Irene Y. Chen
Lab Group - Bio - Resources - Reading List - Blog

I am an Assistant Professor at UC Berkeley and UCSF in Computational Precision Health and EECS as well as a faculty member of Berkeley AI Research (BAIR). I am interested in how we can make machine learning systems for healthcare to be more robust, impactful, and equitable. In particular, I develop computational tools for statistical inference with ML models, noisy data-constrained settings, and addressing algorithmic bias.

I received my PhD from MIT EECS and my joint AB/SM in Applied Math from Harvard University. Previously, I was a postdoctoral researcher at Microsoft Research New England, a data scientist at Dropbox, and an enumerator for the US Census Bureau.

Prospective PhD Students: The CHEN lab is looking for 1-2 PhD students starting Fall 2025. Apply through the Computational Precision Health or EECS (AI-H) admissions portals. Please see my advising statement and lab FAQ for more info.

Contact Info


Twitter: @irenetrampoline

Github: irenetrampoline

Google Scholar


July 2024: Our paper The Data Addition Dilemma has been accepted to MLHC 2024. See you in Toronto!

May 2024: Reflected on my first 100 days as a professor in a blog post.

April 2024: Honored to be named a Google Research Scholar for our project modeling access to care.

April 2024: Excited to receive a grant from Apple Machine Learning Research towards understanding data accumulation.

March 2024: Our paper on LLM guidlines for maternal health has been accepted to FAccT 2024 in Rio de Janeiro!

Feb 2024: Thrilled that our research with Dr. Jin Ge has received the ACG’s Leonidas H. Berry Health Equity Research Award.

Feb 2024: Our work on health disparities in treatment switching rationales using LLMs was awarded CERSI Scientific Symposium 2024 Best Poster and is available on arXiv.

Oct 2023: The lab website is now live. Learn more about the CHEN Lab, especially FAQs.

Aug 2023: I have started as an assistant professor at UC Berkeley and UCSF!

Organizing Committees

CHIL 2025 General Chair

NeurIPS 2024 Tutorial Chair

CHIL 2024 Program Chair

NeurIPS 2023 Comms Chair

Toward Algorithmic Justice in Precision Medicine 2023 Advisory Committee

FAccT 2023 Doctoral Colloquium Chair

ML4H Symposium 2022 General Chair

CHIL Tutorials Chair 2020-21

CHIL 2020 Track Chair

Fair ML for Health Workshop at NeurIPS 2019 Founder and Co-Chair

ML4H Workshop at NeurIPS Organizer (2018-2020)


Google Research Scholar 2024

Apple Machine Learning Research Grant 2024

Rising Star in AI - Harvard CRCS 2021

Rising Star in EECS - University of California Berkeley 2021

Rising Star in ML - University of Maryland 2021

Neurips Top 400 Reviewer 2019

Seth J. Teller Award for Excellence, Inclusion, and Diversity 2018

PD Soros Fellowship Finalist 2018

Derek Bok Certificate of Distinction in Teaching 2011

Selected Papers (Show all)

The Data Addition Dilemma.
Judy Hanwen Shen, Inioluwa Deborah Raji, and Irene Y Chen.
MLHC 2024.

NLP for Maternal Healthcare: Perspectives and Guiding Principles in the Age of LLMs.
Maria Antoniak, Aakanksha Naik, Carla S Alvarado, Lucy Lu Wang, Irene Y Chen.
FAccT 2024.

Machine Learning Approaches for Equitable Healthcare.
Irene Y. Chen.
PhD Thesis, Massachusetts Institute of Technology 2022.

Clustering Interval-Censored Time-Series for Disease Phenotyping.
Irene Y. Chen, Rahul G. Krishnan, David Sontag.
AAAI 2022.

Intimate Partner Violence and Injury Prediction from Radiology Reports.
Irene Y. Chen, Emily Alsentzer, Hyesun Park, Richard Thomas, Babina Gosangi, Rahul Gujrathi, Bharti Khurana.
PSB 2021.
Oral Presentation.

Ethical Machine Learning in Health Care
Irene Y. Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi.
Annual Reviews for Biomedical Data Science 2021.

Treating health disparities with artificial intelligence
Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi
Nature Medicine, January 2020

Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph.
Irene Y. Chen, Monica Agrawal, Steven Horng, David Sontag.
PSB 2020.
Oral Presentation.

Can AI Help Reduce Disparities in General Medical and Mental Health Care?
Irene Y. Chen, Peter Szolovits, Marzyeh Ghassemi.
AMA Journal of Ethics, February 2019.

Why Is My Classifier Discriminatory?
Irene Y. Chen, Fredrik D. Johansson, David Sontag.
NeurIPS 2018.
Spotlight Presentation (top 4% of submitted papers)
Presented at WiML workshop at NeurIPS 2017.