Khipu 2021 Event Series are monthly online meetings to support the advancement of AI talent in Latinamerica. Each event will feature two sessions covering: Conversations on AI and Applications on AI
April event speakers
PART 1 — REINFORCEMENT LEARNING AS A PATH TO AGI
Doina Precup teaches at McGill while conducting fundamental research on reinforcement learning, working in particular on AI applications in areas that have a social impact, such as health care. She’s interested in machine decision-making in situations where uncertainty is high.
She is a senior fellow of the Canadian Institute for Advanced Research, fellow of the Association for the Advancement of Artificial Intelligence and she also heads the Montreal office of Deepmind.
Richard S. Sutton is one of the pioneers of reinforcement learning, an approach to artificial and natural intelligence that emphasizes learning and planning from sample experience, and a field in which he continues to lead the world. He is most interested in understanding what it means to be intelligent, to predict and influence the world, to learn, perceive, act, and think.
Richard is the Chief Scientific Advisor of Amii, a Distinguished Research Scientist at DeepMind and a Professor at the University of Alberta’s Department of Computing Science.
PART 2 — CHALLENGES AND OPPORTUNITIES OF RL IN THE REAL WORLD
Ana L. C.
Ana L. C. Bazzan holds a PhD degree from the University of Karlsruhe in Germany, and is a full professor at the Informatics Institute of the Federal University of Rio Grande do Sul (UFRGS) in Brazil. She has served several times as member of the AAMAS (and other conferences) program committee (as PC member or senior PC member) and was an associated editor for: J. of Autonomous Agents and Multiagent Systems, Advances in Complex systems, and Mutiagent and Grid Systems, among others. She served as a member of the IFAAMAS board (2004-2008 and 2014-2018) and, in 2020, she was a recipient of the Research Prize of the Rio Grande do Sul state research agency.
Her research interests include multiagent systems, agent-based modeling and simulation, machine learning, multiagent reinforcement learning, evolutionary game theory, swarm intelligence, and complex systems. Her work is mainly applied in domains related to traffic and transportation.
Montserrat currently is a Senior Research Engineer working at Google Brain, her research interest involves natural language processing techniques such as speech recognition. She also has developed projects about data analysis and statistical modeling. She is currently working at Google Brain Robotics.
She studied a bachelor’s degree in Computer Science at Tecnológico de Monterrey and a Masters degree in Statistics at Carnegie Mellon University. During her professional career she had developed projects at Microsoft, Carnegie and Google.
Juan Andrés Bazerque received the B.Sc. degree in electrical engineering from Universidad de la República (UdelaR), Montevideo, Uruguay, in 2003, and the M.Sc. and Ph.D. degrees from the Department of Electrical and Computer Engineering, University of Minnesota (UofM), Minneapolis, in 2010 and 1013 respectively.
Since 2015 he has been an Assistant Professor with the Department of Electrical Engineering at UdelaR. His current research interests include stochastic optimization and networked systems, focusing on reinforcement learning, graph signal processing, and power systems optimization and control. Dr. Bazerque is the recipient of the UofM's Master Thesis Award 2009-2010, and co-recipient of the best paper award at the 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communication 2007.