Jie Wang

Jie Wang Assistant Professor School of Artificial Intelligence (home department) and School of Data Science The Chinese University of Hong Kong, Shenzhen Contact: Email, Github, Google Scholar CV (Updated on 2025-06-26) Research Statement I am currently seeking highly motivated research interns (RAs) and Ph.D. students to join my group

Short Bio

I got my PhD in Industrial Engineering from Georgia Institute of Technology, advised by Prof. Yao Xie. I obtained Bachelor in Pure Mathematics from The Chinese University of Hong Kong, Shenzhen. My research develops statistics and optimization methodologies with applications in machine learning.

Awards

• Winner, INFORMS 2024 Data Mining Society's Data Competition (1 out of 26)

• Runner-up, INFORMS 2024 Computing Society Student Paper Award

• Runner-up, INFORMS 2024 Data Mining Best Paper Award Competition

• Finalist, Next-Gen Scholar’s Symposium 2024

• Finalist, INFORMS 2023 Data Mining Society's Data Competition (4 out of 21)

• Winner, Data Mining Best Theoretical Paper, 2023 INFORMS Workshop on Data Mining and Decision Analytics

• Travel Award, Mixed Integer Programming Workshop 2023

• 2022 ISyE Robert Goodell Brown Research Excellence award (Data Science and Statistics Track)

• Honorable Mention, Best Student Poster Award, Georgia Statistics Day 2022

• Winner, 2022 INFORMS Poster Competition

• Best Performance Award for Ph.D. Comprehensive Exam in Statistics, 2021

• Travel Award, 2024 IEEE Information Theory Workshop

• Travel Award, IEEE International Symposium on Information Theory 2019 and 2024

Talks

• 9 December 2024, HKUST IEDA Seminar: Regularization for Adversarial Robust Learning

• 4 December 2024, SJTU ACEM Seminar: Regularization for Adversarial Robust Learning

• 30 November 2024, CUHK(SZ) SDS Program Seminar: Regularization for Adversarial Robust Learning

• 18 November 2024, Tsinghua University IE Program Seminar: Regularization for Adversarial Robust Learning

• 12 November 2024, Singapore University of Technology and Design ESD Pillar Seminar: Regularization for Adversarial Robust Learning

• 18 October 2024, HKUST(GZ) IoT Thrust Seminar: Regularization for Adversarial Robust Learning

• 2024 Asilomar Conference on Signals, Systems, and Computers

• 2024 SIAM Conference on Mathematics of Data Science

• 2024 INFORMS Annual Meeting, oral talk

• 2024 Next-Gen Scholar's Symposium

• 2024 Purdue Operations Conference

• 2024 IEEE International Symposium on Information Theory (ISIT), Athens, Greece

• 2024 Princeton Workshop on Optimization, Learning, and Control

• 2024 International Symposium on Mathematical Programming

• 2024 ISyE Junior Researcher Workshop

• 2024 INFORMS Optimization Society Conference

• 2023 INFORMS Annual Meeting, oral talk and poster presentation

• 2023 INFORMS Workshop on DMDA

• 2023 SIAM Conference on Optimization

• 2023 Mixed Integer Programming (MIP) Workshop

• 2023 ICERM Linear and Non-Linear Mixed Integer Optimization Workshop

• 2022 INFORMS Annual Meeting, oral talk and poster presentation

• 2022 SIAM Seminar at University of Washington

• 2022 SIAM Conference on Mathematics of Data Science

• 2022 International Conference on Continuous Optimization

• 2022 North American School of Information Theory, poster presentation

• 2022 Artificial Intelligence and Statistics, virtual

• 2021 INFORMS Annual Meeting, virtual

• 2021 IEEE International Symposium on Information Theory (ISIT), virtual

• 2020 IEEE International Symposium on Information Theory (ISIT), virtual

• 2019 IEEE International Symposium on Information Theory (ISIT), Paris, France

• 2019 International Conference on Underwater Networks & Systems, Atlanta, Georgia, USA

• 2018 IEEE International Symposium on Information Theory (ISIT), Vail, Colorado, USA

Service

Reviewer for OR, MSOM, TIT, JSAIT, TSP, MP, Journal of Global Optimization, Optimization Letters, Systems and Control Letters, AISTATS, ICLR, NeurIPS, ICML