Zhiling Gu
Zhiling Gu is a Ph.D. candidate in Statistics at Iowa State University (ISU), supervised by Professor Lily Wang and Professor Dan Nettleton.
Her research interests include 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
[7] Gu, Z., Yu, S., Wang, G., Wang, L. TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-based Imaging. (In preparation). [Runner-up, SMI2023 Student Paper Competition]
[6] Gu, Z., Li, X., Wang, G., Wang, L. Structure Identification of Space-time Epidemic Models. (In preparation).
[5] 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 [link]
[4] 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 [link]
[3] 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 [link]
[2] 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 [link]
[1] 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 [link]
Teaching
Courses Taught @Iowa State University
STAT 305: Engineering Statistics, Summer 2021
STAT 226: Introduction to Business Statistics I, Fall 2021, Fall 2020
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
[6] “TSSS: A novel triangulated spherical spline smoothing for data distributed on complex surfaces”. EcoSta 2023, Waseda University, Japan - Aug 2023 (upcoming)
[5] “TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-based Imaging”. ICSA 2023 Applied Statistics Symposium, University of Michigan - June 2023 (upcoming)
[4] “TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-based Imaging”. SMI 2023, University of Minnesota - May 2023
[3] “Structure Identification for Space-time Epidemic Models”. CMStatistics 2022, King’s College London - Dec 2022
[2] “Structure Identification for Space-time Epidemic Models”. The 35th New England Statistics Symposium, University of Connecticut - May 2022
[1] “Discussion of ‘Adaptive Conformal Inference under Distribution Shift’ by Isaac Gibbs and Emmanuel J. Candès”. TrAC Journal Club, Iowa State University - April 2022