He received his PhD in Applied Mathematics and Scientific Computation from the University of Maryland in 2014, and was then a Gibbs Assistant Professor of Mathematics at Yale University until 2017, when he joined UCSD. His research interests are in applied harmonic analysis, machine learning and neural networks, diffusion geometry, analysis of graphs and data sets sampled from continuous geometric structures embedded in high-dimensional spaces, and applications in treatment effectiveness, medical imaging, and other various scientific domains.