About
I am a Ph.D. candidate in Supply Chain, Operations, and Technology at Olin Business School, Washington University in St. Louis. I’m fortunate to be advised by Prof. Dennis Zhang and Prof. Raphael Thomadsen. My research interests are causal inference, machine learning, and data-driven optimization. I’m also interested in their application in marketing, operations, and quantitative finance.
Contacts
- sikun [at] wustl [dot] edu
- xusikun96 [at] gmail [dot] com
Education
- Olin Business School, Washington University in St. Louis (2021-now)
- Ph.D. in Supply Chain, Operations, and Technology
- Columbia University in the City of New York (2019-2020)
- M.S. in Operations Research
- Data Science Institute Scholar
- Shanghai Jiao Tong University (2015-2019)
- B.S. in Industrial Engineering
Conference Proceedings
- Sikun Xu, Ruoyi Ma, Daniel K. Molzahn, Hassan Hijazi, and Cédric Josz. “Verifying Global Optimality of Candidate Solutions to Polynomial Optimization Problems using a Determinant Relaxation Hierarchy.” 60th IEEE Conference on Decision and Control (2021).
Work in Progress
- Causal Inference with Unstructured Data as Control Variables, with Dennis Zhang, Zhenling Jiang, and Zhengling Qi
- Winner’s Curse in Personalized Targeting: Evidence and Solutions, with Dennis Zhang and Raphael Thomadsen
Invited Talks and Conference Presentations
- Winner’s Curse in Personalized Targeting: Evidence and Solutions
- 2024 Conference on Artificial Intelligence, Machine Learning, and Business Analytics (Yale)
- Causal Inference When Controlling for Unstructured Data
- 2024 INFORMS Annual Meeting (Seattle, Sesssion Chair)
- 2024 POMS Annual Conference (Minneapolis)
- 2023 INFORMS Annual Meeting (Phoenix)
- 2023 POMS Annual Conference (Orlando): Data-driven security selection for wealth management
- 2022 INFORMS Annual Meeting (Indianapolis): Data-driven security selection for wealth management
- 2021 INFORMS Annual Meeting (Virtual): Verifying global optimality of candidate solutions to polynomial optimization problems using a determinant relaxation hierarchy [slide]
Guest Lecturer
- Washington University in St. Louis (MGT680E, 2024 Fall)
- Columbia University (IEOR4721, 2022 Spring)
- Columbia University (IEOR4721, 2021 Summer)
Teaching
Teaching Assistants
Columbia University in the City of New York
- IEOR4742 Deep Learning; FL2020
- IEOR4525 Machine Learning; SP2020
Washington University in St. Louis
- SCOT519E Revenue Management; FL2022
- SCOT5704 Operations Management; FL2022
- SCOT500D Project Management; FL2022, SP2023
- SCOT500M Supply Chain Analytics: Stochastic Models; SP2023, SP2024
- SCOT400D Supply Chain Analytics; SP2023
- SCOT558 Advanced Operations Strategy; FL2023
- SCOT356 Operations and Manufacturing Management; FL2024
- MGT680E AI & Machine Learning Business Applications; FL2024
Academic Services
- Session Chair at INFORMS Annual Meeting (2024)
- Reviewer for Journal of Investment Strategies