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. My research interests are data-driven decision-making, causal inference, learning algorithms, and sequential decision analytics. I’m also interested in their application in operations, marketing, and quantitative finance.

Contacts

• sikun [at] wustl [dot] edu
• sx2265 [at] columbia [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

Publications

1. Yilun Zhang, Sikun Xu, Jie Xu, Xueqi Zeng, Zheng Li, and Chi Xie, “Robust Charging Demand Prediction and Charging Network Planning for Heterogeneous Behavior of Electric Vehicles.” Journal of Shanghai Jiao Tong University (Science) (2023).
2. 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 and Zhenling Jiang

Presentations

• 2024 POMS Annual Conference (Scheduled): Causal Inference with Unstructured Data as Control Variables
• 2023 INFORMS Annual Meeting: Causal Inference with Unstructured Data as Control Variables
• 2023 POMS Annual Conference:
  • Data-driven mechanism design and the value of data
  • Recursive hidden Markov model: financial regime Identification and Transition
• 2022 INFORMS Annual Meeting: Data-driven security selection for wealth management
• 2021 INFORMS Annual Meeting: Verifying global optimality of candidate solutions to polynomial optimization problems using a determinant relaxation hierarchy [slide]

Teaching

Columbia University in the City of New York

• IEOR 4721 AI Applications in Finance, Guest Lecturer; SU2021, SP2022
• IEOR 4742 Deep Learning, Course Assistant; FL2020
• IEOR 4525 Machine Learning, Course Assistant; SP2020

Washington University in St. Louis

• SCOT 519E Revenue Management, TA; FL2022
• SCOT 5704 Operations Management, TA; FL2022
• SCOT 500D Project Management, TA; FL2022, SP2023
• SCOT 500M Supply Chain Analytics: Stochastic Models, TA; SP2023
• SCOT 400D Supply Chain Analytics, TA; SP2023
• SCOT 558 Advanced Operations Strategy, TA; FL2023