Alex Cloninger received his Ph.D. in Applied Mathematics and Scientific Computation from the University of Maryland in 2014. He was then a NSF Postdoc and Gibbs Assistant Professor of Mathematics at Yale University until 2017, when he joined UCSD.  Alex conducts research in the area of geometric data analysis, including manifold learning, optimal transport, kernel methods, and deep learning.