Assistant 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:
IoT, Machine Learning, Reliability Engineering, Stochastic Models, Life Data Analysis, Nondestructive Testing and Evaluation, Accelerated Life/Degradation Testing
WORKING EXPERIENCE:
Assistant Professor, Sichuan University – Pittsburgh Institute, 2021.2-Present
Data Scientist, Colgate Technology Center, NJ, 2020.2-2021.1
FUNDED RESEARCH PROJECTS:
1. 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
2. Sichuan Provincial Talent, ¥500,000, 2024.4-2026.3, PI
3. Reliability Modeling Based on Generalized Degradation Branching Stochastic Processes, National Natural Science Foundation of China, 12201441, ¥300,000，2023.1-2025.12, PI
4. 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
5. 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
6. 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, Major Participant
7. 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, Participant
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
SELECTED PUBLISHED JOURNAL ARTICLES:
1. 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, 2025, In Press.
2. 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
3. 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.
4. 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.
5. 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
6. 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
7. C. Wang and E. A. Elsayed#. Stochastic Modeling of Degradation Branching Processes. IISE Transactions, 2020, 53(3): 1-10
8. C. Wang and E. A. Elsayed#. Stochastic Modeling of Corrosion Growth. Reliability Engineering & System Safety, 2020, 204: 0-107120
9. 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.
10. 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
11. 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
12. 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.
13. 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
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. 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
2. C. Wang, Reliability Engineering in Healthcare Systems, 2024 National Industrial Engineering Annual Conference, Zhuhai, China
3. Y. Tang, X. Chen, J. Zhao, and C. Wang. “Reliability Estimation of Complex Systems Based on the Internet of Things,” presented at the 2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes. Yibin, China, September, 2023.
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. H. Zhou, Q. Liu, J. Huang, Z. Li, and C. Wang. “Reliability Estimation of Medical Equipment Based on Big Data,” presented at the 2022 8th International Symposium on System Security, Safety, and Reliability. Chongqing, China, October, 2022.
6. 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.
7. 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, and K. Li. “An Exploration for New Strategy: Degradation Modeling and Treatment Scheduling for the Degenerative Spine Based on Predictive Models,” presented at the 2022 International Conference on Sensing, Measurement & Data Analytics in the Era of Artificial Intelligence (ICSMD). IEEE, 2022: 1-6.
8. C. Wang and E. A. Elsayed, “Stochastic Modeling of Branching Degradation,” 2019 IISE Annual Conference. Orlando, Florida, May, 2019
9. 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
10. C. Wang and E. A. Elsayed, “Stochastic Modeling of Corrosion Growth,” presented at “2018 INFORMS Annual Meeting”. Phoenix, Arizona, November, 2018.
11. C. Wang and E. A. Elsayed, “Missing Degradation Data Interpolation,” presented at the workshop “Data and Decisions”. Arizona, Phoenix, November, 2018
12. 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
PROFESSIONAL AFFILIATIONS AND SERVICES:
Operations Research Society of China (ORSC), Member (2023-Present).
Institute for Operations Research and the Management Sciences (INFORMS), Member and Session Chair (2017-Present).
Institute of Industrial and Systems Engineers (IISE), Member (2018-Present).
Reviewer of the Following Journals:
IISE Transactions
IEEE Internet of Things Journal
Reliability Engineering and System Safety
IEEE Transactions on Automation Science and Engineering
Quality and Reliability Engineering International
Applied Stochastic Models in Business and Industry
Editorial Board Member:
International Journal of Applied Management 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