Zhiling Gu
I am a 4th year Ph.D. student in Statistics at Iowa State University (ISU), where I am supervised by Professor Lily Wang and Professor Dan Nettleton. Before joining ISU, I completed M.Phil. in Risk Management Science advised by Professor Hoi-Ying Wong at The Chinese University of Hong Kong.
I am interested in non-/semi-parametric regression methods, epidemic modeling, spatial/spatiotemporal data analysis, and high dimensional data analysis.
[GoogleScholar] [GitHub] [ISU]
Email: zlgu [at] iastate [dot] edu
Papers/Preprints
Cramer, E. Y., Ray, E. L., Lopez, V. K., Bracher, J., Brennen, A., Castro Rivadeneira, A. J., ..., Gu, Z., & Georgescu, A. (2022). Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States. Proceedings of the National Academy of Sciences, 119(15), e2113561119.
Kim, M., Gu, Z., Yu, S., Wang, G., & Wang, L. (2021). Methods, Challenges, and Practical Issues of COVID-19 Projection: A Data Science Perspective. Journal of Data Science, 19(2), 219-242. doi: [10.6339/21-JDS1013]
Wang, G., Gu, Z., Li, X., Yu, S., Kim, M., Wang, Y., Gao, L., Wang, L. (2021). Comparing and integrating US COVID-19 data from multiple sources with anomaly detection and repairing. Journal of Applied Statistics.doi: [10.1080/02664763.2021.1928016]
Wang, L., Wang, G., Li, X., Yu, S., Kim, M., Wang, Y., Gu, Z., Gao, L. (2021). Modeling and forecasting COVID-19. AMS: Notices Of The American Mathematical Society, 68, 585-595. [PDF]
Wang, L., Wang, G., Gao, L., Li, X., Yu, S. Kim, M., Wang, Y. , Gu, Z. (2020). Spatiotemporal dynamics, nowcasting and forecasting of COVID-19 in the United States. arXiv:[2004.14103]
Teaching
Courses Taught @Iowa State University
STAT 226: Introduction to Business Statistics I, Fall 2021, Fall 2020
STAT 305: Engineering Statistics, Summer 2021
Courses TA’ed @Iowa State University
STAT 486/586: Introduction to Statistical Computing, Spring 2021
STAT 507X: Statistical Learning of Infectious Disease Analytics, Spring 2021
STAT 101: Principles of Statistics, Spring 2020
STAT 226: Introduction to Business Statistics I, Spring 2020
STAT 231: Probability and Statistical inference for engineers, Fall 2019
Presentations
"Structure Identification for Space-time Epidemic Models", King's College London. Dec, 2022. The 15th International Conference of the ERCIM WG on Computational and Methodological Statistics, King's College London.
"Structure Identification for Space-time Epidemic Models". May, 2022. The 35th New England Statistics Symposium, University of Connecticut.
Discussion of the paper "Adaptive Conformal Inference under Distribution Shift" by Isaac Gibbs and Emmanuel J. Candès, April, 2022. @TrAC Journal Club, Iowa State Univeristy. [PDF]