Yu-Jui Huang's research is focused on Mathematical Finance and the Mathematics for Machine Learning. It involves theories and techniques from stochastic analysis, stochastic control, optimal stopping, and viscosity solutions to fully nonlinear PDEs. Current projects involve optimization under time-inconsistent behaviors, systemic risk, and gradient-flow frameworks for machine learning.
