge voice for the underrepresentation of Women in STEM fields, co-founding two incentives to combat this, including Debian Women and Outreachy. She also co-founded the annual Women in Machine Learning Workshop, which is now in its fourteenth year.

24. 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.

25. 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.

26. Daphne Koller, CEO, Insitro

Daphne Koller is the CEO and Founder of insitro, a startup company that aims to rethink drug development using machine learning. She is also the Co-Chair of the Board and Co-Founder of Coursera, the largest platform for massive open online courses (MOOCs). Daphne was the Rajeev Motwani Professor of Computer Science at Stanford University, where she served on the faculty for 18 years. She has also been the Chief Computing Officer of Calico, an Alphabet company in the healthcare space. She is the author of over 200 refereed publications, with her work appearing in publications such as Science, Cell, and Nature Genetics.

27. Rachel Thomas, Founder,

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, 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.

28. 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.

29. 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.

30. Devi Parikh, Co-Founder, Caliper  

Working as both a Co-Founder of Caliper, Assistant Professor at Georgia Tech University and Research Scientist at Facebook, Devi has had a very busy year, especially when you take into account that in this year alone, Devi has authored or co-authored over thirty research papers. Devi's main research interests include computer vision, natural language processing, embodied AI, human-AI collaboration, and AI for creativity, research on which led to Devi being the recipient of many awards including an NSF CAREER award, an IJCAI Computers and Thought award, a Sloan Research Fellowship, an Office of Naval Research (ONR) Young Investigator Program (YIP) award and more.

Interested in networking with inspirational Women in AI? We run monthly Women in AI dinners, bringing together some of the brightest minds in each city for an evening of discussion, networking, keynote talks and a three-course meal with bubbles. You can see more on these dinners here.

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