Associate Professor
EDUCATION:
Ph.D., Industrial and Systems Engineering, Rutgers University, 2020
M.S., Industrial and Systems Engineering, Rutgers University, 2020
M.E., Materials Processing Engineering, Harbin Institute of Technology, 2015
B.E., Materials Science Engineering Honors Class, Harbin Institute of Technology, 2013
RESEARCH INTERESTS:
Internet of Things, Intelligent Operations and Maintenance, Reliability Engineering, Stochastic Models, Medical Informatics
BIOGRAPHY：
Sichuan Province Overseas High-Level Introduced Talent, Sichuan Provincial Talent, MOE Undergraduate Education and Teaching Assessment Expert Group, Ph.D. from Rutgers University, head of the Reliability and Intelligent Risk Management Laboratory, engaged in healthcare systems reliability. PI and Co-PI of the NSFC, National Key R&D Program of China, Sichuan Provincial S&T Program, Sichuan University’s “Med + Informatics” Project, and West China Hospital’s “1.3.5 Project” AI Project, with a total funding of over 2 million RMB. Published more than 20 papers in journals such as IISE Trans and RESS. Received awards including the 2024 National IE Doctoral Student Outstanding Paper Award (as supervisor), the 2021 Best Paper Award in IISE Trans, 1st and 2nd place in the 2019/2020 IISE Data Competition, and Best Student Paper Finalist awards at the 2017/2019 INFORMS NJ / IISE.
WORKING EXPERIENCE:
Associate Professor, Sichuan University – Pittsburgh Institute, 2025.9-Present
Assistant Professor, Sichuan University – Pittsburgh Institute, 2021.2-2025.9
Data Scientist, Colgate Technology Center, NJ, 2020.2-2021.1
FUNDED RESEARCH PROJECTS:
1. Reliability Management of Intelligent Unmanned Systems for Complex Mission Scenarios, Key International (Regional) Cooperative Research Project of the National Natural Science Foundation of China, W2511076, ¥250,000, 2026.1-2030.12, Co-PI. (PI: Prof. Yan-fu Li of Department of IE at Tsinghua University)
2. Development of High-Performance 3D-Printed Polyetherketoneketone Bionic Bone Implants, National Key Research and Development Program of China, Ministry of Science and Technology of the People’s Republic of China, 2025YFC2424900, ¥200,000, 2025.11-2027.10, Co-PI
3. Sichuan Provincial Talent, ¥500,000, 2024.4-2027.3, PI
4. The Intelligent Anomaly Management and Reliability Estimation Approach of Medical Equipment Based on Internet-of-Things, “1·3·5 Project” Artificial Intelligence Project of West China Hospital, Sichuan University, ZYAI24031, ¥200,000, 2024.9-2025.8, PI
5. Reliability Modeling Based on Generalized Degradation Branching Stochastic Processes, Young Scientists Fund of the National Natural Science Foundation of China, 12201441, ¥300,000，2023.1-2025.12, PI
6. Intelligent Reliability Estimation and Operation Management of Medical Equipment Based on Big Data of Internet-of-Things, Natural Science Foundation of Sichuan, 23NSFSC3794, ¥100,000, 2023.1-2024.12, PI
7. Internet-of-Things-Big-Data-Driven Anomaly Detection and Medical Resources Allocation Model of Large-scale Medical Equipment, Med-X for Informatics, Sichuan University, YGJC006, ¥700,000, 2022.6-2023.6, PI
8. The Research and Evaluation System Construction of Common Key Technologies of Reliability of Range of Emergency Treatment Equipment, National Key Research and Development Program of China, Ministry of Science and Technology of the People’s Republic of China, 2022YFC2407601, 2022.11-2025.10, Co-PI
9. Master-Slave Somatosensory Control Nursing Robot for New Crown Medical Care Scenarios, Sichuan International Science and Technology Innovation Cooperation/Hong Kong, Macao and Taiwan Science and Technology Innovation Cooperation Project, 22GJHZ0184, 2022.1-2023.12, Co-PI
HONORS AND AWARDS:
1. Best Conference Paper Award, Tsinghua University-National Doctoral Academic Forum of Industrial Engineering (Advisor), 2024.
2. Sichuan Provincial Talent, 2024
3. Second Prize for Supervising Outstanding Undergraduate Thesis of Sichuan University, 2022
4. Sichuan Overseas High-Level Talent, 2021
5. Best Paper, IISE Transactions – Data Science, Quality and Reliability, 2021
6. 2nd Place, Data Analytics Competition, Data Analytics and Information Systems Division, Institute of Industrial and Systems Engineers, 2020
7. Winner, Data Challenge Competition, Quality Control & Reliability Engineering Division, Institute of Industrial and Systems Engineers, 2019
8. Finalist, Best Paper Competition, Quality Control & Reliability Engineering Division, Institute of Industrial and Systems Engineers, 2019
9. Finalist, Best Paper Competition, New Jersey Chapter, Institute for Operations Research and the Management Science, 2017
PROFESSIONAL AFFILIATIONS AND SERVICES:
1. Member, Undergraduate Education and Teaching Assessment Expert Panel, Ministry of Education, P.R. China, 2025
2. Invited Course Instructor, Medical AI Micro-program, West China Hospital, Sichuan University, 2025
3. Invited Instructor, Training Program on Anesthesiology Information & Intelligent Medicine, West China Hospital, Sichuan University, 2025
4. Member of Operations Research Society of China (ORSC), 2023-Present.
5. Member and Session Chair of Institute for Operations Research and the Management Sciences (INFORMS), 2017-Present.
6. Member of Institute of Industrial and Systems Engineers (IISE), 2018-Present.
SELECTED PUBLISHED JOURNAL ARTICLES:
1. J. Yang, T. Lin, H. Li, T. Wu, K. Li#, C. Wang#. Towards AI-Driven Smart Maintenance of Computed Tomography Equipment: From Health Indicator Design to Transferable Remaining Useful Life Prediction, Reliability Engineering & System Safety, 2026, In press
2. T. Wu, T. Wang, H. Li, C. Wang# and K. Li. Stochastic Modeling of Crack Branching under Uncertainties: A Degradation Branching Framework, Reliability Engineering & System Safety, 2026, In press
3. T. Wu, L. Ma, Y. Cheng, K. Zhang, K. Li, Y. Yang, H. Liu and C. Wang# Stochastic Modeling of Human Lumbar Functional Spinal Units System Degeneration. IISE Transactions, 2026, 58(2), 162–180.
4. Y. Tang, Y. Zhou, T. Wu, C. Wang#, Z. Li, K. Li. AI-driven predictive maintenance for medical imaging equipment: a deep learning framework based on the IoMT data, Reliability Engineering & System Safety, 2026, 270, 112152.
5. T. Wu, C. Ma, C. Wang#, K. Li. Stochastic Modeling of Inter-Dependent System Degradation Branching Processes: Applications to Human Cervical Spine Degeneration, IISE Transactions on Healthcare Systems Engineering, 2025: 1-14
6. H. Zhou, Z. Li, T. Wu, C. Wang# and K. Li#. Prognostic and Health Management of CT Equipment Via a Distance Self-Attention Network Using Internet of Things. IEEE Internet of Things Journal, 2024, 11(19): 31338-31354
7. H. Zhou, Q. Liu, H. Liu, Z. Chen, Z. Li, Y. Zhuo, K. Li, C. Wang#, J. Huang#. Healthcare facilities management: A novel data-driven model for predictive maintenance of computed tomography equipment. Artificial Intelligence in Medicine, 2024, 102807.
8. T. Wang, H. Liu, X. Zhou, C. Wang#. The effect of retirement on physical and mental health in China: a nonparametric fuzzy regression discontinuity study. BMC public health. 2024 Apr 27;24(1):1184.
9. C. Wang, T. Wu, T. Wang and K. Li#, Missing data interpolation and multi-sensors integration and its application in accelerated degradation data, Quality and Reliability Engineering International, 2023, 1, 1-21
10. C. Wang, Q. Liu, H. Zhou, T. Wu, H. Liu, J. Huang#, Y. Zhuo, Z. Li and K. Li#, Anomaly prediction of CT equipment based on IoMT data, BMC Medical Informatics and Decision Making, 2023, 166: 1-14
11. C. Wang and E. A. Elsayed#. Stochastic Modeling of Degradation Branching Processes. IISE Transactions, 2020, 53(3): 1-10
12. C. Wang and E. A. Elsayed#. Stochastic Modeling of Corrosion Growth. Reliability Engineering & System Safety, 2020, 204: 0-107120
13. J. Guo, C. Wang, J. Cabrera and E. A. Elsayed#. Improved inverse Gaussian process and bootstrap: Degradation and reliability metrics. Reliability Engineering & System Safety, 2018, 178, 269-277.
14. T. Wu, C. Wang# & Kang. Li#. Quantitative analysis and stochastic modeling of osteophyte formation and growth process on human vertebrae based on radiographs: a follow-up study. Scientific Reports, 2024, 14, 9393
15. T. Wang, H. Liu, X. Zhou and C. Wang#. Trends in prevalence of hypertension and high-normal blood pressure among US adults, 1999–2018, Scientific Reports, 2024, 14 (1), 25503
16. B. Liu, T. Gang#, C. Wan, C. Wang and Z. Luo. Analysis of nonlinear modulation between sound and vibrations in metallic structure and its use for damage detection. Nondestructive Testing and Evaluation, 2015, 30(3), 277-290.
17. C. Wan, T. Gang#, B. Liu and C. Wang. Characterization of the fatigue process of U71Mn steel based on non-linear ultrasonic technology. Insight-Non-Destructive Testing and Condition Monitoring, 2015, 57(7), 389-394.
REFEREED CONFERENCE PROCEEDINGS
1. Y. Tang, X. Chen, J. Zhao, Q. Liu, H. Zhou, Z. Chen, Z. Li, Y. Zhuo, K. Li, C. Wang, J. Huang. Reliability Estimation of Complex Systems Based on the Internet of Things. The 13th CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (CAA SAFEPROCESS 2023), Yibin, 2023.
2. T. Wu, Y. Tang, H. Liu, Y. Yang, K. Zhang, L. Ma, H. Jiang, X. Wu, Z. Bai, J. Wen, F. Li, Y. Xia, C. Wang, K. Li. An Exploration for New Strategy: Degradation Modeling and Treatment Scheduling for the Degenerative Spine based on Predictive Models. International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), Harbin, 2022
3. H. Zhou, T. Wu, Q. Liu, Y. Zhuo, J. Huang, Z. Li, C. Wang and K. Li. Reliability Estimation of Medical Equipment Based on Big Data, The 8th IEEE International Symposium on System Security, Safety, and Reliability (ISSSR), Chongqing, 2022
4. T. Wu, C. Wang, K. Zhang, K. Li, Y. Cheng, Reliability Estimation and Risk Assessment of the Human Spine Based on Wiener Process, The 12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), Chengdu, 2022
5. C. Wang, E. A. Elsayed, K. Li. and J. Cabrera. “Multisensor Degradation Data Fusion and Remaining Life Prediction,” ASME 2017 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, V005T10A003-V005T10A003, Hawaii, 2017.
PRESENTATIONS
1. C. Wang, Time-Series Data-Driven Decision-Making in Healthcare Systems, The Greater Bay Area Artificial Intelligence and Data Science Application Summit & the 18th China‑R Conference, Guangzhou, Guangdong, China, July, 2025 (invited talk)
2. T. Wu, K. Li and C. Wang, Reliability Modeling of Human Lumbar Spine Degeneration, 2024 National Industrial Engineering Doctoral Academic Forum, Department of Industrial Engineering, Tsinghua University, Beijing, China, December, 2024
3. C. Wang, Reliability Engineering in Healthcare Systems, 2024 National Industrial Engineering Annual Conference, Zhuhai, China
4. C. Wang. “Stochastic Modeling of Degradation Branching Processes,” presented at the 2023 16th Operations Research Society of China Annual Conference. Changsha, Hunan, 2023.
5. C. Wang, H. Zhou, T. Wu, J. Huang, K. Li, Z. Li, and Q. Liu. “Anomaly Detection of CT Equipment Based on IoT Data,” presented at the 2022 International Conference for Chinese Scholars in Industrial Engineering. Chengdu, China, April, 2022.
6. C. Wang and E. A. Elsayed, “Stochastic Modeling of Branching Degradation,” 2019 IISE Annual Conference. Orlando, Florida, May, 2019
7. S. Guo, C. Wang, “Paper Break Prediction Based on Classification in Multivariate Time Series,” presented at the 2019 IISE Annual Conference. Orlando, Florida, May, 2019
8. C. Wang and E. A. Elsayed, “Stochastic Modeling of Corrosion Growth,” presented at “2018 INFORMS Annual Meeting”. Phoenix, Arizona, November, 2018.
9. C. Wang and E. A. Elsayed, “Missing Degradation Data Interpolation,” presented at the workshop “Data and Decisions”. Arizona, Phoenix, November, 2018
10. C. Wang and E. A. Elsayed, “Gamma Process Based Corrosion Volume Loss Stochastic Modeling and Reliability Analysis,” presented at 2017 INFORMS New Jersey Chapter Student Contest. Piscataway, New Jersey, October, 2017.
ACADEMIC CONFERENCE POSTER:
1. C. Wang and E. A. Elsayed, “Stochastic Modeling of Branching Degradation,” 2019 IISE Annual Conference QCRE Best Paper Competition. Orlando, Florida, May, 2019
2. C. Wang and E. A. Elsayed, Stochastic Modeling of Corrosion Growth, 2018 INFORMS Annual Meeting”. Phoenix, Arizona, November, 2018
PATENTS:
1. A Fault Prediction Method and System Based on Industrial Internet of Things Data, ZL202211619820.X, Granted
2. An Anomaly Prediction Method for CT Equipment Based on IoMT Data, 202211619820X, Pending Authorization
3. An Anomaly Prediction Method and System of MRI Equipment Based on IoT Data，2023101030183, Pending Authorization
REVIEWER OF THE FOLLOWING JOURNALS:
IISE Transactions
IISE Transactions on Healthcare Systems Engineering
Reliability Engineering and System Safety
IEEE Internet of Things Journal
IEEE Transactions on Reliability
IEEE Transactions on Automation Science and Engineering
Quality and Reliability Engineering International
INFORMS Journal on Data Science
COURSES TAUGHT:
IE1082: Probabilistic Methods in Operations Research
IE1040: Engineering Economic Analysis
IE1083: Simulation Modeling
Technical Elective: Data Analytics in IE
Technical Elective: Reliability Engineering
Technical Elective: Data Mining