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.