Applied Math Colloquium

<p><strong>Porous muscles: Variational methods for active porous media</strong><br />
Vakhtang Putkaradze, PhD,&nbsp;Vice President, Transformation, Science &amp; Technology ATCO | SpaceLab</p>

<p><strong>Kinetic models of particle systems</strong><br />
Cory D. Hauck, Computer Science and Mathematics Division,&nbsp;Oak Ridge National Laboratory, and Department of Mathematics (Joint Faculty),&nbsp;University of Tennessee</p>

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<p><strong>Multidisciplinary Research in the Center for Applied Scientific Computing</strong><br />
Ming Jiang, Academic Engagement Program Lead, Lawrence Livermore National Laboratory</p>

<p><strong>From PINNs to DeepOnets: Approximating functions, functionals, and operators using deep neural networks</strong><br />
George Karniadakis, Division of Applied Mathematics, Brown University</p>

<p><strong>Classification of round lesions in dual-energy FFDM using a convolutional neural network. Simulation study</strong><br />
Brian Toner, Program in Applied Mathematics, University of Arizona</p>

<p><strong>Algebraic Optimization</strong><br />
Daniel Bienstock, Industrial Engineering and Operations Research, Columbia University&nbsp;</p>

<p><strong>Accelerated Exploration of High-Dimensional Parameter Spaces with MCMC Algorithms</strong><br />
Peter Behroozi, Department of Astronomy and Steward Observatory, University of Arizona</p>

<p><strong>Dissipation Enhancement by Mixing</strong><br />
Gautam Iyer, Department of Mathematical Sciences, Carnegie Mellon University</p>

<p><strong>No equations, no variables, no parameters, no space and no time - some new and some old results in data-driven modeling of complex dynamical systems</strong><br />
Yannis Kevrekidis, Chemical and Biomolecular Engineering, Johns Hopkins</p>

<p><strong>Machine learning and partial differential equations (PDEs)</strong><br />
Eric Vanden-Eijnden, Courant Institute of Mathematical Sciences, NYU</p>