Dr. Gubanov is an assistant professor and a lead PI on a multi-year NSF ($550K) grant and a Casey DeSantis Cancer Innovation Fund ($1.2M) consortium grant with Moffitt Cancer Center to develop new AI for better cancer practices. He earned his PhD from the University of Washington and completed a postdoc at MIT CSAIL. His honors include the Amazon AI AWS Research Award, the Communications of the ACM (CACM) Award, the ACM SIGMOD Research Highlights Award, and the IEEE ICDE Best Paper Award.

Dr. Feng’s recent research focuses on machine learning theory and algorithm design, reinforcement learning in stochastic control, conditional McKean–Vlasov SDEs, data-driven modeling, and the signature method. He is also interested in stochastic analysis, rough path theory, and sub-Riemannian geometry.