about me

I recently obtained PhD of Electrical and Computer Engineering from the University of Illinois Urbana-Champaign and joined Apple. I was advised by Sanmi Koyejo and a member of Stanford Trustworthy AI Research Lab. My PhD thesis focuses on estimations and predictions in dynamical systems where data are collected in non-i.i.d. fashion. Specifically, I (i) developed efficient methods to estimate graphs from continuous time-series with guarantees and (ii) used the graphs to address distribution shifts problems. You can find my thesis here. My PhD research was supported by NSF Graduate Research Fellowship.

Previously, I completed my undergraduate degree at National Taiwan University and master degree at University of Illinois Urbana-Champaign, both in Electrical Engineering. During my graduate studies, I interned at the Brain team at Google and Intel AI lab.

preprints

High-dimensional Markov-switching Ordinary Differential Processes

Katherine Tsai, Mladen Kolar, Sanmi Koyejo

2024+

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), 2024

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

Preference learning of Compound AI System

Xiangwen Wang, Yibo Jacky Zhang, Zhoujie Ding, Katherine Tsai, Sanmi Koyejo

AAAI Multi-Agent AI in the Real World Workshop (AAAI MARW), 2025 (Oral)

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

Pablo Robles-Granda, Katherine Tsai, Sanmi Koyejo

Machine Learning on Graphs (MLoG) Workshop, 2023

thesis

Graphical Models for High-dimensional Stochastic Processes: Estimation and Inference

Katherine Tsai, 2024

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