González-Soto, Mauricio

Mauricio González Soto holds a Bachelor's degree in Applied Mathematics and a Master's degree in Data Science from the Instituto Tecnológico Autónomo de México (ITAM). He began his career as a Data Scientist in the banking sector in Mexico, where he researched the propagation of financial risk through graphs and complex systems. Later, at a start-up, he focused on analysing conversations on social media by applying network theory. His interest in the fundamentals led him to pursue a PhD in Computer Science at the National Institute of Astrophysics, Optics and Electronics (INAOE), under the supervision of Enrique Sucar and Hugo J. Escalante, obtaining his degree in September 2021. He then continued his academic work with a two-year postdoctoral fellowship at the University of Vienna, Austria. His research focuses on the theory and philosophy of probability, Bayesian statistics, Bayesian epistemology, causality, decision-making under uncertainty, as well as fundamental aspects of machine learning, particularly reinforcement learning due to its connection with decision-making and causality.