Madelein Udell

Madeleine Udell is a PhD candidate in Computational and Mathematical Engineering at Stanford University. She has served as a TA and as an instructor for EE364a at Stanford. Her research applies convex optimization techniques to a variety of non-convex applications, including sigmoidal programming, biconvex optimization, and structured reinforcement learning problems, with applications to political science, biology, and operations research.