## Seminars

## Applied Mathematics Department Colloquium - Nick Trefethen

Oct. 3, 2024

Nick Trefethen, Professor of Applied Mathematics in Residence, Harvard University The AAA Algorithm for Rational Approximation With the introduction of the AAA algorithm in 2018 (Nakatsukasa-Sete-T., SISC), the computation of rational approximations changed from a hard problem to an easy one. We've been exploring the implications of this transformation ever...

## Applied Mathematics Department Colloquium - Ioannis Kevrekidis

Sept. 12, 2024

Ioannis Kevrekidis, Bloomberg Distinguished Professor, Department of Applied Mathematics and Statistics, Johns Hopkins Whiting School of Engineering No Equations, No Variables, No Space and No Time: Data and the Modeling of Complex Systems I will give an overview of a research path in data driven modeling of complex systems over...

## Applied Mathematics Colloquium - Dane Taylor

May 24, 2024

Dane Taylor, Department of Mathematics and Statistics, University of Wyoming Consensus processes over networks: Past, present, and future Models for consensus---that is, the reaching of agreement---have been developed, e.g., to study how group decisions are collectively made within social networks, how groups of animals collectively move, and how decentralized machine-learning...

## Applied Mathematics Colloquium - Cecilia Diniz Behn

April 12, 2024

Cecilia Diniz Behn, Department of Applied Mathematics and Statistics, Colorado School of Mines Dynamics of sleep homeostasis The “homeostatic sleep drive” describes sleep need that increases during wake and decreases during sleep. Using a physiologically-based mathematical model of sleep-wake regulatory neurophysiology, we simulate sleep-wake behavior under conditions representing individuals with...

## Applied Mathematics Colloquium - Mark Ward

March 8, 2024

Mark Ward, Department of Mathematics, Purdue University The Data Mine Model for Partnerships The Data Mine at Purdue University is a pioneering experiential learning community for undergraduate and graduate students of any background to learn data science. The first data-intensive experience embedded in a large learning community, The Data Mine...

## Applied Mathematics Colloquium - Leonid Berlyand

March 1, 2024

Leonid Berlyand, Department of Mathematics, Penn State University Enhancing Accuracy in Deep Learning Using Random Matrix Theory We discuss applications of random matrix theory (RMT) to the training of deep neural networks (DNNs). Our focus is on the pruning of DNN parameters, guided by the Marchenko-Pastur spectral RMT approach. Our...

## Applied Mathematics Colloquium - Chad Topaz

Feb. 23, 2024

Chad Topaz, Professor of Complex Systems, Williams College Data Science for Criminal and Social Justice Tens of millions of people in the United States have been directly impacted by the criminal justice system, with nearly half the population affected through close familial or social ties. Alongside the direct harm inflicted...

## Applied Mathematics Colloquium - Pascale Garaud

Feb. 16, 2024

Pascale Garaud; Department of Applied Mathematics; University of California, Santa Cruz Regimes of stratified turbulence across parameter space: from asymptotic analysis to DNS In this talk I will present recent theoretical and numerical progress in modeling the dynamics of stratified turbulence in regimes appropriate of the Earth's atmosphere and oceans,...

## Applied Mathematics Colloquium - Donna Calhoun

Feb. 9, 2024

Donna Calhoun, Department of Mathematics, Boise State University Coupling scientific software through the adaptive tree-based library ForestClaw Coupling scientific research codes presents several challenges. The codes may not be on the same mesh, so results from each simulation must be communicated between meshing environments. Each simulation likely comes with its...

## Applied Mathematics Colloquium - Gunilla Kreiss

Jan. 26, 2024

Gunilla Kreiss, Department of Information Technology, Uppsala University Cut FEM meets finite differences There is a cut-FEM methodology with ghost penalty stabilization, which can be applied to hyperbolic conservation laws and wave equations, and allows for using Cartesian grids. Explicit time-stepping is preferable for hyperbolic problems. The stabilization will ensure...