The focus of this seminar is various methods in scientific computing, the analysis of their convergence properties and computational efficiency, and their adaptation to specific applications.

The seminar meets Mondays 1:30-2:20pm EST in TBD. Meeting details are included in the weekly seminar announcements.

Date	Speaker and Title
Jan 31	Alex Townsend (Cornell University) An approximation theory perspective on feed-forward neural networks
Feb 07	Nicolas Boulle (University of Oxford) Data-driven discovery of Green's functions
Feb 14
Feb 21
Mar 07	Alice Cortinovis (EPFL) On randomized algorithms for trace estimation
Mar 14
Mar 21	Shanyin Tong (Courant Institute, NYU) Extreme Event Probability Estimation using PDE-Constrained Optimization and Large Deviation Theory, with Application to Tsunamis
Apr 11	Jason Kaye (Simons Foundation) Accelerating Greens function methods for time-dependent quantum many-body calculations: fast history integration for Dyson equations
Apr 18	Mallory Gaspard (Cornell University) Optimal Driving Under Traffic Signal Uncertainty
	MingYi Wang (Cornell University) Optimal Adaptive Cancer Therapy in a Stochastic Setting
Apr 25	Vasileios Charisopoulos (Cornell University) A superlinearly convergent subgradient method for sharp semismooth problems
	Megan Renz (Cornell University) Compressing Neural Networks with Interpolative Decompositions
May 02	No seminar
May 09	Michael Lindsey (Courant Institute of Mathematical Sciences, New York University) A sampling of quantum Monte Carlo methods