Haoting Zhang

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haoting_zhang@berkeley.edu

My name is Haoting Zhang. I am a Ph.D. student in the Department of Industrial Engineering & Operations Research (IEOR) at the University of California, Berkeley. I am advised by Prof. Zeyu Zheng and Prof. Rhonda Righter. I enjoy doing research at the intersection of simulation analytics and machine learning, to bring together the relative strengths of OR methods and machine learning. I have done two internships at Amazon Supply Chain Optimization Technology (SCOT), working on improving customer experience related to supply chain and monitoring overstock inventory management.

Education

Ph.D. in Operations Research from the University of California, Berkeley (Expected 2025)
Committee: Zeyu Zheng, Rhonda Righter, Zuo-Jun (Max) Shen, Park Sinchaisri
M.S. in Operations Research from the University of California, Berkeley (2021)
B.S. in Mathematics from Sichuan University (2019)

Research Interests

Simulation Analytics, Stochastic Systems, and Machine Learning

Publications

  1. Clustering Then Estimation of Spatio-Temporal Self-Exciting Processes LINK
    Haoting Zhang, Donglin Zhan, James Anderson, Rhonda Righter, and Zeyu Zheng
    INFORMS Journal on Computing, 2024
  2. Daily Physical Activity Monitoring–Adaptive Learning from Multi-source Motion Sensor Data LINK
    Haoting Zhang, Donglin Zhan, Yunduan Lin, Jinghai He, Qing Zhu, Zuo-Jun (Max) Shen, and Zeyu Zheng
    In Conference on Health, Inference, and Learning (CHIL), 2024
  3. Enhancing Language Model with Both Human and Artificial Intelligence Feedback Data LINK
    Haoting Zhang, Jinghai He, Jingxu Xu, Jingshen Wang, and Zeyu Zheng
    In 2024 Winter Simulation Conference (WSC), 2024
    (Selected as the Best Theoretical Paper Award at WSC 2024)
  4. Contextual Gaussian Process Bandits with Neural Networks LINK
    Haoting Zhang, Jinghai He, Rhonda Righter, Zuo-Jun (Max) Shen, and Zeyu Zheng
    In Advances in Neural Information Processing Systems, 2023
  5. Neural Network-Assisted Simulation Optimization with Covariates LINK
    Haoting Zhang, Jinghai He, Donglin Zhan, and Zeyu Zheng
    In 2021 Winter Simulation Conference (WSC), 2021
  6. Simulating Nonstationary Spatio-Temporal Poisson Processes using the Inversion Method LINK
    Haoting Zhang, and Zeyu Zheng
    In 2020 Winter Simulation Conference (WSC), 2020
    (Selected as the Best Theoretical Paper Award at WSC 2020)

Working Papers

  1. Language Model Prompt Selection via Simulation Optimization LINK
    Haoting Zhang, Jinghai He, Rhonda Righter, and Zeyu Zheng
    Under Major Revision at Management Science
  2. Machine Learning-Assisted Stochastic Kriging Metamodels for Offline Simulation Online Application LINK
    Haoting Zhang, Jinghai He, Rhonda Righter, Zuo-Jun (Max) Shen, and Zeyu Zheng
    Under Major Revision at INFORMS Journal on Computing
  3. Does Attention in Transformers Help Wildfire Prediction? LINK
    Yunkai Zhang, Donglin Zhan, Haoting Zhang, Zuo-Jun (Max) Shen, Zeyu Zheng, and Qing Zhu
    short version accepted by INFORMS Workshop on Data Mining and Decision Analytics 2024

Teaching Experience

  • Graduate Student Instructor
    • IEOR 263A Applied Stochastic Process I, Fall 2024
    • IEOR 166 Decision Analytics, Fall 2023

Industrial Internships

  • Applied Scientist Intern (May 2024 – Aug. 2024)
    • Department of Supply Chain Optimization Technology (SCOT) at Amazon, Bellevue, WA
  • Applied Scientist Intern (June 2023 – Sep. 2023)
    • Department of Supply Chain Optimization Technology (SCOT) at Amazon, Bellevue, WA