Stats, Optimization, and Machine Learning Seminar - Abtin Rahimian

Abtin Rahimian, Courant Institute of Mathematical Sciences, New York University

Fast algorithms for structured matrices in simulations of physical systems

 Real-world complex phenomena are typically characterized by interacting physical processes, uncertain parameters, dynamic boundaries, and close coupling over a wide span of spatial and temporal scales. Predictive computational models of such phenomena inherit these characteristics and require many novel algorithmic components. In this talk, I will identify some common features and challenges in physical modeling, focusing on cellular hemodynamics and cell biomechanics, and outline algorithms that enable predictive simulations of these processes. I will discuss some recent advances in efficiently solving large linear systems arising from the discretization of such models using the Tensor-Train decomposition.