By Yazmin How, Digital Content Manager — RE•WORK

March 08, 2019

“Women make up only a quarter of computer scientists, their numbers appear to be even smaller in the AI field in particular.” — The Atlantic

Encouraging the next generation of AI experts to start their work in the field is essential for young people of all genders, ethnicities and backgrounds. The computer science world is still vastly male dominated and this, of course, translates directly into roles in AI. At Google, 21 percent of technical roles are filled by women, according to company figures released last June, and in their 2018 diversity report, Facebook said that only 22 percent of its technical workers are women. As well as the immediately obvious concern of unequal opportunities for girls entering the field, there are deeper concerns with limited opinions going into programming which can lead to biased systems. Algorithms inherit bias based on the programmers who build the AI e.g. images of people shopping and washing are mostly linked to women, for example.

Programs such as Girls Who Code, The Knowledge Society and AI4ALL are providing opportunities to young people from a variety of backgrounds to try their hand at AI. AI4ALL which runs out of Stanford states that ‘AI will change the world’, and then asks ‘Who will change AI?’

At every RE•WORK summit, we emphasise the importance of diversity in AI by recording episodes of our podcast ‘Women in AI’, hosing female-led panel discussions and fireside chats, and we endeavour to ensure our lineup of speakers embraces diversity and we welcome some of the leading women in AI such as Timnit Gebru, Daphne Koller, Raquel Urtasun, Doina Precup, Joelle Pineau and many others.

This International Women’s Day we’d like to focus on the emerging talent in the field with this list of 30 Rising Stars Under 30 Working in AI:

1. Chelsea Finn, Research Scientist, Google Brain

(Speaker at RE•WORK Summits & recommended by Jeff Clune, Senior Research Scientist, Uber AI Labs)

Having only received her Bachelor’s in EECS a MIT in 2014, Chelsea has had immense success in the past few years. Working alongside global experts she is carrying out pioneering research in deep learning. Chelsea presented her latest work at the Deep Learning Summit earlier this year and also joined RE•WORK on the women in AI podcast which will be published later this month.

When speaking about her cutting edge work in meta-learning, Chelsea shared: “How do we learn to imitate with only a few examples? We want a robot to be able to learn a new task from something it’s never seen before from a single demonstration. We collect data (the task here it to reach a box) and we train it to be able to translate from the demonstration to be able to perform the task. We want it to be able to perform the task in an environment it’s never seen before from a single demonstration.

2. Sara Hooker, Deep Learning Researcher, Google

(Speaker at RE•WORK Summits)

“I taught myself machine learning, and hope others do the same.”

Whilst Sara was teaching herself machine learning, in January 2014, she founded Delta Analytics. Delta is a 501(c)3 non-profit that brings together researchers, data scientists, and software engineers from around the Bay Area to volunteer their skills for nonprofits around the world. Delta teaching fellows build technical capacity around the world to empower communities to use their data for good. Her pilot course was in Nairobi, Kenya and all of curriculum and code is available for free on the website.

Sara has spoken at multiple RE•WORK events and joined us in a fireside chat with Natacha Mainville, also from Google, at the Deep Learning Summit in Toronto last November. You can watch the video of the interview here.

3. 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.

4. Yixuan Li, Research Scientist, Facebook AI

(Speaker at RE•WORK Summits & Recommended by Jeff Clune, Senior Research Scientist, Uber AI Labs)

Yixuan (Sharon) Li is a Research Scientist at Facebook AI, Computer Vision Group. She leads the research effort on large-scale visual learning with high dimensional label space. Before joining Facebook, she 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. At the Deep Learning Summit in San Francisco earlier this January, she shared her latest work on ‘Advancing State-of-the-art Image Recognition with Deep Learning on Hashtags.’

“Every day there are billions of images uploaded onto our platform, therefore our model needs to be trained on billions of images and very large label space.”

5. Polina Mamoshina, Research Scientist, AI division, Insilico Medicine

(Speaker at RE•WORK Summits)

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 the drug discovery engine and developing biochemistry, transcriptome, and cell-free nucleic acid-based biomarkers of aging and disease. She recently co-authored seven academic papers in peer-reviewed journals.

6. Nicole He, Creative Technologist, Google Creative Lab

(Recommended by Cathy Pearl, Voice User Interface Designer, Google)

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!”

7. Bonnie Li, Machine Learning Researcher, Mila

(Recommended by The Knowledge Society)

17-year-old Bonnie is currently working on fundamental research in Reinforcement Learning that can lead us steps closer to Artificial General Intelligence. Bonnie spoke at the RE•WORK Deep Learning Summit in January, and speaking about her supervision under the global pioneer Yoshua Bengio, she explained ‘Yoshua has given me a lot of guidance, but I’ve also learnt a lot by myself. But you have to work everyday to make advancements.’

‘Advancements in education and AI are very helpful, they have allowed me, a 17 year old, to get into the field and do many experiments! You would think that we are well on the way to AI general intelligence with deep reinforcement learning (in popular thinking) however it is important to note still the inability of machines to adapt and generalize.’

8. Yizel Vizcarra, Conversational AI Engineer, Autodesk

(Recommended by AI4ALL)

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 where she enhances and optimises the dialogue of their virtual assistant. 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.

9. Laura Douglas, Co-Founder & CEO, MyLevels

(Speaker at RE•WORK Summits)

While studying maths and economics at UCL and Cambridge, Laura was drawn to behavioural economics and took a job in trading at Morgan Stanley. In 2015 she became fascinated by AI and the impact it could have in healthcare and so went into Machine Learning research. Laura’s main research focus has been in Probabilistic, Generative and Bayesian Machine Learning — and particularly applications in healthcare. She’s worked on 5 different AI health projects, including predicting personalised medication and the AI doctor at Babylon Health, but it has become clear now that the biggest opportunity for AI is going to come in preventative health. Laura founded MyLevels, a personalised health app to ‘shine a light on traditional advice and immediately see for yourself what really works for you.’ Laura spoke on the Women in AI Podcast about her journey founding MyLevels, listen here.

10. Jocelin Su, Founder, She.codes

(Recommended by Tess Posner, CEO, AI4ALL)

Jocelin Su is a high school student in San Jose, California who is interested in studying math and CS. She currently conducts research in computational genetics at Stanford University, and was a participant of the national Math Olympiad Summer Program. After attending Stanford AI4ALL in 2016, she was inspired to found the She.codes workshop program to teach programming to middle school girls, and continues to mentor students in CS outreach. She.codes holds coding workshops for girls to learn cutting-edge topics in programming and in the 2019 session they will be covering various topics in AI including learning to build ‘your own smart movie recommender system through hands-on activities, coding contests and projects.’ In her spare time, Jocelin enjoys music and making art.

11. Eunice Chendjou, Founder & CEO, DataGig

(Speaker at RE•WORK Summits)

Eunice is the founder at DataGig, an online marketplace where enterprises hire vetted data experts and vendors for their big data and analytics projects on-demand.Prior to founding DataGig, she was 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.

“I strongly believe in building the next generation of women and minorities in the tech industries. I volunteer by mentoring students at Code2College, a non-profit whose mission is to dramatically increase the number of girls, underrepresented students of color and low-income students who enter STEM degree programs and fields.”

12. Bianca Furtuna, Applied Machine Learning Scientist, Microsoft

(Speaker at RE•WORK Summits)

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.”

13. Anusha Balakrishnan, Research Engineer, Faceboo

(Speaker at RE•WORK Women in AI Dinner)

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 is a research engineer at Facebook on the Conversational AI team. She conducts research on building better conversational systems, with a specific focus on Natural Language Generation (NLG) and dialogue policy. 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. Anusha joined RE•WORK in January at the Women in AI Dinner where she presented her most recent work on Conversational AI at Facebook.

14. Tasha Nagamine, Chief AI Officer, Droice Labs

(Speaker at RE•WORK Summits)

Since graduating from Brown University in 2013, Tasha has completed her PhD in Philosophy at Columbia University and worked as a Research Assistant on neural basis of speech and language processing, deep neural networks (DNNs) for automatic speech recognition. “At Droice, we use artificial intelligence to help clinicians make better decisions for individual patients. What treatment should a patient be given? Are there any potential complications? What tests need to be done? All of these (and many more) are examples of difficult, data-intensive questions that doctors must answer every day. By answering these questions, AI has the power to fundamentally transform healthcare but has been hampered by slow adoption into common clinical practice. This presentation will describe Droice Labs technology and address strategies for translating AI into deployable hospital solutions.”

15. Jasmine Hsu, Software Engineer, Google

(Recommended by Sara Hooker, Deep Learning Researcher, 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.

16. Lucy Yu, FiveAI

(Speaker at RE•WORK Summits)

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.

17, Fanny Riols, Applied Research Scientist, Element AI

(Recommended by Caroline Chavier, Founder, Parin Women in ML and Data Science)

Fanny Riols ian 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.

18. Joy Buolamwini, Founder, Algorithmic Justice League and Graduate Researcher, MIT Media Lab

Joy is a self proclaimed ‘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.

As a graduate researcher at the MIT Media Lab, she leads the Algorithmic Justice League to fight coded bias. Her research explores the intersection of social impact technology and inclusion. In support of this work, Buolamwini was awarded a $50,000 grant as the Grand Prize winner of a national contest inspired by the critically acclaimed film Hidden Figures, based on the book by Margot Lee Shetterly.

19. AJung Moon, Senior Advisor of Research & Industry, UN Secretary General’s High-level Panel on Digital Cooperation

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. As a roboticist with experience in both roboethics and HRI, she has been heavily involved in international and Canadian discussions on artificial intelligence and autonomous systems. She 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.

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

(Recommended by Jeff Clune, Senior Research Scientist, Uber AI Labs and Sara Hooker, Deep Learning Researcher, Google)

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. Rosanne shared her work on ‘Intrinsic Dimension of Objective Landscapes in Deep Neural Networks’ at the Women in AI Dinner in San Francisco last June.

21. Ashley Edwards, Research Scientist, Uber AI Labs

(Recommended by Jeff Clune, Senior 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.

22. Merve Alanyali, Data Scientist, LV=

(Speaker at RE•WORK Summits)

Merve is enthusiastic about combining diverse set of machine learning methods to address complex data science problems. Merve is a 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.

23. Anna Huang, AI Resident, Google (Magenta)

(Recommended by Sara Hooker, Deep Learning Researcher, Google)

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 milisecond 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.

24. Lucy X Wang, Senior Data Scientist, BuzzFeed

(Speaker at RE•WORK Women in AI Reception)

Lucy is a full-stack data scientist and manager keen on solving emerging machine learning problems.Completed graduate work in machine learning with research on information diffusion. Interests include social networks, NLP, and deep learning. At BuzzFeed, she’s currently leading a team in maximizing social media distribution and revenue, through deep learning-based recommendation models and reporting and spoke at the RE•WORK Women in AI Reception: BuzzFeed trains models to find out which social channels does a particular piece of content have the best match with. They are working to solve the problem of what social channel they should direct content to. Lucy spoke about a common problem in machine learning: “Underlying data is not a source of truth. It is very messy”. She spoke about identifying the need to mimic human creation behaviour, therefore they had created models off of past human-generated data. Lucy explained that a lot of quality assessment is required for results. Therefore they created a slack bot to ask users if it was a good recommendation and the answer is fed back into the model to retrain.

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

(Speaker at RE•WORK Summits)

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. Having spoken at several RE•WORK Summits as well as appearing on the Women in AI Podcast, Maithra has expressed her passion for ensuring AI is created without negative bias and is created by a diverse team to result in fair and equal systems. 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.

26. Daniela Massiceti, PhD Student in Computer Vision, University of Oxford

(Recommended by Sara Hooker, Deep Learning Researcher, Google)

Daniela is a doctoral student 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. She has also dabbled in some other multi-modal combinations. Crossing vision with audio, she prototyped a device which created 3D soundscapes of virtual environments for audio-only spatial navigation!

27. Jade Leung, Head of Research and Partnerships, Center for Governance of Artificial Intelligence

(Speaker at RE•WORK Summits)

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.

28. Alice Piterova, Head of Privacy, Hazy

(Speaker at RE•WORK Summits)

Alice reviews Hazy’s product features for AI ethics, data privacy and compliance and helps define Hazy’s core message to the world. Prior to joining Hazy Alice coordinated the cross-party parliamentary group on AI (APPG AI), helping the UK Government to address ethical implications and design new standards for applying machine learning in commercial, political and social areas. 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.

29, Liz Asai, CEO, 3Derm

(Speaker at RE•WORK Summits)

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.

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

(Speaker at RE•WORK Summits)

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.

Happy International Women’s Day 2019! Would you like to expand your network in AI as well as supporting diversity in the field? Check out our Podcast, or the Women in AI Dinner series (which is open to all genders!). If you know anyone influential working in AI who you think should be showcased, let us know! Email Yaz at yhow@re-work.co.