Pablo Hernandez Leal
Pablo is a Senior Machine Learning Researcher. Pablo is interested in how learning algorithms developed for single-agent environments should be adapted to multiagent settings. One of his objectives is to propose efficient multiagent learning algorithms for strategic interactions using models and concepts from game theory, Bayesian reasoning, and reinforcement learning.
Before joining Borealis Pablo studied at INAOE in Mexico and at Washington State University in the USA, later he worked as a researcher at CWI, the National Research Institute for Mathematics and Computer Science of the Netherlands.
Born and raised in Mexico, Pablo loves tacos and spicy food. After living in Amsterdam for a couple of years, he likes biking to work although the Canadian weather sometimes makes this impossible.