Chih-Li Sung
Assistant Professor, Department of Statistics & Probability
Location: C418 Wells Hall
Phone: 517-355-0319
Email: sungchih@msu.edu
Website: https://chihli.github.io/
CV: Download CV
Bio
Chih-Li Sung (pronounced CHI LEE SUNG) is an Assistant Professor in the [Department of Statistics and Probability](https://stt.natsci.msu.edu/) at [Michigan State University](https://msu.edu/). His research interests include **computer experiment, uncertainty quantification, machine learning, big data, and applications of statistics in engineering**. His research is supported by [NSF DMS 2113407](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2113407&HistoricalAwards=false) and [NSF DMS 2338018](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2338018). He was awarded [NSF CAREER Award](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2338018) (2024-2029), and awarded [Statistics in Physical Engineering Sciences (SPES) Award](https://www.amstat.org/your-career/awards/statistics-in-physical-engineering-sciences-award) from ASA in 2019. He is currently an associate editor for [Technometrics](https://www.tandfonline.com/toc/utch20/current) and [Computational Statistics & Data Analysis](https://www.sciencedirect.com/journal/computational-statistics-and-data-analysis) (CSDA). Chih-Li Sung received a Ph.D. at the Stewart School of Industrial & Systems Engineering at Georgia Tech in 2018. He was jointly advised by Profs. [C. F. Jeff Wu](https://www2.isye.gatech.edu/~jeffwu/) and [Benjamin Haaland](https://medicine.utah.edu/faculty/mddetail/u6012617). He also received a B.S in applied mathematics and an M.S. in statistics from National Tsing Hua University in 2008 and 2010, respectively.
Courses
- STT 442: Prob & Stat II Statistics
- STT 481: Capstone in Statistics (W)
Selected Publications
- Mak, S., Sung, C.-L., , Yeh, S.-T., Wang, X., Chang, Y.-C., Joseph, V. R., Yang, V., and Wu, C. F. J. (2018). An efficient surrogate model for emulation and physics extraction of large eddy simulations. Journal of the American Statistical Association, 113(524):1443-1456. View Publication
- Sung, C.-L. (2022). Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak. Annals of Applied Statistics, 16(4), 2505-2522. View Publication
- Sung, C.-L., Barber, B. D., and Walker, B. J. (2022) Calibration of inexact computer models with heteroscedastic errors. SIAM/ASA Journal on Uncertainty Quantification, 10(4), 1733-1752. View Publication
- Sung, C.-L., Hung, Y., Rittase, W., Zhu, C., and Wu, C. F. J. (2020). A generalized Gaussian process model for computer experiments with binary time series. Journal of the American Statistical Association, 115(530), 945-956. View Publication
- Sung, C.-L., Hung, Y., Rittase, W., Zhu, C., and Wu, C. F. J. (2020). Calibration for computer experiments with binary responses and application to cell adhesion study. Journal of the American Statistical Association, 115(532), 1664-1674. View Publication
- Sung, C.-L., Ji, Y., Mak, S., Wang, W., and Tang, T. (2024) Stacking designs: designing multifidelity computer experiments with target predictive accuracy. SIAM/ASA Journal on Uncertainty Quantification, 12(1), 157-181. View Publication
- Sung, C.-L., Wang, W., Plumlee, M., and Haaland, B. (2020). Multi-resolution functional ANOVA for large-scale, many-input computer experiments. Journal of the American Statistical Association, 115(530), 908-919. View Publication