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HKU IDS Scholar

Dr Wenjie HUANG

Research Assistant Professor
 
HKU Musketeers Foundation Institute of Data Science and
Department of Data and Systems Engineering, HKU

📧 huangwj@hku.hk

📞 (852) 3917 8255

🏢 HW 823-A, Haking Wong Building, HKU

🌐 Department of Data and Systems Engineering

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Strategic Research Areas
Smart Society

Key Expertise

Risk Analytics and Robust Optimization; Sequential Decision-Making; Data Science/AI for Operations Management;

About Me

Dr. Wenjie Huang is Research Assistant Professor in Department of Data and Systems Engineering and Musketeers Foundation Institute of Data Science, The University of Hong Kong (HKU), recruited by HKU-100 Global Recruitment Exercise.

He received B.S. degree in Industrial Engineering and Management, with minor in Economics, from Shanghai Jiao Tong University in 2014, and then Ph.D. degree in Industrial Systems Engineering and Management, from National University of Singapore in 2019, supervised by William B. Haskell and Tang Loon Ching. Prior to joining HKU, he held joint postdoc positions at School of Data Science, The Chinese University of Hong Kong, and Department of Decision Sciences, HEC Montréal, Québec, Canada (also affiliated with Shenzhen Research Institute of Big Data and Group for Research in Decision Analysis (GERAD)), from Sep 2019 to Sep 2021, working with Prof. Erick Delage and Prof. Zizhuo Wang.

He has been acting as the role of PI/Co-PI/Co-I for Hong Kong RGC (GRF and Theme-Based) funds and NSFC (Young Scientist-Type C, General, and Original Exploration) funds. His research was selected as Finalists of 2025 IEEE CASE Best Application Paper Award, feature article by IEEE CSS-DES Newsletter, and presentation at INFORMS MSOM Conference. He is an ad-hoc reviewer/programme committee member for several top journals and conferences including: Operations Research, Journal of Machine Learning Research, IEEE Transactions on Automatic Control, INFORMS Journal on Computing, Production and Operations Management, AAAI, UAI, and IEEE CDC.

Current Research Project

Professor Zhang’s current research focuses on developing knowledge-enhanced predictive decision analytics methods to characterize the high-dimensional biological, clinical and behavioral data for drug discovery, precision medicine, and public health.

Selected Publications and Preprints

    1. Wenjie Huang, Xiaobo Li, Yinuo Lin and Lei Xu, “Efficiency versus accuracy: The optimal level of decentralization in humanitarian operations for sudden-onset disasters”, Available at SSRN 5053496, 2025.
    2. Wenjie Huang, Erick Delage and Shanshan Wang, “The role of mixed discounting in risk-averse sequential decision-making”, Available at SSRN 5013140, 2025.
    3. Jian Wu, William B. Haskell, Wenjie Huang and Huifu Xu, “Efficiently computing the quasi-concave envelope with incomplete information”, under 2nd round review, SIAM Journal on Optimization, arXiv preprint arXiv:2008.13309v6, 2026. 
    4. Yupeng Wu, Wenyun Li, Wenjie Huang and Chin Pang Ho, “DRL-ORA: Distributional reinforcement learning with online epistemic risk adaptation”, Conference on Uncertainty in Artificial Intelligence (UAI), 2026.  
    5. Jian Wu, William B. Haskell, Wenjie Huang and Huifu Xu, “Robust data-driven quasi-concave optimization”, INFORMS Journal on Computing, 2026. 
    6. Junjie Lei, Wenjie Huang and Zizhuo Wang, “Assortment planning under spectral risk measures”, European Journal of Operational Research, 2026. 
    7. Wenjie Huang, Jing Jiang and Xiao Liu, “Online non-convex learning for river pollution source identification”, IISE Transactions, 2023.  
    8. William B. Haskell, Huifu Xu and Wenjie Huang, “Preference robust optimization for choice functions on the space of CDFs”, SIAM Journal on Optimization, 2022.  
    9. Wenjie Huang, Pham Viet Hai and William B. Haskell, “Model and reinforcement learning for Markov games with risk preferences”, AAAI Conference on Artificial Intelligence (AAAI), 2020.  
    10. Wenjie Huang and William B. Haskell, “Stochastic approximation for risk-aware Markov decision processes”, IEEE Transactions on Automatic Control, 2020.  

Selected Publications and Preprints

  1. Wenjie Huang, Xiaobo Li, Yinuo Lin and Lei Xu, “Efficiency versus accuracy: The optimal level of decentralization in humanitarian operations for sudden-onset disasters”, Available at SSRN 5053496, 2025.
  2. Wenjie Huang, Erick Delage and Shanshan Wang, “The role of mixed discounting in risk-averse sequential decision-making”, Available at SSRN 5013140, 2025.
  3. Jian Wu, William B. Haskell, Wenjie Huang and Huifu Xu, “Preference robust optimization with quasi-concave choice functions in multi-attribute decision-making: Characterization and computation”, arXiv preprint arXiv:2008.13309v5, 2024 
  4. Junjie Lei, Wenjie Huang and Zizhuo Wang. “The impact of risk-awareness on assortment planning”, Available at SSRN 4826377, 2024.
  5. Shijie Pan and Wenjie Huang, “Online non-convex optimization with long-term non-convex constraints”, arXiv preprint arXiv:2311.02426v3, 2024.

Selected Publications

  1. Wenjie Huang, Jing Jiang and Xiao Liu. “Online non-convex learning for river pollution source identification”. IISE Transactions, Volume 55, Issue 3, DOI: https://doi.org/10.1080/24725854.2022.2068087, (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, Volume 249, 123736. DOI: https://doi.org/10.1016/j.energy.2022.123736, (2022).

  3. William B. Haskell, Huifu Xu, and Wenjie Huang. “Preference robust optimization for choice functions on the space of cumulative distribution functions (CDFs).” SIAM Journal on Optimization, Vol. 32, Iss. 2 (2022). DOI: https://doi.org/10.1137/20M1316524, (2022).

  4. Wenjie Huang and William B. Haskell. “Stochastic approximation for risk-aware Markov decision processes.” IEEE Transactions on Automatic Control, Volume 66, Issue 3. DOI: 10.1109/TAC.2020.2989702, (2020).

  5. Wenjie Huang, Pham Viet Hai and William B. Haskell. “Model and reinforcement learning for Markov games with risk preferences.” Proceedings of the AAAI Conference on Artificial Intelligence, 34(02), 2022-2029. DOI: https://doi.org/10.1609/aaai.v34i02.5574, (2020).

Research Interests

My research interests span: Data-driven decision-making, Sequential decision-making (e.g., dynamic programming, reinforcement learning), Optimization (continuous, stochastic and robust), with the applications of those theory in operations management and social good/sustainability problems. I entertain a strong interest for quantitative methodologies that can help manage the risk, uncertainty and ambiguity for engineering and service systems.

Funding

  • NSFC Young Scientist Fund Project #72201224, “Risk-aware accelerated and variance-reduced reinforcement learning with application in portfolio optimization.”, Expected Jan 2023 – Dec 2025, Principal Investigator.
  • HKU-100 Scholars – Research Start-up Funds, Expected 2021 – 2024, Principal Investigator.
  • Hong Kong RGC Theme-based Research Scheme, “SynchroHub: cyber-physical internet for synchronizing cross-border logistics hubs in the Greater Bay Area (GBA)”, Expected 2023 – 2027, Co-Principal Investigator.

Awards

Seminar

Workshop

HKU-IDS Scholar

Google Orcid Home
Dr Wenjie HUANG
Research Assistant Professor
HKU Musketeers Foundation Institute of Data Science and
Department of Data and Systems Engineering, HKU
huangwj@hku.hk
 (852) 3917 8255
HW 823-A, Haking Wong Building, HKU
Department of Data and Systems Engineering
Key expertise

Decision-making under uncertainty, Data-driven decision-making, Sequential decision-making

About me

Dr. Wenjie Huang is Research Assistant Professor in Department of Data and Systems Engineering, The University of Hong Kong. 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), Quebec, Canada. His research projects have been supported by NSFC research funds, NRF Singapore and NUS Young Investigator Award.

Selected Preprints
  1. Wenjie Huang, Xiaobo Li, Yinuo Lin and Lei Xu, “Efficiency versus accuracy: The optimal level of decentralization in humanitarian operations for sudden-onset disasters”, Available at SSRN 5053496, 2024.
  2. Wenjie Huang, Erick Delage and Shanshan Wang, “The role of mixed discounting in risk-averse sequential decision-making”, Available at SSRN 5013140, 2024.
  3. Jian Wu, William B. Haskell, Wenjie Huang and Huifu Xu, “Preference robust optimization with quasi-concave choice functions in multi-attribute decision-making: Characterization and computation”, arXiv preprint arXiv:2008.13309v5, 2024 
  4. Junjie Lei, Wenjie Huang and Zizhuo Wang. “The impact of risk-awareness on assortment planning”, Available at SSRN 4826377, 2024.
  5. Shijie Pan and Wenjie Huang, “Online non-convex optimization with long-term non-convex constraints”, arXiv preprint arXiv:2311.02426v3, 2024.
Selected Publications

  1. Wenjie Huang, Jing Jiang and Xiao Liu. “Online non-convex learning for river pollution source identification”. IISE Transactions, Volume 55, Issue 3, DOI: https://doi.org/10.1080/24725854.2022.2068087, (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, Volume 249, 123736. DOI: https://doi.org/10.1016/j.energy.2022.123736, (2022).

  3. William B. Haskell, Huifu Xu, and Wenjie Huang. “Preference robust optimization for choice functions on the space of cumulative distribution functions (CDFs).” SIAM Journal on Optimization, Vol. 32, Iss. 2 (2022). DOI: https://doi.org/10.1137/20M1316524, (2022).

  4. Wenjie Huang and William B. Haskell. “Stochastic approximation for risk-aware Markov decision processes.” IEEE Transactions on Automatic Control, Volume 66, Issue 3. DOI: 10.1109/TAC.2020.2989702, (2020).

  5. Wenjie Huang, Pham Viet Hai and William B. Haskell. “Model and reinforcement learning for Markov games with risk preferences.” Proceedings of the AAAI Conference on Artificial Intelligence, 34(02), 2022-2029. DOI: https://doi.org/10.1609/aaai.v34i02.5574, (2020).

Research Interests

My research interests span: Data-driven decision-making, Sequential decision-making (e.g., dynamic programming, reinforcement learning), Optimization (continuous, stochastic and robust), with the applications of those theory in operations management and social good/sustainability problems. I entertain a strong interest for quantitative methodologies that can help manage the risk, uncertainty and ambiguity for engineering and service systems.

Funding
  • NSFC Young Scientist Fund Project #72201224, “Risk-aware accelerated and variance-reduced reinforcement learning with application in portfolio optimization.”, Expected Jan 2023 – Dec 2025, Principal Investigator.

  • HKU-100 Scholars – Research Start-up Funds, Expected 2021 – 2024, Principal Investigator.
  • Hong Kong RGC Theme-based Research Scheme, “SynchroHub: cyber-physical internet for synchronizing cross-border logistics hubs in the Greater Bay Area (GBA)”, Expected 2023 – 2027, Co-Principal Investigator.
Seminar