Meet our Panelists
(alphabetically by last names)

• Yoshua Bengio (Mila) :  Yoshua Bengio, a globally recognized authority in artificial intelligence (AI), has achieved acclaim for his groundbreaking contributions to deep learning, acknowledged with the 2018 A.M. Turing Award alongside Geoffrey Hinton and Yann LeCun. Serving as a Full Professor at Université de Montréal, Bengio is also the Founder and Scientific Director of Mila – Quebec AI Institute. 

He holds key roles, co-directing the CIFAR Learning in Machines & Brains program and acting as Scientific Director of IVADO. His accolades include the 2019 Killam Prize and, in 2022, he attained the status of the most cited computer scientist globally. Bengio is a distinguished Fellow of the Royal Society of London and Canada, a Knight of the Legion of Honor of France, an Officer of the Order of Canada, and a Member of the UN's Scientific Advisory Board for Independent Advice on Breakthroughs in Science and Technology since 2023. Demonstrating his commitment to ethical AI development, Bengio actively contributed to the Montreal Declaration for the Responsible Development of Artificial Intelligence.

• Craig Boutilier (Google) :  Craig Boutilier assumed the role of Principal Scientist at Google in January 2015, marking a significant juncture in his illustrious career. Prior to this, until January 2017, he held the position of Professor in the Department of Computer Science at the University of Toronto, concurrently serving as the Canada Research Chair in Adaptive Decision Making for Intelligent Systems. In collaboration with Tyler Lu, he co-founded Granata Decision Systems from 2012 to 2015. 

His research portfolio encompasses areas such as knowledge representation, probabilistic reasoning, decision-making under uncertainty, multiagent systems, and machine learning. Currently, his focus includes preference elicitation, mechanism design, game theory, computational advertising, Markov decision processes, and probabilistic inference. With over 200 publications and eight patents (with several more pending), Dr. Boutilier has made significant contributions to the field.

Boutilier is a Fellow of the Royal Society of Canada (RSC), the Association for Computing Machinery (ACM) and the Association for the Advancement of Artificial Intelligence (AAAI). He was the recipient of the 2018 ACM/SIGAI Autonomous Agents Research Award, He was awarded a Tier I Canada Research Chair, an Isaac Walton Killam Research Fellowship, and an IBM Faculty Award. He received the Killam Teaching Award from University of British Columbia in 1997. He has also received several best paper awards throughout his research career. 

• Elad Hazan (Princeton and Google):  Elad Hazan is a professor of computer science at Princeton University. His research focuses on the design and analysis of algorithms for basic problems in machine learning and optimization. Amongst his contributions are the co-invention of the AdaGrad algorithm for deep learning, and the first sublinear-time algorithms for convex optimization. 

He is the recipient of the Bell Labs prize, the IBM Goldberg Best Paper Award twice, in 2012 and 2008, a European Research Council grant, a Marie Curie fellowship and twice the Google Research Award. He served on the steering committee of the Association for Computational Learning and has been program chair for COLT 2015. In 2017 he co-founded In8 inc. focusing on efficient optimization and control, acquired by Google in 2018. He is the co-founder and director of Google AI Princeton.

• Rob Nowak (UW Madison) :  Robert Nowak is the Grace Wahba Professor of Data Science and holds the Keith and Jane Nosbusch Professorship in Electrical and Computer Engineering at the University of Wisconsin-Madison. His research focuses on machine learning, optimization, and signal processing. He serves on the editorial boards of the SIAM Journal on the Mathematics of Data Science and the IEEE Journal on Selected Areas in Information Theory.

His research has been recognized with several awards, such as the 2014 IEEE W.R.G. Baker Award for the most outstanding paper in any IEEE publications.  He has collaborated with The New Yorker magazine to create a unique interactive crowdsourcing system for their weekly cartoon caption contest. The system invites readers to submit witty captions for a cartoon, generating thousands of entries and up to one million ratings every week. The system adaptively focuses the crowd toward rating the funniest captions using multi-armed bandit algorithms, leading to more statistically precise rankings compared to traditional crowdsourcing methods.

• Tobias Schnabel (Microsoft Research) :  Tobias Schnabel is a researcher in the Information and Data Sciences group, at Microsoft Research in Redmond. He is interested in improving human-facing machine learning systems in an integrated way, considering not only algorithmic but also human factors.

His research draws from causal inference, reinforcement learning, machine learning, HCI, and decision-making under uncertainty. His work has often used recommender systems or information retrieval systems as natural application domains. Before joining Microsoft, Tobias obtained his Ph.D. from the Computer Science department at Cornell under Thorsten Joachims.