Jie Shen

School: Schaefer School of Engineering & Science
Department: Computer Science
Building: Gateway South Building
Room: 351
Email: jie.shen@stevens.edu

Ph.D. in Computer Science, Rutgers University, 2018

M.S. in Computer Science, Shanghai Jiao Tong University, 2014

B.S. in Mathematics, Shanghai Jiao Tong University, 2011


My research interests lie in both the theoretical aspects and applications of machine learning. I am particularly interested in high-dimensional statistics, large-scale optimization, and their interplay. The problems that I have been working on include: low-rank matrix recovery, variable selection, online and stochastic optimization, active learning, and statistical social science.


Graduate Research Assistant, Rutgers University, 2014 - 2018

Visiting Scholar, National University of Singapore, 2013 - 2014

Graduate Research Assistant, Shanghai Jiao Tong University, 2011 - 2013

Professional Service

Conference Reviewer:

  • ICML 2019, 2018, 2017, 2016

  • NeurIPS 2018, 2017, 2016, 2015

  • COLT 2018

  • AISTATS 2019

Journal Reviewer: 

  • IEEE Transactions on Information Theory

  • Information and Inference: A Journal of the IMA

  • IEEE Transactions on Pattern Analysis and Machine Intelligence

  • IEEE Transactions on Image Processing

  • Pattern Recognition

  • Neurocomputing


Assistant Professor, Stevens Institute of Technology, 2018 - present

Professional Societies

Member of Institute of Mathematical Statistics (IMS)

Selected Publications
Conference Proceedings
  1. Jie Shen, Ping Li. "Partial Hard Thresholding: Towards A Principled Analysis of Support Recovery", Proceedings of the 31st Annual Conference on Neural Information Processing Systems (NeurIPS), Long Beach, CA, USA, pages 3127-3137, 2017.
  2. Jie Shen, Ping Li. "On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit", Proceedings of the 34th International Conference on Machine Learning (ICML), Sydney, Australia, pages 3115-3124, 2017.
  3. Jie Shen, Ping Li, Huan Xu. "Online Low-Rank Subspace Clustering by Basis Dictionary Pursuit", Proceedings of the 33rd International Conference on Machine Learning (ICML), New York City, NY, USA, pages 622-631, 2016.
  4. Jie Shen, Huan Xu, Ping Li. "Online Optimization for Max-Norm Regularization", Proceedings of the 28th Annual Conference on Neural Information Processing Systems (NeurIPS), Montreal, Canada, pages 1718-1726, 2014.
  1. Jie Shen and Ping Li. "A Tight Bound of Hard Thresholding", Journal of Machine Learning Research 18(208): 1-42, 2018.
  • CS 541 Artificial Intelligence