Feifan Wang is an Assistant Professor in the Department of Industrial Engineering at Tsinghua University. He obtained his Ph.D. from Arizona State University. Prior to joining Tsinghua University, he was an Assistant Professor / Analyst with Mayo Clinic. His research focuses on modeling, analysis, optimization, and control of complex systems, with applications in healthcare systems and production systems. His research has been recognized with the Best Paper Award from IISE Transactions and Best Student Paper Award from IEEE International Conference on Automation Science and Engineering (CASE). He has twice been a finalist for the Best Paper Award on Healthcare Automation from IEEE CASE. His Ph.D. dissertation was honored with the Dean's Dissertation Award from Arizona State University.

August 2023 – Present, Assistant Professor, Department of Industrial Engineering, Tsinghua University

March 2021 – June 2023, Assistant Professor / Analyst, Mayo Clinic

Ph.D., May 2021, Industrial Engineering, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, USA.

M.S., March 2016, Industrial Engineering, Department of Industrial and Systems Engineering, Zhejiang University, China.

B.S., June 2013, Industrial Engineering, Department of Industrial Engineering, Zhejiang University of Technology, China.

Best Paper Award on Healthcare Automation Finalist, IEEE International Conference on Automation Science and Engineering (CASE), 2023

Best Paper Award on Healthcare Automation Finalist, IEEE International Conference on Automation Science and Engineering (CASE), 2021

Design and Manufacturing Best Paper Award, IISE Transactions, 2021

Dean's Dissertation Award, Arizona State University, 2020

Best Student Paper Award, IEEE International Conference on Automation Science and Engineering (CASE), 2019

Featured Article in IISE Transactions, ISE Magazine, 2019

Healthcare systems, production systems

Graduate Courses

Advanced Operations Research II: Stochastic Processes

Undergraduate Courses

Production Planning and Control

Seminar on Science, Technology and Humanities

Wang, F., Su, Y., Ju, F.*, Krishnan, B., Dauod, H., & Patel, N. (2024). Fast Schedule Recovery Method for Semiconductor Packaging Lines With Machine Failures and Constrained Time Windows. IEEE Transactions on Automation Science and Engineering.

Wang, F., Huang, Y.*, & Ju, F. (2023). Simulation Optimization Gantry Call-back Control Method for Proton Therapy Systems. IEEE Transactions on Automation Science and Engineering, 20(3), 1565-1576.

Wang, F., Huang, Y. L.*, Ju, F., & Grega, J. C. (2022). Resident Rotation Scheduling for Categorical Internal Medicine Residency Program. IEEE Robotics and Automation Letters, 7(2), 4142-4148.

Fathizadan, S., Ju, F.*, Wang, F., Rowe, K., & Hofmann, N. (2022). Dynamic Material Deposition Control for Large-Scale Additive Manufacturing. IISE Transactions, 54(9), 817-831.

Wang, F., & Ju, F.* (2021). Decomposition-based Real-time Control of Multi-stage Transfer Lines with Residence Time Constraints. IISE Transactions, 53(9), 943-959.

Wang, F., Fathizadan, S., Ju, F.*, Rowe, K., & Hofmann, N. (2020). Print Surface Thermal Modeling and Real-Time Layer Time Control for Large-Scale Additive Manufacturing. IEEE Transactions on Automation Science and Engineering, 18(1), 244-254.

Wang, F., & Ju, F.* (2020). Transient and Steady-state Analysis of Multi-stage Production Lines with Residence Time Limits. IEEE Transactions on Automation Science and Engineering, 18(1), 122-134.

Wang, F., Ju, F.*, & Kang, N. (2019). Transient Analysis and Real-time Control of Geometric Serial Lines with Residence Time Constraints. IISE Transactions, 51(7), 709-728. (Design and Manufacturing Best Paper Award, Featured Article in ISE Magazine)

Li, M., He, Y., Guo, L., & Wang, F.* (2024, August). Real-time Service Capacity Allocation with Advance Arrival Information and Instantaneous Services. In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE) (pp. 684-689). IEEE.

Wang, F.*, Jones, D., Walker, L., Borah, B., & Salehinejad, H. (2023, August). Partially Observable Markov Decision Process Model for Dynamic Human Activity Recognition using Radio Frequency Signals. In 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) (pp. 1-6). IEEE.

Wang, F.*, Huang, Y., Graff, S., & Peterson, J. (2023, August). Technician Scheduling and Staffing for Medical Procedures in Heart Rhythm Services. In 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) (pp. 1-6). IEEE. (Best Paper Award on Healthcare Automation Finalist)

Wang, F., & Huang, Y. L.* (2022, August). Impacts of Proton Accelerator Upgrade on System Level Performance of Proton Therapy Systems. In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (pp. 799-804). IEEE.

Wang, F., & Ju, F.* (2022, August). Simulation-based Real-time Production Control with Different Classes of Residence Time Constraints. In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (pp. 1860-1865). IEEE.

Wang, F., Huang, Y. L., & Ju, F.* (2021, August). Rollout-based Gantry Call-back Control for Proton Therapy Systems. In 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) (pp. 962-967). IEEE. (Best Paper Award on Healthcare Automation Finalist)

Wang, F., Ju, F.*, Rowe, K., & Hofmann, N. (2019, August). Real-time Control for Large Scale Additive Manufacturing Using Thermal Images. In 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) (pp. 36-41). IEEE. (Best Student Paper Award)

Wang, F., Lu, Y., & Ju, F.* (2018, August). Condition-based Real-time Production Control for Smart Manufacturing Systems. In 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) (pp. 1052-1057). IEEE.

Wang, F., Ju, F.*, & Lu, Y. (2017, August). A Study on Performance Evaluation and Status-based Decision for Cyber-physical Production Systems. In 2017 13th IEEE International Conference on Automation Science and Engineering (CASE) (pp. 1000-1005). IEEE.