Yoshua Bengio is recognized as one of the world’s leading experts in artificial intelligence and a pioneer in deep learning. Following his studies in Montreal, culminating in a Ph.D. in computer science from McGill University in 1991, Professor Bengio did postdoctoral studies at the Massachusetts Institute of Technology (MIT) in Boston.

Since 1993, Yoshua Bengio has been a professor in the Department of Computer Science and Operational Research at the Université de Montréal. In addition to holding the Canada Research Chair in Statistical Learning Algorithms, he is also the founder and scientific director of Mila, the Quebec Institute of Artificial Intelligence, the world’s largest university-based research group in deep learning. He is also the Scientific Director of IVADO.

His contribution to research is undeniable. In 2018, Yoshua Bengio is the computer scientist who collected the largest number of new citations in the world, thanks to his three reference works and some 500 publications.

His ultimate goal is to understand the principles that lead to intelligence through learning and his research has earned him multiple awards. In 2017, he was made an Officer of the Order of Canada and a Fellow of the Royal Society of Canada, in addition to receiving the Prix Marie-Victorin and being named Scientist of the Year by Radio-Canada. In 2018, he was also awarded the 50th Anniversary Medal by Quebec’s Ministère des Relations internationales et de la Francophonie. These honours reflect the profound influence of his work on the evolution of our society.

Concerned about the social impacts of this new technology, he actively contributed to the development of the Montreal Declaration for Responsible Development of Artificial Intelligence.

Daphne Koller brings to insitro her many years of experience in the areas of machine learning, statistical modeling, computational biology, and computational medicine. She was the Rajeev Motwani Professor of Computer Science at Stanford University, where she was hired as the first machine learning professor in 1995 and served on the faculty for 18 years. Her work in machine learning spans a broad range of topics, including probabilistic graphical models, structured prediction, active learning, time series modeling, reinforcement learning, and many more. She was also one of the pioneers in applying machine learning to biomedical data sets and has worked on topics such as reconstruction of regulatory networks, phenotypic effects of genetic variation, and interpretation of microscopy images in cancer. She is the author of over 200 refereed publications appearing in diverse venues such as NIPS, ICML, Science, Cell, and Nature Genetics, and has an h-index of over 120. She is also the author of the leading textbook on Probabilistic Graphical Models.

Daphne co-founded Coursera in 2012, where she served as the company’s Co-CEO until 2014, and then as President until 2016. Coursera is the world’s largest online education platform with over 30 million learners worldwide, and over 150 university partners in six continents. She is currently the Co-Chair of the Coursera Board. Most recently, Daphne served as the Chief Computing Officer at Calico Labs, an Alphabet (Google) company that is using advanced technology to understand aging and design interventions that help people lead longer, healthier lives.

Daphne was recognized as one of TIME Magazine’s 100 most influential people in 2012 and Newsweek’s 10 most important people in 2010. She has been honored with multiple awards and fellowships during her career including the Sloan Foundation Faculty Fellowship in 1996, the ONR Young Investigator Award in 1998, the Presidential Early Career Award for Scientists and Engineers (PECASE) in 1999, the IJCAI Computers and Thought Award in 2001, the MacArthur Foundation Fellowship in 2004, and the ACM Prize in Computing in 2008. Daphne was inducted into the National Academy of Engineering in 2011 and elected a fellow of the American Academy of Arts and Sciences in 2014 and of the International Society of Computational Biology in 2017.

Gary Marcus, scientist, bestselling author, and entrepreneur, was CEO and Founder of the machine-learning startup Geometric Intelligence, recently acquired by Uber, and is known for his provocative and bold claims in artificial intelligence, neuroscience, and cognitive science. Trained by Steven Pinker, he received his PhD at MIT at age 23. His professional research, published in leading journals such as Science, Nature, Cognition, and Artificial Intelligence, has focused on the foundations of cognition in humans, animals and machines, spanning fields from developmental psychology to neuroscience to genetics to artificial intelligence. A special interest has been on the challenge of endowing machines with common sense.

He is also well-known for his writing for the general public, including frequent essays and op-eds for The New Yorker and The New York Times. His books include The Algebraic Mind, The Birth of the Mind, Kluge: The Haphazard Evolution of the Human Mind, The New York Times Bestseller, Guitar Zero and The Future of the Brain: Essays By The World’s Leading Neuroscientists.

In a 2012 essay for The New Yorker, he was perhaps the first person to publicly criticize deep learning, drawing on arguments he developed in his 2001 technical book The Algebraic Mind. More recently, in a 2018 arXiv article, Deep Learning: A Critical Appraisal, he asked whether deep learning might be “approaching a wall.” The challenges he laid out there were covered everywhere from The New York Times to Wired to The Financial Times and Wall Street Journal.

In another provocative 2012 essay, Moral Machines, Marcus was the first to adapt “trolley problems” to driverless cars, anticipating much recent research on the ethics of AI. His next book, REBOOT: Getting to AI We Can Trust, to be published by Pantheon in Fall 2019, co-authored with Ernie Davis, calls for a fundamental rethinking of current approaches to artificial intelligence.

Dr. Kathryn Hume is the interim Head of Borealis AI, the machine learning research lab backed by the Royal Bank of Canada. Prior to joining Borealis, Dr. Hume held leadership positions at Integrate.ai and Fast Forward Labs, where she helped over 50 Fortune 500 organizations develop and implement AI programs. Dr. Hume is a widely respected author and speaker on AI, with work appearing at TED, HBR and the Globe and Mail. She has taught courses on digital transformation and legal ethics at the business and law schools at Harvard, MIT, the University of Toronto and the University of Calgary. She holds a PhD in Comparative Literature from Stanford University and speaks seven languages

Marc G Bellemare is a research scientist at Google Brain in Montreal, Canada; CIFAR Learning in Machines & Brain Fellow; adjunct professor at McGill University; and was recently awarded a Canada CIFAR AI chair, held at the Montreal Institute for Learning Algorithms (Mila). He received his Ph.D. from the University of Alberta where he studied the concept of domain-independent agents and developed the highly-successful Arcade Learning Environment, the platform for AI research on Atari 2600 games. From 2013 to 2017 he was a research scientist at DeepMind where he made major contributions to the field of deep reinforcement learning. He is known for his work on reinforcement learning, including approximate exploration, representation learning, and the distributional method.

Celeste Kidd is an Assistant Professor of Psychology at the University of California, Berkeley, where her lab investigates learning and belief formation. The Kidd Lab is one of few in the world that combine technologically sophisticated behavioral experiments with computational models in order to broadly understand knowledge acquisition. Her lab employs a range of methods, including eye-tracking and touchscreen testing with human infants, in order to show how learners sample information from their environment and build knowledge gradually over time. Her work has been published in PNAS,Neuron, Psychological Science, Developmental Science, and elsewhere. Her lab has received funding from NSF, DARPA, Google, the Jacobs Foundation, the Human Frontiers Science Program, and the Templeton Foundation. She is a recipient of the American Psychological Science Rising Star designation, the Glushko Dissertation Prize in Cognitive Science, and the Cognitive Science Society Computational Modeling Prize in Perception/Action. Kidd was also named as one of TIME Magazines 2017 Persons of the Year as one of the “Silence Breakers” for her advocacy for better protections for students against sexual misconduct.

Hassan Sawaf has worked in the automatic speech recognition, computer vision, natural language understanding, and machine translation fields for 20+ years. In 1999, he cofounded AIXPLAIN AG, a company offering speech recognition and machine translation services to enterprises, before “cloud” was yet a mainstream concept. His startup was acquired by AppTek in 2004, where he served as COO and Chief Scientist till SAIC acquired AppTek’s assets in 2010. Hassan was then Chief Scientist and Technical Fellow in SAIC with focus on Human Language Technology and Artificial Intelligence. In 2013 he joined eBay as senior director and head of AI, growing the Artificial Intelligence capability that is now enabling a large parts of the business. Since September of 2016 he joined Amazon to lead the Applied Science for Amazon AI, building up the science foundations for various AWS AI services.

Constanza is interested in achieving an inclusive Fourth Industrial Revolution in emerging countries. This led her to found and direct C Minds (www.cminds.co), an impact technology agency based in San Francisco and Mexico City. From C Minds, Constanza works with governments and institutions in the development of public policy and programs on issues of digital transformation, seeking to enhance the benefits of new technologies in emerging countries. She also leads initiatives to explore the power of technology to accelerate financial innovation, sustainable mobility, safety, health and education, among other issues. Other initiatives that C Minds coordinates, such as the AI for Good Lab, seek to deepen the ethical debate on the social and labor consequences of the technological transformation we are experiencing, particularly in Mexico. C Minds is also collaborating with the Jalisco Government and Tec de Monterrey University to develop a first AI center in Guadalajara as part of a regional network to be built.

Constanza has been a consultant for the United Nations, the World Bank and national and local governments. Her work has been recognized in international media and she was named Global Shaper by the World Economic Forum, Gifted Citizen by City of Ideas, British Government’s International Leader by the Government of the United Kingdom, winner of the SU Global Impact Challenge in Mexico and a Singularity University GSP graduate, among other recognitions.

Carolina can best be described as an established academic with an entrepreneurial mindset, who also happens to have 25+ years of experience in research, development and broad programming.

After obtaining her PhD in fundamental physics from the Universidad de los Andes, she went on to become an award-winning university professor who worked closely with the government of Venezuela to predict everything from avalanches to life-threatening diseases. After teaching computational physics and astrophysics for nearly a decade, she decided to move to Canada, which ultimately led to her rise as Stradigi AI’s Chief Scientific Officer and Co-Founder in 2017. Since then, she oversees all projects from both a scientific and business perspective, leads her team of 30+ research scientists, works closely with top executives to build relationships with clients and proudly offers guidance and mentoring to students.

Carolina is a member and advocate of the Montreal Artificial Intelligence Ethics group. She is passionate about ensuring that the benefits of AI are democratically available, the prevention of the weaponization and/or malicious use of AI, issues relating to privacy and the quantification and correction of bias in datasets. More recently, her focus has been on interpretability. Her belief in simplifying the way humans can understand the processes in which an algorithm arrives to its predictions is crucial for building trust, gaining executive buy-in and the early adoption of this technology in various industries. Carolina is also actively involved with the Vector Institute which has Dr. Geoffrey Hinton as its Chief Scientific Advisor, a man described as the “Godfather of Deep Learning”. As such, she serves on a panel for the 1000 AIMs initiative reviewing Ontario University programs seeking Vector Institute recognition.

Having conducted extensive AI research since 2002, she is a highly sought-after public speaker and has worked alongside renowned advisors and business pioneers in the industry enabling her to continuously create, innovate and develop new solutions to help organizations with their complex business problems.

Ruslan Salakhutdinov received his PhD in machine learning (computer science) from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an Assistant Professor in the Department of Computer Science and Department of Statistics. In February of 2016, he joined the Machine Learning Department at Carnegie Mellon University as an Associate Professor.

Ruslan’s primary interests lie in deep learning, machine learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data. He is an action editor of the Journal of Machine Learning Research and served on the senior programme committee of several learning conferences including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, Microsoft Research Faculty Fellow, Canada Research Chair in Statistical Machine Learning, a recipient of the Early Researcher Award, Connaught New Researcher Award, Google Faculty Award, Nvidia’s Pioneers of AI award, and is a Senior Fellow of the Canadian Institute for Advanced Research.

Hallie Benjamin is a Senior Strategist with Google AI, where she had led inclusive product and user testing for fairness. She was also an Assembly Fellow with Harvard’s Berkman Klein Center and the MIT Media Lab. Her applied research with Assembly focused on empowering startups to responsibly and ethically build, procure, and use advanced technologies like Artificial Intelligence.

She has spent the last decade working at the intersection of social justice and business, and is currently pushing for the design and development of inclusive technology that works for everyone. Before joining Google, she spent several years in management consulting where she led cross-functional teams using data visualization to envision the future of business.

Originally from Toronto, Canada, Hallie has an MA in Economics and Global Affairs from the Munk School at the University of Toronto, and a BA in Economics and Political Science from McGill University.

Jose A. Murillo established and leads the Analytics Business Unit at Banorte –the second largest financial group in Mexico. His group has been recognized as a success story within the data and analytics industry. The value created with analytics on 2018, the third year of operations of his group, exceeded 700 million USD–during his tenure the value created has exceeded 1.7 billion dollars. This case was published at Harvard Business Review as an example of a company which made its analytics investments pay-off (2018). Also, his team obtained the Lafferty Global Award on Credit Card Excellence for the impact of analytics on customer equity (2016). Jose was named among the top analytics and data professionals in North America by Corinium in its first and second edition. He has been published in several industry and refereed journals, he is a frequent speaker at analytics forums and he is a member of Queen’s University Advisory Board for the Masters in Management Analytics.

Prior to Banorte, Jose was a top-ranking official at Mexico’s Central Bank and participated for more than a decade at the Monetary Policy Committee holding the staff’s view on inflation –a key variable for policy decision. Also, he was an advisor to the International Monetary Fund on statistics and led missions to Ecuador and Chile. At the academia he taught economics at Rice University, ITAM and El Colegio de Mexico. He holds a PhD in economics from Rice University and graduated from ITAM (Cum Laude and received national prizes from the Chamber of Commerce and Tlacalel Prize).

Deepak Agarwal is a vice president of engineering at LinkedIn where he is responsible for all AI efforts across the company. He is well known for his work on recommender systems and has published a book on the topic. He has published extensively in top-tier computer science conferences and has coauthored several patents. He is a Fellow of the American Statistical Association and has served on the Executive Committee of Knowledge Discovery and Data Mining (KDD). Deepak regularly serves on program committees of various conferences in the field of AI and computer science. He is also an associate editor of two flagship statistics journals.

Jodie Wallis is Managing Director for Artificial Intelligence (AI) and Applied Intelligence at Accenture in Canada. Jodie is responsible for expanding Accenture’s business presence in the AI ecosystem, attracting top talent, and bringing innovation and global AI expertise to Canadian clients across all industries.
In her role, Jodie works with clients to develop AI strategies, discover sources of value and implement AI solutions. She also leads Accenture’s collaboration with business partners, government and academia and oversees Accenture’s investments in the Canadian AI ecosystem, including its sponsorship of the Vector Institute for Artificial Intelligence.
Through more than 25 years at Accenture, Jodie has developed deep expertise in management and technology consulting. She is a frequent speaker and contributor on the implications of AI for society and the future of work. Recent engagements include Collision (May 2019), the G7 Multistakeholder Conference on Artificial Intelligence: Enabling the Responsible Adoption of AI (Dec. 2018) and the Canada-UK Colloquium on Artificial Intelligence & Society: Choices, Risks and Opportunities (Nov. 2018).
Jodie is also co-host of Accenture’s award-winning podcast series “The AI Effect,” and was named one of the “10 Toronto artificial intelligence experts you should know” by ITBusiness.ca. Capping off an incredible year, she was recognized as Digital Leader of the Year at Canada’s Women in IT Awards.
Jodie earned her Bachelor of Mathematics with Honours from the University of Waterloo, where she majored in Operations Research and minored in Statistics and Computer Science. She actively volunteers in the Toronto community, serving as co-chair of the organizing committee for the Covenant House Guts + Glory Corporate Challenge, which raises funds for Canada’s largest agency serving at-risk, homeless and trafficked youth.

César A. Hidalgo is a Chilean-Spanish-American physicist, author, and entrepreneur. He currently holds a Chair at the Artificial and Natural Intelligence Toulouse Institute (ANITI), an is also an Honorary Professor at the University of Manchester and a Visiting Professorship at Harvard’s School of Engineering and Applied Sciences.

From 2010 to 2019, Hidalgo lead MIT’s Collective Learning group, and was an Associate Professor at MIT. Prior to joining MIT, Hidalgo was a research fellow at Harvard.

Hidalgo is also a founder of Datawheel, an award winning company specialized in the creation of data distribution and visualization systems.

Hidalgo holds a PhD in Physics from the University of Notre Dame and a Bachelor in Physics from Universidad Católica de Chile.

Hidalgo is known for creating the field of Economic Complexity, which uses high resolution data and network methods to explain and predict patterns of industrial and economic development. Hidalgo is also known for the creation of multiple data visualization and distribution systems, and for advancing ideas on the use of Artificial Intelligence in democracy.

Hidalgo’s contributions have been recognized with numerous awards, including the 2018 Lagrange Prize, multiple Webby Awards (DataUSA, DataAfrica, & Streetchange), an Information is Beautiful Award (DataUSA), and the Bicentennial Medal of the Chilean Congress, among others. Hidalgo’s is the author of Why Information Grows (Basic Books, 2015), which has been translated to over ten languages and was a finalist for the Hayek Prize. Hidalgo is also a lead author of The Atlas of Economic Complexity (MIT Press, 2014), a highly cited book on the basic principles and methods used in economic complexity.

Craig Martell is the Head of Machine Intelligence at Dropbox. Prior to joining Dropbox, he led a number of AI teams and initiatives at LinkedIn, including the development of the LinkedIn AI Academy. Before LinkedIn, Craig was a tenured computer science professor at the Naval Postgraduate School specializing in natural-language processing (NLP). He has a Ph.D. in Computer Science from the University of Pennsylvania and is the co-author of the MIT Press book Great Principles of Computing.

AJung Moon is an Assistant Professor at McGill University (Dept. of Electrical & Computer Engineering). She is an experimental roboticist specializing in ethics and responsible design of interactive robots and autonomous intelligent systems. She studies how our interaction with machines influence people’s behaviours and decisions and investigates different ways to integrate our societal values in the design and deployment of autonomous systems. Prior to joining McGill, she served as a Senior Advisor for the UN Secretary-General’s High-level Panel on Digital Cooperation, a taskforce that investigated the need for improved technology governance and policy across national borders. She also ran a start-up AI ethics consultancy, Generation R Consulting and founded the Open Roboethics Institute, a Canadian nonprofit that investigates societal and ethical implications of robotics and AI.
She completed a BASc (University of Waterloo) in Mechatronics Engineering, and a MASc and a PhD (University of British Columbia) in Mechanical Engineering. She became a Vanier Scholar in 2013 and developed interactive robot behaviours that allows for a human and a robot to nonverbally negotiate their way out of conflicts that arise in human-robot teamwork. She currently serves on the Government of Canada Advisory Council on Artificial Intelligence among others.

Jana is a consultant for the Slovakian Government, Deputy Prime Ministers Office, on two agendas, AI and Women in Digital. She was appointed a Gender Equality Rapporteur for CAHAI, and has a legal and technical background.
She focuses on work related to AI regulatory frameworks within Council of Europe, the European Commission and the domestic Slovakian regulatory framework. She collaborated on Slovakian Digitalisation Strategy 2030 together with the Action plan focused on measures targeting design and deployment of artificial intelligence. These two documents came into effect mid-2020.
Prior to this, Jana’s most recent work in private sector was leading work on a rulebook of Robotics Process Automation (RPA) governance within a tier 1 investment bank within their technical architecture team, and establishing comparison and feasibility study on RPA vs. RDA implementation in large legacy technology stacks corporate environments. A designed instance of RPA and deployed into production environment became a software robot which can be used across multiple industries, and thanks to process engineering and AI functions, like Optical Character Recognition, automates repetitive and manual error prone mundane human tasks.
Jana’s extra curriculum work has involved setting up coding weekends for girls at Bank of America Merrill Lynch in London, and volunteering for CodeFirst:Girls London General course. She is passionate about activities promoting and supporting girls and women in their interests and uptake of STEM related fields of study and career.

Alice Xiang is the Head of Fairness, Transparency, and Accountability Research at the Partnership on AI, where she leads a team of interdisciplinary researchers. Core areas of her research include bridging technical and legal approaches to algorithmic bias, assessing explainability techniques in deployment, and examining risk assessment tools. Alice’s work sits at the intersection of social justice and AI; she seeks to tackle the ways in which algorithmic decision-making can further entrench societal biases and inequalities.
She recently taught a course on “Algorithmic Fairness, Causal Inference, and the Law” at Tsinghua University’s Yau Mathematical Sciences Center, where she was a Visiting Scholar. She has also given lectures and speeches at events hosted by the AAAS, IEEE, Simons Institute, Harvard Institute of Quantitative Social Science, Tsinghua Statistical Sciences Center, RE•WORK, and others.
Alice’s research has been published in peer-reviewed machine learning conferences, statistics journals, and law reviews. She has also been quoted in Axios, Mercury News, and VentureBeat, among others, for her work on algorithmic bias and transparency, criminal justice risk assessment tools, and the limitations of AI.
Prior to joining PAI, Alice worked as an attorney at Gunderson Dettmer, representing startups and venture capital firms. She has also worked in civil appellate litigation at the Department of Justice, econometrics research at the Federal Reserve, and data science at LinkedIn. Alice holds a Juris Doctor from Yale Law School, a Master’s in Development Economics from Oxford, a Master’s in Statistics from Harvard, and a Bachelor’s in Economics from Harvard.