Mauricio Tec is a Postdoctoral Researcher at the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. Previously, he completed his Ph.D. in Statistics at the University of Texas at Austin. His main research interest is developing new AI and statistical methods for public policy, healthcare, and scientific applications. He considers major challenges like causality, sequential decisions, uncertainty quantification, and modeling complex structured data. Thus, he focuses mainly on deep and reinforcement learning, Bayesian statistics, and causal inference techniques. He believes that AI can revolutionize scientific discovery when combined with rigorous statistical modeling and collaboration with domain experts. His application domains have included climate change, epidemiology, and cancer research. He is personally interested in robotics and has competed in the Robocup with the UT Austin Villa Robot Soccer team. For him, the most exciting research topics are those inspired by real-world problems with actionable outcomes.