about me
My name is Katherine Tsai. I am a PhD student of Electrical and Computer Engineering at University of Illinois Urbana-Champaign and am currently a visiting student at Stanford University. I am advised by Sanmi Koyejo and working closely with Mladen Kolar. My research interests lie broadly at the intersections of machine learning, signal processing, and high-dimensional statistics. My PhD research focuses on developing principled methodologies to estimate graphs from stochastic processes, and to understand the complex interactions of dynamical systems like brain networks. I like to think about the underlying statistical and optimization problems. My research is mainly supported by NSF Graduate Research Fellowship.
Previously, I completed the undergraduate degree at National Taiwan University and the master degree at University of Illinois Urbana-Champaign, both in Electrical Engineering. I spent a summer at Google Brain in 2022, working on adapting to distribution shifts using causal inference techniques.
journal publications
Latent Multimodal Functional Graphical Model Estimation
[ manuscript ] [ code ] [ arXiv ] [ poster ]
Katherine Tsai, Boxin Zhao, Sanmi Koyejo, Mladen Kolar
Journal of the American Statistical Association (JASA), 2023
A Nonconvex Framework for Structured Dynamic Covariance Recovery
[ manuscript ] [ code ] [ arXiv ] [ poster ]
Katherine Tsai, Mladen Kolar, Sanmi Koyejo
Journal of Machine Learning Research (JMLR), 2022
Joint Gaussian graphical model estimation: A survey
[ manuscript ] [ arXiv ]
Katherine Tsai, Sanmi Koyejo, Mladen Kolar
WIREs Computational Statistics, 2022
conferences and workshops
Proxy Methods for Domain Adaptation
[manuscript] [code] [ arXiv ] [ poster ]
Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou, Matt J. Kusner, Alexander D'Amour, Sanmi Koyejo, Arthur Gretton
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Adapting to Latent Subgroup Shifts via Concepts and Proxies
[ manuscript ] [ code ] [ arXiv ]
Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai (in alphabetical order)
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
On Feasible Statistics of Graph Probabilistic Generative Models
[ arXiv ]
Pablo Robles-Granda, Katherine Tsai, Sanmi Koyejo
Machine Learning on Graphs (MLoG) Workshop, 2023