Research

My research interests span Risk Analytics and Robust Optimization, Sequential Decision-Making, and Data Science/AI for Operations Management (especially applications in social good/sustainability). I entertain a strong interest for quantitative methodologies that can help manage the risk, uncertainty and ambiguity for engineering and service systems.

Selected Publications and Working Papers

Risk Analytics and Robust Optimization

"Beyond homoscedastic noise: Adaptive square root principal component pursuit" (with Hao Yin), Work-in-Progress.
"Online joint pricing and capacity allocation under risk-aware retailer" (with Youxin Wang), to be submitted to European Journal of Operational Research, 2027.
"Dynamic vehicle-battery rebalancing in shared electric micromobility systems: An adaptive distributionally robust target-based approach" (with Zhuojun Liu and Lianmin Zhang), to be submitted to Transportation Research Part E: Logistics and Transportation Review, 2027.
"Joint preference estimation and robust optimization" (with Junjie Lei, Yanyu Lu, Erick Delage and Zuo-Jun Max Shen), to be submitted to International Conference on Machine Learning (ICML), 2027.
"Target-oriented bi-level optimization for recycling subsidy design" (with Yao Gao, Ling Jian and Lianmin Zhang), to be submitted to European Journal of Operational Research, 2026.
"Large-scale non-parametric preference learning via risk comparisons" (with Fei He, Kai Tu and Man-Chung Yue), under review, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2026.
"Optimal partial centralization under decentralized self-selection and processing bottlenecks" (with Xiaobo Li, Yinuo Lin and Lei Xu), under review, Manufacturing & Service Operations Management, 2026. Accepted for 2025 Durham Early Career Scholars Professional Development Workshop: Operations and Analytics, Supply Chain Management Track Accepted at 2024 INFORMS MSOM Conference
"Efficiently computing the quasi-concave envelope with incomplete information" (with Jian Wu, William B. Haskell and Huifu Xu), under 3rd round review, SIAM Journal on Optimization, 2026.
"Robust assortment optimization under nested logit model" (with Yicheng Liu and Zizhuo Wang), Operations Research Letters, 2026.
"Adjustable robust disassembly planning and dynamic capacity expansion for reverse supply chain network" (with Yao Gao and Xinbao Liu), OMEGA-International Journal of Management Science, 2026. Preprint
"Robust data-driven quasi-concave optimization" (with Jian Wu, William B. Haskell and Huifu Xu), INFORMS Journal on Computing, 2026. Preprint Code
"Assortment planning under spectral risk measures" (with Junjie Lei and Zizhuo Wang), European Journal of Operational Research, 2026. Supplemental Materials Preprint
"Preference robust optimization for choice functions on the space of CDFs" (with William B. Haskell and Huifu Xu), SIAM Journal on Optimization, 2022. Preprint
"Randomized smoothing variance reduction method for large-scale non-smooth convex optimization" (with Xun Zhang), Operations Research Forum, 2021. Supplemental Materials
"Data-driven satisficing measure and ranking", Journal of the Operational Research Society, 2019. Preprint
"Contextual and active preference robust optimization" (with Erick Delage and Zuo-Jun Max Shen), Work-in-Progress.
"Decision preservation under entropic aggregation of target-calibrated robust losses" (with Lianming Zhang), Work-in-Progress.
"A dominance principle for robust assortment optimization under the nested logit model" (with Hao Yin), Work-in-Progress.

Sequential Decision-Making

"Fast convergent risk-aware reinforcement learning" (with Junjie Lei, Dionysios Kalogerias and Zuo-Jun Max Shen), to be submitted to Journal of Machine Learning Research, 2026.
"Target-based semi-amortized dynamic programming for complex crowd evacuation" (with Shijie Pan, Xudong Wu, Qixiu Cheng and Jiayu Chen), under review, Decision Analysis, 2026.
"The role of mixed discounting in risk-averse sequential decision-making" (with Erick Delage and Shanshan Wang), R&R, Management Science, 2026.
"A unified minimax framework for online non-convex long-term constrained optimization" (with Shijie Pan and Jianyu Xu), under review, Journal of Artificial Intelligence Research, 2026. Preprint
"SAFE-AD: Socially-aware field-enhanced reinforcement learning for autonomous driving in interactive traffic" (with Zian Wang, Zejian Deng, Yiming Shu, Jiahui Xu, Yong Wang, Shen Li, Dongpu Cao, Chen Sun), under minor revision, Communications in Transportation Research, 2026.
"Shaping sparse rewards in reinforcement learning: A semi-supervised approach" (with Wenyun Li and Chen Sun), IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), 2026.
"DRL-ORA: Distributional reinforcement learning with online epistemic risk adaptation" (with Yupeng Wu, Wenyun Li and Chin Pang Ho), Conference on Uncertainty in Artificial Intelligence (UAI), 2026. acceptance rate: 30.5%
"Generalizable trajectory prediction via inverse reinforcement learning with Mamba-Graph architecture" (with Wenyun Li, Zejian Deng and Chen Sun), IEEE Intelligent Vehicles Symposium (IV), 2026. oral presentation, acceptance rate: 8.5%
"Online non-convex learning for river pollution source identification" (with Jing Jiang and Xiao Liu), IISE Transactions, 2023. Supplemental Materials Preprint
"Model and reinforcement learning for Markov games with risk preferences" (with Viet Hai Pham and William B. Haskell), AAAI Conference on Artificial Intelligence (AAAI), 2020. Supplemental Materials acceptance rate: 20.6%
"Stochastic approximation for risk-aware Markov decision processes" (with William B. Haskell), IEEE Transactions on Automatic Control, 2020. Supplemental Materials Featured publication selected by IEEE CSS-DES Newsletter
"Risk-aware Q-learning for Markov decision processes" (with William B. Haskell), IEEE Conference on Decision and Control (CDC), 2017.
"Exploiting transitivity structure in online ranking via pairwise comparisons" (with Ethan Hao Feng Lam, Alec Kirkley and Sebastian Morel-Balbi), Work-in-Progress.
"Joint risk and time preference elicitation in inverse reinforcement learning" (with Jiaming Lyu and Leon Zehao Jiang), Work-in-Progress.
"Sharp prophet inequalities for multi-unit selection with geometric discounting" (with Yicheng Liu), Work-in-Progress.

Data Science/AI for Operations Management and Social Good

"Forecast-to-control interfaces for critical spare-parts inventory management" (with Mingyuan Zhu, Ginger Y. Ke, Shan Dai, Xiaoqiang Cai and Lianmin Zhang), to be submitted to Production and Operations Management, 2026.
"Target-aware network dismantling with limited budgets" (with Jiaqi Song, Fei Jing, Xingqin Qi, Qingpeng Zhang), under review, Nature Human Behaviour, 2026.
"Data-and-structure-driven transshipment policy in heterogeneous multi-retailer system" (with Yaping Zhao, Yimo Yan, Weilei Feng, Linhui Fu, Yong-Hong Kuo and Zhen Li), under major revision, IISE Transactions, 2026.
"Dynamic order scheduling and multi-energy coordination: a greedy-serial MAPPO approach" (with Yaping Zhao, Weilei Feng, Jiarong Li, Likun Jia, Jingsi Huang), ENGINEERING Management, 2026.
"Revenue maximization leveraging positive effect of queue length" (with Zongyou Xu and Junjie Lei), IISE Annual Conference & Expo, 2026. Preprint 2nd Place, 2026 IISE Innovative Design Competition
"Data-driven inventory management for new products: An adjusted Dyna-Q approach with transfer learning" (with Xinye Qu and Longxiao Liu), IEEE International Conference on Automation Science and Engineering (CASE), 2025. Finalist, 2025 IEEE CASE Best Application Paper Award
"Towards cyber-physical internet: A systematic review, fundamental model and future perspectives" (with Hang Wu, Ming Li, Chenglin Yu, Zhiyuan Ouyang, Kee-hung Lai, Zhiheng Zhao, Shenle Pan, Shuaian Wang, Ray Y. Zhong, Yong-Hong Kuo, Fangni Zhang, Zuo-Jun Max Shen, Eric Ballot and George Q. Huang), Transportation Research Part E: Logistics and Transportation Review, 2025.
"Stochastic scheduling of high-speed railway meal service for on-time delivery" (with Lei Xu, Yaping Zhao, Siqi Ma and Rongsen Jin), Transportation Research Board (TRB) Annual Meeting, 2024.
"Profit model for electric vehicle rental service: Sensitive analysis and differential pricing strategy" (with Rui Miao, Peng Guo, Qi Li and Bo Zhang), Energy, 2022.
"Profit optimization for milage-based pricing of electric vehicle lease" (with Rui Miao, Qi Li, Peng Guo, Leiyu Mi, Zhiqi Zhang, Jie Zhang and Zhibin Jiang), IEEE Transactions on Engineering Management, 2020.
"System resilience assessment method of urban lifeline system for GIS" (with Mengzhi Ling), Computers, Environment and Urban Systems, 2018.
"Research on lease and sale of electric vehicles based on value engineering" (with Rui Miao, Donghao Pei, Xiyao Gu, Zefeng Li, Jie Zhang, Zhibin Jiang), International Journal of Production Research, 2016.

Research Grants

PI "Contextual and active preference robust optimization" Hong Kong RGC General Research Fund 17211325, 2026/01–2028/12.
PI "Online adaptive risk-aware epistemic uncertainty quantification in reinforcement learning" HKU Seed Fund for PI Research — Basic Research, 2025/06–2027/06.
PI "Risk-aware accelerated and variance-reduced reinforcement learning with application in portfolio optimization" NSFC Young Scientist Fund (C Class) 72201224, 2023/01–2025/12.
PI "HKU-100 Scholars" Research Start-up Funds 2022/01–2024/12.
Co-PI "SynchroHub: cyber-physical internet for synchronizing cross-border logistics hubs in the Greater Bay Area (GBA)" Hong Kong RGC Theme-based Research Scheme T32-707/22-N, 2022/23.
Co-I "Portfolio optimization based on partial information on risk preferences" Zhejiang Provincial NSFC Research Fund (General Program) LY23G010001, 2023/01–2025/12.
Co-I "Target based distributionally robust optimization with application to inventory routing problem" NSFC Research Fund (General Program) 72171156, 2022/01–2025/12.
Co-I "Drawdown risk valuation, hedging and related portfolio selection problems" NSFC Research Fund (General Program) 12171408, 2022/01–2025/12.
Co-I "Online learning and optimization algorithms under data-scarce and non-stationary model scenarios" NSFC Research Fund (Original Exploratory Program) 72150002, 2021/01–2023/12.
Participant "Practical considerations for large-scale competitive decision making" NUS Young Investigator Award R266000111133, 2017/03–2020/02.

Service

Ad-hoc Reviewer for:

Operations Management, Operations Research and Optimization

Operations Research; Production and Operations Management; INFORMS Journal on Computing; European Journal of Operational Research; OMEGA-International Journal of Management Science; Transportation Research Part E: Logistics and Transportation Review; International Journal of Production Research; Computational Management Science; Computer & Operations Research; Annals of Operations Research

Machine Learning and Artificial Intelligence

Journal of Machine Learning Research; Journal of Artificial Intelligence Research; International Journal of Approximate Reasoning; AAAI Conference on Artificial Intelligence; Conference on Uncertainty in Artificial Intelligence

IEEE Journals and Conferences

IEEE Transactions on Automatic Control; IEEE Transactions on Intelligent Transportation Systems; IEEE Transactions on Engineering Management; IEEE Control Systems Letters; IEEE Conference on Decision and Control; IEEE International Conference on Intelligent Transportation Systems