Dr. WANG Chen, Associate Professor, Department of Industrial Engineering, Tsinghua University. She obtained the bachelor's degree of Industrial Engineering from Beihang University, and the master's degrees of Statistics and Industrial and Systems Engineering and the doctoral degree of Industrial and Systems Engineering from University of Wisconsin-Madison. The research at Wang's group focuses on data-driven decision and risk analysis, and is dedicated to provide smart decision solutions to cope with technical and societal challenges involving risk, uncertainty and trade-offs. Wang’s research group welcomes students who are interested in decision modeling (including utility, probability judgment, optimization, stochastic process, game theory), statistical and machine learning, and human-AI collaborative decision-making.
Honors and AwardsTeaching:
Tsinghua University Benchmark Course, Applied Statistics and Data Analytics, 2020
National First-Class Undergraduate Course, Applied Statistics and Data Analytics, 2020
Tsinghua University Excellent Undergraduate Course, 2019
Tsinghua University Teaching Achievement Award, First Prize, 2019.
Tsinghua University Annual Teaching Excellence Award, 2017, 2019
IISE Transactions Design and Manufacturing Best Paper Honorable Mention, 2018
INFORMS Decision Analysis Society Best Student Paper Award, 2013
Educational BackgroundPh.D., Industrial and Systems Engineering, 2013, University of Wisconsin-Madison
M.S., Statistics, 2011, University of Wisconsin-Madison
M.S., Industrial and Systems Engineering, 2009, University of Wisconsin-Madison
B.Engr., Industrial Engineering, 2007, Beihang University
Employment HistoryJan. 2019 – present, Associate Professor, Department of Industrial Engineering, Tsinghua University
Sept. 2013 – Jan. 2019, Assistant Professor, Department of Industrial Engineering, Tsinghua University
CoursesApplied Statistics and Data Analytics
Systems Design and Management
Service Operations Management
Engineering and Technology Management
Word Organization and Human Resources Management
Systems Engineering – Technical Processes
Quantitative Analysis Methods – Decision Analysis
Research InterestsDecision Analysis; Risk Analysis; Data-driven Operations Management
Ongoing research fields: natural disaster risk perception, multivariate risk prediction and assessment, game-theoretic modeling of risk decisions, data-driven modeling of decision processes, etc.
Research ProjectsExpert Elicitation of Extreme Risks，2015.01-2017.12，National Science Foundation of China Young Investigator Grant Program, PI.
Wang, S., C. Wang*, Quantile judgments of lognormal losses: An experimental investigation, Decision Analysis 18(1) 78-99, 2021.
Song, S., C. Wang*, Incentivizing catastrophe risk sharing, IISE Transactions 52(12) 1358-1385, 2020.
Taheri, E., C. Wang*, Eliciting public risk preferences in emergency situations, Decision Analysis 15(4) 223-241, 2018.
Feng, W., C. Wang, M. Shen*, Process flexibility design in heterogeneous and unbalanced networks: A stochastic programming approach, IISE Transactions 49(4) 1-19, 2017.
Wang, C.*, V. M. Bier, Quantifying adversary capabilities to inform defensive resource allocation, Risk Analysis 36(4) 756-775, 2015.
Wang, C., V. M. Bier, Using preference orderings to make quantitative trade-offs. L. A. Cox, Jr. (Ed.) Breakthroughs in Decision Science and Risk Analysis, Wiley, 2014.
Wang, C.*, V. M. Bier, Expert elicitation of adversary preferences using ordinal judgments. Operations Research 61(2) 372-385, 2013.
Bier, V. M., J. Menoyo, C. Wang, Achieving realistic levels of defensive hedging based on non-monotonic and multi-attribute terrorist utility functions. J. W. Hermann (Ed.) Handbook of Operations Research for Homeland Security, Springer, 2012.
Wang, C., V. M. Bier*, Target-hardening decisions based on uncertain multiattribute terrorist utility. Decision Analysis 8(4) 286-302, 2011.