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 Gates 122 (except on 3/18 when we will meet in Rhodes 571). Meeting details are included in the weekly seminar announcements.

Date	Speaker and Title
Jan 22	Nicholas Nelsen (Caltech) An operator learning perspective on parameter-to-observable maps
Jan 29	TBA
Feb 05	Mathieu Lauriere (NYU Shanghai) Deep Backward and Galerkin Methods for Learning Finite State Master Equations
Feb 12	Jiequn Han (Flatiron Institue) Enjoy the Best of Both Worlds: A Neural-Network Warm-Start Approach for PDE Problems
Feb 19	Kirill Serkh (University of Toronto) The Approximation of Singular Functions by Series of Non-integer Powers
Feb 26	February break
Mar 04	Alexander Terenin (Cornell University) Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
Mar 11	TBA
Mar 18	John Guckenheimer (Math, Cornell) Exploring Your Environment: Biological Strategies for Controlling Motor Behaviors
Mar 25	TBA
Apr 01	Spring break
Apr 08	Fabian Faulstich (Rensselaer Polytechnic Institute) Coupled Cluster Theory — The Gold Standard of Quantum Chemistry
Apr 15	Marissa Gee (CAM, Cornell) Optimal path planning with occasionally observed random modes
	MingYi Wang (CAM, Cornell) Succeeding in a toxic environment
Apr 22	Kangbo Li (Cornell University, CS)
	Annan Yu (Cornell University, CAM) How to avoid HiPPOs
Apr 29	Didem Unat (Koç University)
May 06	Irina Tolkova (Cornell Lab of Ornithology)