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Academic Staff

W.J. Huang

Research Assistant Professor
Affiliation with HKU Musketeers Foundation Institute of Data Science (HKU-IDS)
Email:

huangwj@hku.hk

Tel:

3917 8255

Office:

HW 8-15

Institute of Data Science (IDS) website:

https://datascience.hku.hk/ 

Biography

Dr. Wenjie Huang is Research Assistant Professor in Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong (HKU). He is also with HKU-Musketeers Foundation Institute of Data Science. He received Ph.D. degree from the Department of Industrial Systems Engineering and Management, National University of Singapore (NUS) in 2019 and B.S. degree in the Department of Industrial Engineering from Shanghai Jiao Tong University, China in 2014. Prior to joining HKU, he held joint postdoc positions at School of Data Science, The Chinese University of Hong Kong, Shenzhen and Group for Research in Decision Analysis (GERAD), Canada. His research projects are supported by NSFC research funds, NRF Singapore and NUS Young Investigator Award.

Personal website: https://sites.google.com/view/huangwenjie

https://datascience.hku.hk/ 

 


Research Topics:

  • Decision making under uncertainty
  • Data-driven decision-making
  • Sequential decision-making
  • Operations management
  • Smart society

Selected Publications:

  1. Wenjie Huang, Jing Jiang and Xiao Liu, “Online non-convex learning for river pollution source identification”, IISE Transactions, 2022.
  2. Rui Miao, Peng Guo, Wenjie Huang, Qi Li and Bo Zhang, “Profit model for electric vehicle rental service: sensitive analysis and differential pricing strategy”, Energy, 2022.
  3. William B. Haskell, Huifu Xu and Wenjie Huang, “Preference robust optimization for choice functions on the space of CDFs”, SIAM Journal on Optimization, 2022. 
  4. Wenjie Huang and William B. Haskell, “Stochastic approximation for risk-aware Markov decision processes”, IEEE Transactions on Automatic Control, 2020.
  5. Wenjie Huang, Pham Viet Hai and William B. Haskell, “Model and reinforcement learning for Markov games with risk preferences”, AAAI, 2020.