David Betancourt

Ph.D. Student
Research Areas: 
Machine Learning; Reinforcement Learning; Uncertainty Modeling; Computational Mechanics; Autonomous Decision-Making; Anomaly Detection; Time Series Prediction

My Ph.D. research is at the intersection of machine learning, uncertainty modeling, and numerical methods. In particular, I am developing machine learning algorithms that can be used in domains under significant uncertainty—with randomness, imprecise data, hidden information, and partial observability. Ultimately, the main goal of my research is to develop methods and algorithms for autonomous decision-making and control, where artificial agents have to act in real-world situations. The applications of my research include: physical infrastructure systems, markets & finance, cloud computing, and cyber-security.