Hanxiao Zhang
Dr. Hanxiao Zhang is a Tenure-Track Assistant Professor and Master Supervisor in the Department of Management Science and Logistics, School of Management, Beijing Institute of Technology.
Her research interests include reliability and risk management, operations and maintenance service management, maintenance scheduling optimization, and stochastic optimization. Her research has been published in leading international journals, including the European Journal of Operational Research, IISE Transactions, and Reliability Engineering & System Safety.
She is the Principal Investigator of a Young Scientists Fund project supported by the National Natural Science Foundation of China (NSFC). She serves as a committee member of the Systems Reliability Committee of the Systems Engineering Society of China and as a Young Editorial Board Member of Quality and Reliability.
Prospective students with backgrounds in mathematics, industrial engineering, and related disciplines are welcome to apply for graduate study through either the recommended-admission track or the national graduate entrance examination.
Email: zhanghxiao@outlook.com
Education
2017–2022, Ph.D, Department of Industrial Engineering, Tsinghua University
2013–2017, B.S., School of Mathematics and Statistics, Wuhan University
Professional Experience
2026–Present, Tenure-Track Assistant Professor, School of Management, Beijing Institute of Technology
2023–2026, Lecturer, Department of Industrial Engineering, Beijing Jiaotong University
2022–2023, Postdoctoral Fellow, City University of Hong Kong
[1] Zhang, H., Zhang, C., Wang, Y., & Li, Y. F.* (2026). Service Reliability of Intelligent Computing Cluster Systems for Large Language Models. Reliability Engineering & System Safety, 272, 112484.
[2] Zhang, H., Liu, X.*, Yang, L., & Qian, Y. (2026). Approximate approaches for reliability evaluation and redundancy allocation for large-scale multi-state series–parallel systems. Reliability Engineering & System Safety, 271, 112234.
[3] Zhang, H., Wang, Z.*, Liu, X., Gaudoin, O., & Xie, M. (2025). Joint optimization of condition-based production and maintenance with mutual production-deterioration dependencies. Reliability Engineering & System Safety, 256, 110679.
[4] Wang, Z., Yang, L., Fang, X., Zhang, H.*, & Xie, M. (2025). Image-based remaining useful life prediction through adaptation from simulation to experimental domain. Reliability Engineering & System Safety, 255, 110668.
[5] Zhang, H., Li, Y. F.*, Xie, M., & Zhang, C. (2024). Two-stage distributionally robust optimization for joint system design and maintenance scheduling in high-consequence systems. IISE Transactions, 56(8), 793-810.
[6] Liu, X., Lee, C. K., Zhang, H.*, Chen, P., Huang, J., & Wong, C. N. (2024). Fault diagnosis based on incomplete sensor variables with a hierarchical semi-supervised Gaussian mixture classifier. Applied Mathematical Modelling, 138, 115764.
[7] Zhang, H., & Li, Y. F.* (2022). Integrated optimization of test case selection and sequencing for reliability testing of the mainboard of Internet backbone routers. European Journal of Operational Research, 299(1), 183-194.
[8] Zhang, H., & Li, Y. F.* (2022). Robust optimization on redundancy allocation problems in multi-state and continuous-state series–parallel systems. Reliability Engineering & System Safety, 218, 108134.
[9] Zhang, H., Sun, M., & Li, Y. F.* (2022). Reliability–redundancy allocation problem in multi-state flow network: minimal cut-based approximation scheme. Reliability Engineering & System Safety, 225, 108564.
[10] Wang, Y., Jiang, Z., Li, Q., Ma, J., Song, S., Zhang, H., & Wang, X. V. (2026). Digital workshop health status evaluation method based on DTVSM. Journal of Manufacturing Systems, 88, 108-125.
[11] Shan, A., Jiang, Z.*, Li, Q., Zhang, H., & Blesa, J. (2026). A novel flexible interval maintenance strategy for multi-unit heterogeneous degrading systems under uncertainty. Reliability Engineering & System Safety, 271, 112227.
[12] Zhang, C., Li, Y. F.*, Zhang, H., Wang, Y., Huang, Y., & Xu, J. (2024). Distributionally robust resilience optimization of post-disaster power system considering multiple uncertainties. Reliability Engineering & System Safety, 251, 110367.
[13] Zheng, W., Zhang, H., & Li, Y. F.* (2023). A systematic approach to the high-level maintenance scheduling for high-speed trains in China. IEEE Transactions on Reliability, 73(1), 142-155.
[14] Li, Y. F.*, & Zhang, H. (2022). The methods for exactly solving redundancy allocation optimization for multi-state series-parallel systems. Reliability Engineering & System Safety, 221, 108340.
1. Young Scientists Fund, National Natural Science Foundation of China (NSFC), 2025–2027, PI.
Redundancy Design and Operations & Maintenance Service Optimization for Flexible Manufacturing Systems under Stochastic Dynamic Environments.
2. Natural Science Talent Fund, Beijing Jiaotong University, 2024–2027, PI.
Reliability and Redundancy Strategies for Multi-State Systems.
3. National Key Research and Development Program of China, 2024–2027, Participant.
Development and Application Demonstration of an Integrated Strategic Management and Control System for Enterprise Groups in Discrete Manufacturing Industries.
4. General Program, National Natural Science Foundation of China (NSFC), 2024–2027, Participant.
Robust Reliability Design and Operations & Maintenance Decision Optimization for Multi-Component Systems under Mixed Uncertainties.
[1] Best Applications Paper Award, IISE Transactions, 2026
[2] Outstanding Doctoral Dissertation, Systems Engineering Society of China, 2024
[3] National Second Prize, First “Kede Cup” China Machinery Industry–Education Integration Education and Teaching Innovation Competition, Chinese Mechanical Engineering Society, 2024
[4] First Prize, Undergraduate Teaching Achievement Award, Beijing Jiaotong University, 2024
[5] First Prize, Comprehensive Excellence Scholarshi, Tsinghua University, 2021
[6] Outstanding Undergraduate Thesis, Beijing Jiaotong Universit (Supervisor), 2026
[7] Grand Prize, 19th Tsinghua IE “Liangjian” National Industrial Engineering Application Case Competition (Faculty Advisor), 2024
