Yoshua Bengio is Full Professor of the Department of Computer Science and Operations Research, head of the Montreal Institute for Learning Algorithms (MILA), CIFAR Program co-director of the CIFAR program on Learning in Machines and Brains,  Canada Research Chair in Statistical Learning Algorithms. His main research ambition is to understand principles of learning that yield intelligence. He supervises a large group of graduate students and post-docs. His research is widely cited (over 80000 citations found by Google Scholar in September 2017, with an H-index of 101).

Yoshua Bengio is currently action editor for the Journal of Machine Learning Research, associate editor for the Neural Computation journal, editor for Foundations and Trends in Machine Learning, and has been associate editor for the Machine Learning Journal and the IEEE Transactions on Neural Networks.

Dr. Werner Vogels is Chief Technology Officer at Amazon.com where he is responsible for driving the company’s customer-centric technology vision.

As one of the forces behind Amazon’s approach to cloud computing, he is passionate about helping young businesses reach global scale, and transforming enterprises into fast-moving digital organizations.

Vogels joined Amazon in 2004 from Cornell University where he was a distributed systems researcher. He has held technology leadership positions in companies that handle the transition of academic technology into industry. Vogels holds a PhD from the Vrije Universiteit in Amsterdam and has authored many articles on distributed systems technologies for enterprise computing.

Rediet Abebe is a Junior Fellow at the Harvard Society of Fellows. She holds a Ph.D. in computer science from Cornell University, where she was advised by Jon Kleinberg, as well as an M.S. in applied mathematics from Harvard University, an M.A. in mathematics from the University of Cambridge, and a B.A. in mathematics from Harvard College. Her research is broadly in the fields of artificial intelligence and algorithms, with a focus on discrete algorithms, optimization, network and computational science, and their applications to equity and social good concerns. As part of this research agenda, she co-founded and co-organizes Mechanism Design for Social Good (MD4SG), a multi-institutional, interdisciplinary research initiative working to improve access to opportunity for historically underserved and disadvantaged communities. This initiative has participants from over 100 institutions in 20 countries and has been supported by organizations including Schmidt Futures, the MacArthur Foundation, and the Institute for New Economic Thinking.

Abebe’s work has informed policy and practice at various organizations including the National Institute of Health and the Ethiopian Ministry of Education. Throughout 2019, she served on the NIH Advisory Committee to the Director Working Group on AI, whose recommendations were unanimously approved by the General Director’s advisory committee. Abebe was recently named one of 35 Innovators Under 35 by the MIT Technology Review. She has also been honored by ELLE as a woman transforming technology and the 2019 Bloomberg 50 list as a “one to watch.” She has recently presented her research in venues including the National Academy of Sciences, the United Nations, and the Museum of Modern Art. In 2017, Abebe co-founded Black in AI, a non-profit organization tackling representation and inclusion issues in the field. Her research is deeply influenced by her upbringing in her hometown of Addis Ababa, Ethiopia. 

Stuart Russell is a pioneer in the understanding and uses of artificial intelligence (AI), its long-term future, and its relation to humanity. He also is a leading authority on robotics and bioinformatics.

Stuart Russell is the author or coauthor of three books on knowledge, reasoning, and machine learning, including the standard textbook on artificial intelligence. Stuart Russell is a professor of Electrical Engineering and Computer Sciences at UC-Berkeley and Adjunct Professor of Neurological Surgery at UC-San Francisco.

Artificial intelligence. AI is a machine’s ability to perceive its environment and use that information to maximise its chance at succeeding at some goal. All of the technologies behind artificial intelligence are evolving at exponential rates and are just now beginning to rocket up the curve. Soon artificially intelligent machines will be doing things we can barely conceive, in virtually every area of human business, life, and culture. Few people understand this future better than Stuart Russell, who wrote the standard textbook on AI (with coauthor Peter Norvig), now in its third edition.

Robotics. Stuart Russell is also a leading researcher in the practical applications of machine intelligence. If AI is the brain of the machine of the future, the robot is its body. Robots are taking over more and more functions that once required a human actor, with far-reaching consequences — and opportunities — for people, businesses, and society as a whole. He has focused recently on the threat of autonomous weaponry.

Biological information. As an Adjunct Professor of Neurological Surgery, Stuart has been researching computational physiology, with a current focus on Intensive Care Unit monitoring systems. He is a leader in the development of technologies that make sense of biological data and that apply this information in ways that advance human health.

Credentials. In addition to the positions already mentioned, Stuart Russell holds the SmithZadeh Chair in Engineering at UC-Berkeley and is Vice-Chair of the World Economic Forum’s Council on AI and Robotics. He is the recipient of many awards and held the Chaire Blaise Pascal in Paris from 2012 to 2014. He is a researcher at a number of research centers, including the Berkeley Artificial Intelligence Research Lab (BAIR), the Berkeley Center for New Media (BCNM), and the Synthetic Biology Institute (SBI). He is the founder and Vice-President of Bayesian Logic, Inc., a data analysis start-up under contract with the UN to build a new Nuclear Test Ban Treaty global monitoring system.

Dr. Joseph Sirosh is the CTO for Microsoft AI. Prior to this role, he has served as a Corporate Vice President of the AI and Data Platform at Microsoft responsible for Databases, Big Data, Machine Learning Cognitive Services, Bot Services and Information Management, and as the Vice President of the Global Inventory Platform at Amazon where he also spent nearly 9 years in various roles including building internal Machine Learning platforms. Prior to Amazon he was the VP of R&D at Fair Isaac Corporation. He holds a PhD in Neural Networks from the University of Texas at Austin and a BTech from Indian Institute of Technology, Chennai.

AI Ethics Global Leader, Distinguished Research Staff Member, IBM Research AI

Francesca Rossi is AI Ethics Global Leader, Distinguished Research Staff Member at IBM Research AI and professor of computer science at the University of Padova, Italy, currently on leave.

Her research interests focus on artificial intelligence, specifically they include constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making. She is also interested in ethical issues in the development and behaviour of AI systems, in particular for decision support systems for group decision making. She has published over 170 scientific articles in journals and conference proceedings, and as book chapters. She has co-authored a book. She has edited 17 volumes, between conference proceedings, collections of contributions, special issues of journals, as well as the Handbook of Constraint Programming.  She has more than 100 co-authors.

She is a AAAI and a EurAI fellow, and a Radcliffe fellow 2015. She has been president of IJCAI and an executive councillor of AAAI. She is Editor in Chief of JAIR and a member of the editorial board of Constraints, Artificial Intelligence, AMAI, and KAIS. She co-chairs the AAAI committee on AI and ethics and she is a member of the scientific advisory board of the Future of Life Institute and of the Leverhulme Centre for the Future of Intelligence. She is in the executive committee of the IEEE global initiative on ethical considerations on the development of autonomous and intelligent systems and she belongs to the World Economic Forum Council on AI and robotics. She is a member of the board of directors of the Partnership on AI, where she represents IBM as one of the founding partners. 

Hui Xiong is a Professor at Rutgers University, and is currently on leave and serving as head of Business Intelligence Lab and Talent Intelligence Center at Baidu Inc. His research interests include data mining, mobile computing, and their applications in business. He has authored over 200 research articles, and co-edited or coauthored 4 books including the widely used Encyclopedia of GIS, which has been recognized as the Top 10 Most Popular Computer Science Book authored by Chinese scholars at Springer. Dr. Xiong has served as chair/co-chair for many international conferences in data mining, including a Program Co-Chair (2013) and a General Co-Chair (2015) for the IEEE International Conference on Data Mining (ICDM), and a Program Co-Chair of the Research Track (2018) and the Industry Track (2012) for the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). Dr. Xiong’s research has generated substantive impact beyond academia. He is an ACM distinguished scientist and has been honored by the 2018 Ram Charan Management Practice Award as the Grand Prix winner from the Harvard Business Review, the 2017 IEEE ICDM Outstanding Service Award, and the ICDM-2011 Best Research Paper Award.

Ralf Herbrich leads a diverse range of departments and initiatives that have, at their core, research in the area of artificial intelligence (AI), spanning data science, machine learning and economics. Ralf’s teams apply and advance the science in many established scientific fields including computer vision, natural language processing, data science and economics. Ralf joined Zalando SE as SVP Data Science and Machine Learning in January 2020. Previously, he served as Managing Director of the Amazon Development Center in Germany (with its locations in Berlin, Dresden, Aachen and Tübingen) and was Director of Machine Learning at Amazon in Berlin from 2013. Prior to these roles, he led Facebook’s Unified Ranking and Allocation team in 2011. From 2000 to 2011, he served as Director of Microsoft’s Future Social Experiences (FUSE) Lab UK and worked for nine years at Microsoft Research Lab in Cambridge, UK. Ralf has published over 80 peer-reviewed papers and holds over 40 patents. He obtained a Ph.D. in Statistics from Technical University of Berlin in 2000 and his Diploma in Computer Science from the same institution in 1997. His research interests include Bayesian inference and decision making, natural language processing, computer vision, learning theory, robotics, distributed systems and programming languages. Ralf is one of the inventors of the Drivatars™ system in the Forza Motorsport series as well as the TrueSkill™ ranking and matchmaking system in Xbox Live.

Meredith Whittaker is the Minderoo Research Professor at New York University and the founder of Google’s Open Research group.

Her research and advocacy focus on the social implications of artificial intelligence and the tech industry responsible for it, with a particular emphasis on power and the political economy driving the commercialization of computational technology. Prior to NYU, she worked at Google for over a decade, where she led product and engineering teams, founded Google’s Open Research Group, and co-founded M-Lab, a globally distributed network measurement platform that now provides the world’s largest source of open data on internet performance. She also worked extensively on issues of privacy and security, helping provide funding, strategy, and support for efforts dedicated to providing privacy from governments and large tech corporations. As a long-time tech worker, she also helped lead labor organizing at Google. She was one of the core organizers pushing back against Google’s military contracts, the company’s insufficient response to concerns about AI and its harms, and was a central organizer of the Google Walkout. She continues to work in solidarity with organizers in tech, driven by the belief that worker power and collective action are necessary to ensure meaningful tech accountability, especially in the context of concentrated industrial power. She has advised the White House, the FCC, the City of New York, the European Parliament, and many other governments and civil society organizations on artificial intelligence, internet policy, measurement, privacy, and security.

Timnit is currently a research scientist at Google in the ethical AI team. Prior to that Timnit did a postdoc at Microsoft Research, New York City in the FATE (Fairness Transparency Accountability and Ethics in AI) group, where she studied algorithmic bias and the ethical implications underlying any data mining project (see this New York Times article for an example of my work). She received her PhD from the Stanford Artificial Intelligence Laboratory, studying computer vision under Fei-Fei Li. Timnit’s thesis pertains to data mining large scale publicly available images to gain sociological insight, and working on computer vision problems that arise as a result. The Economist, The New York Times and others have covered part of this work. Some of the computer vision areas Timnit is interested in include fine-grained image recognition, scalable annotation of images, and domain adaptation. Prior to joining Fei-Fei’s lab she worked at Apple designing circuits and signal processing algorithms for various Apple products including the first iPad. Timnit also spent an obligatory year as an entrepreneur (as all Stanford undergrads seem to do). Her research was supported by the NSF foundation GRFP fellowship and the Stanford DARE fellowship

Grady Booch is Chief Scientist for Software Engineering at IBM Research where he leads IBM’s research and development on embodied cognition. Having originated the term and the practice of object-oriented design, he is best known for his work in advancing the fields of software engineering and software architecture. A co-author of the Unified Modeling Language (UML), a founding member of the Agile Alliance, and a founding member of the Hillside Group, Grady has published six books and several hundred technical articles, including an ongoing column for IEEE Software and IEEE Spectrum. Grady is also a trustee for the Computer History Museum. He is an IBM Fellow, an ACM Fellow, an IEEE Fellow, has been awarded the Lovelace Medal and given the Turing Lecture for the BCS, and was named an IEEE Computer Pioneer for his work in software architecture.

Grady has served as an architect or architectural mentor for a multitude of complex software-intensive systems across many domains around the world, including finance, transportation, defense, commerce, productivity, government, medical, gaming, animation, software development, artificial intelligence, and many others.

Grady is currently developing a major transmedia documentary for public broadcast on the intersection of computing and the human experience: Computing.