Biography

I am a quantitative researcher at Citadel Securities. My research covers machine learning, statistics, and optimization.

Previously, I got my Ph.D. in Statistics from UC Berkeley, where I was fortunate to be advised by Michael I. Jordan and Martin J. Wainwright. During my graduate study, I was a member in the Berkeley Artificial Intelligence Research (BAIR) Lab. I also did several internships at Citadel Securities, Ant Financial, and Microsoft Research. I completed a B.Sc. with honors in Mathematics at the University of Hong Kong, where I completed my undergraduate theses with Ngaiming Mok in complex geometry and with Guangyue Han in coding and information theory. I was born and grew up in Shanghai, China.

• Quantitative Researcher

          Citadel Securities

          Sep. 2019 - Present

          New York, NY

• Quantitative Research Intern

          Citadel Securities

          June 2018 - Sep. 2018

          Chicago, IL

• Research-based Software Engineer with Le Song

          Ant Financial

          Dec. 2017 - Jan. 2018

          Hangzhou, China

• Graduate Student Instructor for CS 189/289A: Introduction to Machine Learning

          UC Berkeley

          Fall 2017

          Berkeley, CA

• Research Intern with Yelong Shen and Jianfeng Gao

          Microsoft Research

          Summer 2017

          Redmond, WA

• Talk on HopSkipJumpAttack: A Query-Efficient Decision-Based Attack.
  IEEE Symposium on Security and Privacy, May 2020.

• Oral and Poster on LS-Tree: Model Interpretation When the Data Are Linguistic.
  AAAI, Feb 2020.

• Spotlight Talk and Poster on ML-LOO: Detecting Adversarial Examples with Feature Attribution.
  AAAI, Feb 2020.

• Talk on model interpretation and adversarial robustness.
  Shanghai Jiao Tong University, July 2019.

• Talk on model interpretation and adversarial robustness.
  Facebook, June 2019.

• Poster on L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data.
  International Conference on Learning Representations (ICLR), May 2019.

• Oral and Poster on Learning to Explain: An Information-Theoretic Perspective on Model Interpretation.
  International Conference on Machine Learning (ICML), July 2018.

• Spotlight Talk and Poster on Language-based Image Editing with Recurrent Attentive Models.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2018.

• Poster on Kernel Feature Selection via Conditional Covariance Minimization.
  31st Neural Information Processing Systems (NIPS), December 2017.

• Poster on Nonconvex Finite-Sum Optimization Via SCSG Methods. 31st Neural Information Processing Systems (NIPS), December 2017.

• Talk on FDR control on directed acyclic graphs. 10th International Conference on Multiple Comparison Procedures, June 2017.

• Poster on Decentralized decision making on networks with FDR control. 10th International Conference on Multiple Comparison Procedures, June 2017.

• Citadel Fellowship for 2018-2019.
  Presented to an exceptional PhD graduate student in Statistics.

• Berkeley Fellowship for 2015-2017.
  Presented only to Berkeley’s top admitted doctoral students.

• Ho Sin Hang Prize in Science for 2015. Presented to the best third year B.Sc. student in physical sciences.

• Y.M. Chen Memorial Prize in Mathematics for 2015. Presented to the best third year student in mathematical analysis.

• B.Sc. Class of 1971 Prize for 2014. Presented to the best second year B.Sc. student in physical sciences.

• Wong Yung Chow Prize in Mathematics for 2014. Presented to the best second year student in Mathematics.

• Ho Fook Prize for 2013.
  Presented to the best first year B.Sc. student.

• Walter Brown Memorial Prizes in Mathematics for 2013. Presented to the best first year student in Mathematics.

• jianbochen at berkeley dot edu