Leonardo Andrés Zepeda Núñez

Welcome to my Home Page

I am an assistant professor in the Department of Mathematics at the University of Wisconsin-Madison, where I belong to the Applied and Computational Mathematics group. I am also an affiliate of the Institute for Foundations of Data Science (IFDS) at the Wisconsin Institute for Discovery (WID). Prior to UW-Madison, I was a postdoctoral fellow at the Lawrence Berkeley National Laboratory in the Mathematics group led by James Sethian, working primarily with Lin Lin., and I was a visiting assistant professor at the Department of Mathematics at the University of California, Irvine, working with Hongkai Zhao. I graduated in June 2015 from MIT with a Ph.D. in Mathematics under the direction of Laurent Demanet. I am a former student of École Polytechnique and University Pierre et Marie Curie Paris VI.

I am particularly interested in Machine Learning, Numerical Analysis, Scientific Computing, Wave Propagation and Inverse Problems. Broadly speaking my research has three main venues:

My current projects are applications of deep learning to scientific computing, using neural networks to accelerate molecular dynamics, and second order optimization methods for machine learning; fast solvers for the Helmholtz equation, and new numerical methods for quantum chemistry, in particular, numerical methods for bath parametrization within the DMFT framework.

For more details on my research and teaching please take a look at my github page.

I am always looking for self-motivated PhD students and postdocs to join my group. For students please apply through UW-Madison Math PhD program.