Yuhang Wu 吴雨航

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I am a fourth-year Ph.D. candidate in IEOR at the University of California, Berkeley, advised by Professor Zeyu Zheng.
Previously, I received my B.S. degree in Statistics in July 2021 from School of Mathematical Science, Peking University, where I was also a member of Elite Program for Applied Mathematics and Statistics.

Contact

Department of IEOR
University of California, Berkeley
Email: wuyh ᴀᴛ berkeley.edu

Research Interests

    My research interest lies in the broad fields of statistics and applied probability, especially theory and applications of experimental design and causal inference.

Selected Publications and Manuscripts

  1. Debiasing Seller-Side Experiments via Multinomial Logit Models in Two-Sided Plaforms Chenyu Zhang, Yuhang Wu, Zeyu Zheng, Nian Si
    Preliminary version appeared in Conference on Digital Experimentation @ MIT (CODE@MIT), 2024
  2. Technical Note: Adaptive A/B Tests and Simultaneous Treatment Parameter Optimization Yuhang Wu, Zeyu Zheng, Guangyu Zhang, Zuohua Zhang, Chu Wang
    Major revision requested at Operations Research
    Preliminary version appeared in Ninth Market Innovation Workshop (MIW) 2024, and also Amazon 2024 Consumer Science Summit
  3. Large Language Model Enhanced Machine Learning Estimators for Classification Yuhang Wu, Yingfei Wang, Chu Wang, Zeyu Zheng
    Winter Simulation Conference (WSC), 2024
  4. A Preliminary Study on Accelerating Simulation Optimization with GPU Implementation Jinghai He, Haoyu Liu, Yuhang Wu, Zeyu Zheng, Tingyu Zhu
    Winter Simulation Conference (WSC), 2024
  5. Performance Evaluation and Stochastic Optimization with Gradually Changing Non-Stationary Data Yuhang Wu, Zeyu Zheng
    Operations Research, to appear
  6. 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
  7. Best Arm Identification with Fairness Constraints on Subpopulations Yuhang Wu, Zeyu Zheng, Tingyu Zhu
    Winter Simulation Conference (WSC), 2023
  8. 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

Talks

  1. INFORMS Annual Meeting, session on "Exploration, Experimental Design, and Algorithmic Decision Making", Seattle, US, October 2024

  2. Ninth Marketplace Innovation Workshop (MIW), Virtual, May 2024

  3. Annual POMS Conference, session on "Experimentation", Minneapolis, US, April 2024

  4. Winter Simulation Conference, San Antonio, US, December 2023

  5. INFORMS Annual Meeting, sessions on "Experimental Design and A/B Tests in Marketplaces" and "Learning and optimization in nonstationary environments", Phoenix, US, October 2023

  6. INFORMS Annual Meeting, session on "Data-driven Decision-making: Understanding and Improving Standard Policies", Indianapolis, US, October 2022

  7. Amazon ATS Science Summit, Barcelona, Spain, September 2022

  8. SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), session on "Mining, Inference and Learning", Washington, D.C., US, August 2022

Experiences

  1. Research analyst intern at Team KEPL, Cubist Systematic Strategies
    New York, US, May-August 2024
    I had a really enjoyable summer there. If you are interested in KEPL, feel free to contact me.

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