Yuhang Wu 吴雨航

I'm a quantitative analyst at KEPL group, Cubist systematic strategies. I received my Ph.D. in Operations Research from UC Berkeley's IEOR department and Berkeley AI Research Lab (BAIR) in three and a half years. Previously, I received my B.S. degree in Statistics from School of Mathematical Sciences at Peking University. Contact University of California, Berkeley Email: wuyh ᴀᴛ berkeley.edu

Research Interests

I mainly work on applied statistics and probability, especially theory and applications of experimental design and causal inference.

Selected Publications and Manuscripts

1. A/B Test and Online Experiment Under Diminishing Marginal Effects: Regret Minimization and Statistical Inference Jingxu Xu, Yuhang Wu, Yingfei Wang, Chu Wang, Zeyu Zheng
   SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
2. Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Boostrapping Pu Yang, Yunzhen Feng, Ziyuan Chen, Yuhang Wu, Zhuoyuan Li
   Advances in Neural Information Processing Systems (NeurIPS), 2025, Spotlight
3. Technical Note: Adaptive A/B Tests and Simultaneous Treatment Parameter Optimization Yuhang Wu, Zeyu Zheng, Guangyu Zhang, Zuohua Zhang, Chu Wang
   Extended abstract appeared in Marketplace Innovation Workshop (MIW), 2024
   Operations Research, to appear
4. Performance Evaluation and Stochastic Optimization with Gradually Changing Non-Stationary Data Yuhang Wu, Zeyu Zheng
   Operations Research, to appear
5. Non-stationary A/B Tests: Optimal Variance Reduction, Bias Correction, and Valid Inference Yuhang Wu, Zeyu Zheng, Guangyu Zhang, Zuohua Zhang, Chu Wang
   Management Science, 2024
6. Best Arm Identification with Fairness Constraints on Subpopulations Yuhang Wu, Zeyu Zheng, Tingyu Zhu
   Winter Simulation Conference (WSC), 2023
7. Non-stationary A/B Tests Yuhang Wu, Zeyu Zheng, Guangyu Zhang, Zuohua Zhang, Chu Wang
   SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

Experiences

• Quantitative Analyst Internship, KEPL Group, Cubist Systematic Strategies
  New York, US, May-August 2024
  KEPL is a fast-growing multi-asset systematic trading team at Cubist/Point72. We are actively looking for quant researcher/engineer talents at different levels. If you are interested, feel free to contact me.

Services

Rreviewer for:

• Journals: Operations Research, Management Science, Naval Research Logistics, Probability in the Engineering and Informational Sciences

• Conferences: ICML, AISTATS, KDD, WSC