Chih-Li Sung

Chih-Li Sung

Assistant Professor, Department of Statistics and Probability

About me

Chih-Li Sung (pronounced CHI LEE SUNG) is an Assistant Professor in the Department of Statistics and Probability at Michigan State University. His research interests include computer experiment, uncertainty quantification, machine learning, and applications of statistics in engineering. His research is partially supported by National Science Foundation (NSF).

He was awarded NSF CAREER Award (2024-2029), and awarded Statistics in Physical Engineering Sciences (SPES) Award from ASA in 2019. He is currently an associate editor for Technometrics and Computational Statistics & 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 and Benjamin Haaland. 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.

News

  • đź“Ś I’m very honored and grateful to receive the NSF CAREER Award.
  • [Dec 2024] The paper “Advancing inverse scattering with surrogate modeling and Bayesian inference for functional inputs” has been accepted by SIAM/ASA Journal on Uncertainty Quantification.
  • [August 2024] I will be presenting “Functional-input Gaussian processes with applications to inverse scattering problems” (slides) in the session Advances in Statistical Learning and Uncertainty Quantification: Theory and Computation at 2024 JSM
  • [June 2024] The paper “Active learning for a recursive non-additive emulator for multi-fidelity computer experiments” has been accepted by Technometrics.
  • [May 2024] The paper “Category tree Gaussian process for computer experiments with many-category qualitative factors and application to cooling system design” has been accepted by Journal of Quality Technology.
  • [April 2024] Our lab hosted an engaging event: “🎲 Rolling the Dice: Unveiling Normal Distributions” as part of the MSU Science Festival. Our booth provided a fun and hands-on learning experience, helping learners of all ages understand the concept of normal distribution through fun and interactive games.
  • [March 2024] The paper “Stacking designs: designing multifidelity computer experiments with target predictive accuracy” is published in SIAM/ASA Journal on Uncertainty Quantification.
  • [Feb 2024] The paper “A review on computer model calibration” is published in WIREs Computational Statistics.
  • [Feb 2024] The paper “Mesh-clustered Gaussian process emulator for partial differential equation boundary value problems” has been accepted by Technometrics.

Special thanks to MSU and NSF for their support.