Coursework
A list of my past coursework can be found here.
Selected Projects
-
Understanding Young Stellar Cluster Formation in the Triangulum Galaxy (M33) through Point Process Models [paper]
Final project for Spatial Statistics (M1399.000300, Fall 2024) -
Application of Functional Clustering Methods to Climate Data [slides]
Personal project during undergraduate research internship at the Data Science & Machine Learning Lab. (Summer 2023)
Paper reviews
Paper & book chapter reviews from the regular seminar of the Causal Inference Lab.
- Lin, Z., Kong, D., & Wang, L. (2023). Causal inference on distribution functions.
[paper review slides] [original paper] - Miao, X., Zhao, J., & Kang, H. (2024). Transfer learning between U.S. presidential elections: How should we learn from a 2020 ad campaign to inform 2024 ad campaigns?
[paper review slides] [original paper] - Pimentel, S. D., & Huang, Y. (2024). Covariate-adaptive randomization inference in matched designs.
[paper review slides] [original paper] - Lee, Y., Buchanan, A. L., Ogburn, E. L., Friedman, S. R., Halloran, M. E., Katenka, N. V., Wu, J., & Nikolopoulos, G. K. (2023). Finding influential subjects in a network using a causal framework.
[paper review slides] [original paper] - Wainwright, M. J. (2019). High-dimensional statistics: A non-asymptotic viewpoint.
[book review slides] [original book]