About Me

Hello! I am a maching learning scientist at Abridge, where I lead the evaluation team. I am interested in using ML to improve healthcare and biomedicine.

My previous research focused on NLP and cognitive neuroscience, in particular the representations that support language and memory. I was a postdoctoral fellow at the Princeton Neuroscience Institute, where I worked with Uri Hasson, Ken Norman, and Danqi Chen. I obtained my PhD in EECS at UC Berkeley, where I was advised by Dan Klein and Jack Gallant. During my PhD, I had the opportunity to spend a wonderful summer at the Allen Institute for AI. I earned a BSE in Computer Science at Princeton with minors in Neuroscience, Statistics and Machine Learning, and Applied Math. I am deeply grateful to my collaborators and to those who have funded my research, including the CV Starr Postdoctoral Fellowship, IBM PhD Fellowship, NSF Graduate Research Fellowship, Fulbright Fellowship, and BAIR.

Outside of research I like to run, bike, and learn languages.

Selected Publications

Representations of Semantic Relations in the Human Cerebral Cortex
Catherine Chen, Lily Gong, Fatma Deniz, Daniel Klein, Jack Gallant.
bioRxiv

Bilingual Language Processing Relies on Shared Semantic Representations that are Modulated by Each Language
Catherine Chen, Lily Gong, Christine Tseng, Daniel Klein, Jack Gallant, Fatma Deniz.
PNAS 2026
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The Cortical Representation of Language Timescales is Shared between Reading and Listening
Catherine Chen, Tom Dupré la Tour, Jack Gallant, Daniel Klein, and Fatma Deniz.
Nature Communications Biology 2024
brainviewer code

Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents
Catherine Chen, Zejiang Shen, Daniel Klein, Gabriel Stanovsky, Doug Downey, Kyle Lo.
ACL Findings 2023
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Constructing Taxonomies from Pretrained Language Models
Catherine Chen,* Kevin Lin,* Daniel Klein.
NAACL 2021
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*=equal contribution