Jiaming is an assistant professor in data science and computer science at the University of Rochester. He was a postdoctoral researcher at Yale CS department, under the supervision of Andre Wibisono. He obtained PhD in operations research at Georgia Tech, advised by Renato Monteiro.
Jiaming’s primary research goal is to design, analyze, and implement fast algorithms for solving a general class of problems in data science. His research interests broadly include topics in optimization and sampling, such as convex and nonconvex optimization, nonsmooth optimization, stochastic optimization, and high-dimensional sampling algorithms.