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 135,000 citations found by Google Scholar in September 2017, with an H-index of 125).

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.

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.

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 appearing in venues such as Science, Cell, and Nature Genetics.

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. Her teaching was recognized via the Stanford Medal for Excellence in Fostering Undergraduate Research, and as a Bass University Fellow in Undergraduate Education

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.

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.

Kathryn Hume  oversees the application of research for RBC’s artificial intelligence institute, helps guide company strategy, and assists in supporting Borealis AI’s brand profile among its audience.

She was previously VP of product and strategy at AI-powered software platform integrate.ai, which has raised $50 million to date, including a $39 million Series A round in September 2018. She was also previously the director of sales and marketing at machine-intelligence research company, Cloudera Fast Forward Labs. Hume frequently speaks and writes about AI and teaches courses on enterprise adoption of AI, law and ethics at Harvard, MIT, Stanford, and the University of Calgary.

Naveen Singla leads the Data Science Center of Excellence for Bayer. His team is passionate about driving better decisions using data and analytics. The Center works to develop strategies and solutions for solving real-world issues, such as food security, by delving into how machines learn structure from data.

Singla has more than a decade of experience finding meaning in data for applications in the areas of biometrics, high-frequency stock trading and agriculture. During his tenure at Bayer, he has served as the director of analytics, where he helped grow the value realized from data science and establish a data-driven mindset by developing strategies, influencing leaders, and implementing solutions for improving food security. Prior to that, Singla led Predictive Analytics and was a strategic scientist working to improve decision-making processes in the R&D pipeline. He also established a learning program and culture for Bayer’s data science community of 500 employees.

Singla holds a bachelor’s degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Delhi, India, and a PhD in Electrical Engineering from Washington University in St. Louis.

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.

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.

Jacomo Corbo is Chief Scientist and Co-Founder of QuantumBlack, a McKinsey Company. He focuses on the problem of applying AI and other technology to improving the quality and scalability of QuantumBlack’s client delivery. He is passionate about helping organizations adopt AI at scale to radically improve their performance, and is responsible for architecting and overseeing work at some of QuantumBlack’s most important clients to ensure they do just that. Jacomo’s specific focus is on methodological innovations on the most complex challenges that QuantumBlack works on across industries, from manufacturing quality on sparse machine data to price and demand forecasts to pharmacovigilance problems and working capital problems.

Since 2011, Jacomo has served as a Senior Fellow at the Mack Institute for Innovation Management at the University of Pennsylvania’s Wharton School.

For five years previously, he served as the Canada Research Chair in Information and Performance Management (2011 – 2015).  Prior to this, he was a visiting scholar and research fellow in the Operations and Information Management Department at the Wharton School (2008 – 2010). Between 2006 and 2008, Jacomo was the Race Strategist for the Renault F1 Team Ltd. and was subsequently the Chief Race Strategist for the Lotus Renault F1 Team.

Jacomo holds a Ph.D. from the Department of Computer Science at Harvard University, an S.M. in Applied Mathematics from the Harvard Graduate School of Engineering and Applied Sciences, and a B.Eng. in Electrical Engineering from McGill University.

Jose 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).

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.

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.

Geoff Benton joined 23andMe in 2010 and leads a team focused on developing the next generation of data-driven health products for 23andMe customers. This team works to keep 23andMe at the forefront of science and technology, driving the development of interventional studies and predictive models for human health that utilize genetics, lifestyle, and environment. Previously, he was a venture capital intern at Burrill and Company. Geoff earned his PhD in Cell Biology from the University of California, San Francisco.

Hao Liu is currently working as a research scientist at Business Intelligence Lab, Baidu Research. He is the core member of the intelligent transportation product of Baidu Maps. His research interests are in the areas of large-scale data mining and big data processing. Hao received his BSc degree from the South China University of Technology (SCUT) in 2012 and his PhD degree from the Hong Kong University of Science and Technology (HKUST) in 2017, respectively.