Weijie Su

Hi, I am an Assistant Professor in the Wharton Statistics and Data Science Department and, by courtesy, in the Department of Computer and Information Science, at the University of Pennsylvania. I serve as a co-director of Penn Research in Machine Learning. Prior to joining Penn in Summer 2016, I obtained my Ph.D. from Stanford University in 2016, under the supervision of Emmanuel Candès. I received my bachelor's degree from Peking University in 2011.

Experience

• The Wharton School
  • Assistant Professor Jul 2016 –
• Stanford University
  • Research Assistant Sep 2011 – Jun 2016
• Microsoft
  • Research Intern Jun 2014 – Sep 2014
• Microsoft
  • Research Intern Jun 2013 – Sep 2013
• Victrio
  • Data Analyst Dec 2012 – Jan 2013
• Microsoft
  • Research Intern Jul 2010 – Sep 2010

Education

• Stanford University Doctor of Philosophy (PhD) Statistics 2011 – 2016
• Peking University Bachelor of Arts (B.A.) Economics 2008 – 2011
• Peking University Bachelor of Science (B.S.) Mathematics 2007 – 2011

Awards and Honors

• Facebook Faculty Research Award, 2020
• Alfred P. Sloan Research Fellowship, 2020
• NSF CAREER Award, 2019-2024
• Theodore W. Anderson Stanford Dissertation Award in Theoretical Statistics, 2016

Weijie Su, Stephen Boyd, Emmanuel Cand&egraves (2016), A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights, Journal of Machine Learning Research, (to appear).

Lucas Janson and Weijie Su (2016), Familywise Error Rate Control via Knockoffs, Electronic Journal of Statistics, 10 (1), pp. 960975.

Weijie Su and Emmanuel Cand&egraves (2016), SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax, Annals of Statistics , 44 (3), pp. 10381068.

Weijie Su, Malgorzata Bogdan, Emmanuel Cand&egraves (Under Review), False Discoveries Occur Early on the Lasso Path.

Damian Brzyski, Alexej Gossmann, Weijie Su, Malgorzata Bogdan (Under Review), Group SLOPE – Adaptive Selection of Groups of Predictors.

Cynthia Dwork, Weijie Su, Li Zhang (Under Review), Private False Discovery Rate Control.

Malgorzata Bogdan, Ewout van den Berg, Chiara Sabatti, Weijie Su, Emmanuel Cand&egraves (2015), SLOPE – Adaptive Variable Selection via Convex Optimization, Annals of Applied Statistics, 9 (3), pp. 11031140.

Weijie Su, Stephen Boyd, Emmanuel Cand&egraves (2014), A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights, Neural Information Processing Systems.

Past Courses

STAT431 STATISTICAL INFERENCE

Graphical displays; one and twosample confidence intervals; one and twosample hypothesis tests; one and twoway ANOVA; simple and multiple linear leastsquares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodnessoffit tests. A methodology course. This course does not have business applications but has significant overlap with STAT 101 and 102.

STAT511 STATISTICAL INFERENCE

Graphical displays; one and twosample confidence intervals; one and twosample hypothesis tests; one and twoway ANOVA; simple and multiple linear leastsquares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodnessoffit tests. A methodology course.

STAT991 SEM IN ADV APPL OF STAT

This seminar will be taken by doctoral candidates after the completion of most of their coursework. Topics vary from year to year and are chosen from advance probability, statistical inference, robust methods, and decision theory with principal emphasis on applications.