Chris Lin

CS PhD Student
University of Washington

clin25 [at] cs [dot] washington [dot] edu

github | google scholar

I am a 5th-year PhD student in Computer Science at the University of Washington, where I am advised by Su-In Lee. My research interests include AI interpretability and its applications to biology. I am especially interested in the interpretability of models' internal representations.

In 2024, I spent a wonderful summer at Microsoft Research New England as a research intern, working with Alex Lu, Ava Amini, and Lorin Crawford. Before my PhD, I worked as an ML Engineer/Data Scientist developing ML models for drug discovery at GSK and AstraZeneca. I received my MS in Statistics from Stanford. I got my undergrad degrees in Statistics and Molecular & Cell Biology from UC Berkeley.

Selected Papers

Ensembling Sparse Autoencoders
Soham Gadgil*, Chris Lin*, Su-In Lee
Preprint, 2025
[paper]

An Efficient Framework for Crediting Data Contributors of Diffusion Models
Chris Lin*, Mingyu Lu*, Chanwoo Kim, Su-In Lee
ICLR, 2025
[paper] [code] [project page]

On the Robustness of Removal-Based Feature Attributions
Chris Lin*, Ian Covert*, Su-In Lee
NeurIPS, 2023
[paper]

Contrastive Corpus Attribution for Explaining Representations
Chris Lin*, Hugh Chen*, Chanwoo Kim, Su-In Lee
ICLR, 2023
[paper] [code]

Isolating salient variations of interest in single-cell data with contrastiveVI
Ethan Weinberger*, Chris Lin*, Su-In Lee
Nature Methods, 2023
[paper] [code]

Simple Causal Relationships in Gene Expression Discovered through Deep Learned Collective Variables
Ching-Hao Wang, Kalin Vetsigian, Chris Lin, Finnian Firth, Glyn Bradley, Lena Granovsky, Jeremy L. England
Preprint, 2023
[paper]

Isolating salient variations of interest in single-cell transcriptomic data with contrastiveVI
Ethan Weinberger*, Chris Lin*, Su-In Lee
ICLR MLDD Workshop, 2022
[paper]

Graph Neural Networks Including Sparse Interpretability
Chris Lin, Gerald J. Sun, Krishna C. Bulusu, Jonathan R. Dry, Marylens Hernandez
Preprint, 2020
[paper]

Effect of assisted reproductive technology on multiple sclerosis relapses: Case series and meta-analysis
Riley Bove, Kelsey Rankin, Chris Lin, Chao Zhao, Jorge Correale, Kerstin Hellwig, Laure Michel, David A. Laplaud, Tanuja Chitnis
Multiple Sclerosis Journal, 2019
[paper]

Predicting Inpatient Discharge Prioritization With Electronic Health Records
Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Ng, Nigam H. Shah
Preprint, 2018
[paper]