Weijie J. Su


I am an Assistant Professor of Statistics in the Department of Statistics at the Wharton School, University of Pennsylvania. I am also affiliated with the AMCS program (Applied Mathematics and Computational Science).

Prior to joining Penn in Summer 2016, I obtained my Ph.D. in Statistics from Stanford University in 2016, under the supervision of Emmanuel Cand├Ęs. I received my bachelor's degree in Mathematics from Peking University in 2011. I spent three summers at Microsoft Research (Beijing, 2010; Redmond, 2013; Silicon Valley, 2014).

My Google Scholar profile and CV.


Office: 472 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104

Email: suw AT wharton DOT upenn DOT edu

Recent news

  • I received the 2019 NSF CAREER Award.

  • In this new paper (joint with Bin Shi, Simon Du, and Michael Jordan), we obtain accelerated methods by discretizing high-resolution ODEs using a symplectic scheme.

  • In Spring 2019, I will be offering a course in gradient-based optimization methods with applications in machine learning (STAT 991).

  • The FDR-Linking theorem is introduced in a new paper. This theorem is used to understand FDR control of the Benjamini–Hochberg procedure under dependence.

  • In a new paper (joint with Bin Shi, Simon Du, and Michael Jordan), we introduce a set of high-resolution differential equations to model, analyze, interpret, and design accelerated optimization methods.