Zhiling Gu
Zhiling Gu is a Ph.D. candidate in Statistics at Iowa State University (ISU), advised by Professor Lily Wang and Professor Dan Nettleton.
Her research interests include non-/semi-parametric regression methods, spatiotemporal data analysis, statistical machine learning, and high dimensional data analysis.
Google scholar: RWgzgCsAAAAJ
ORCID: 0000-0002-8052-7608
GitHub: https://github.com/guzhiling
Email: zlgu [at] iastate [dot] edu
Selected Works
Gu, Z. and Wang, L. (In preparation). Statistical Learning and Inference of Surface-based Functional Data with Applications in Neuroimaging Analysis.
Gu, Z., Yu, S., Wang, G., Lai, M., Wang, L. TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-based Imaging. (Revision Invited). [An earlier version won runner-up of SMI2023 Student Paper Competition, theory track]
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]
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]
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 & Activities
Contributed discussion of “Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis”, ISU Causal Inference Working Group - November 2023
Contributed poster, ISU Statistics 75th Anniversary Research Conference - Sept 2023
Participant, “Invitation to Algebraic Statistics and Applications”. Institute for Mathematical and Statistical Innovation, Chicago - Sept 2023
Invited talk, EcoSta 2023, Waseda University, Japan - Aug 2023
Invited talk, ICSA 2023 Applied Statistics Symposium, University of Michigan - June 2023
Contributed discussion of “Parameterizing and Simulating from Causal Models”. ISU Causal Inference Working Group - May 2023
Invited talk, SMI 2023, University of Minnesota - May 2023
Invited talk, CMStatistics 2022, King’s College London - Dec 2022
Contributed poster, The 35th New England Statistics Symposium, University of Connecticut - May 2022
Contributed discussion of “Adaptive Conformal Inference under Distribution Shift” by Isaac Gibbs and Emmanuel J. Candès. TrAC Journal Club, Iowa State University - April 2022