I am Professor of Mathematics at the University of Michigan working in high-dimensional probability and mathematical data science. I study probabilistic structures that appear across mathematics and various branches of data science, especially in random matrix theory, geometric functional analysis, convex and discrete geometry, high-dimensional statistics, information theory, learning theory, signal processing, numerical analysis, network science, and computational biology. Here you will find my research snapshots and learn more about my research and activities.
My primary appointment is in the Department of Mathematics. I am also affiliated with Michigan Institute for Data Science, the Program for Applied and Interdisciplinary Mathematics and the new Michigan Center for Single-Cell Genomic Data Analytics.
New: I have written up four lectures on probabilistic methods for data science, which I gave at the 2016 PCMI Summer School. The lectures will be published by AMS.
Up and running: Happy to announce a new journal: Mathematical Statistics and Learning. It will publish papers of highest quality in all aspects of mathematical statistics and learning, including those studied in traditional areas of statistics and in machine learning as well as in theoretical computer science and signal processing. Please send us excellent papers and enjoy reading!