Working with CHEN Lab

Thank you for your interest in working with us! Please read my advising statement for more information about what it’s like working with Irene. Irene’s email is iychen [at] berkeley.edu

PhD applicants: 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. If you are a US citizen or permanent resident, you may be eligible for a fee waiver. Unfortunately due to volume, Irene can’t respond to all emails about PhD admissions, but each application receives our careful attention.

Admitted UC Berkeley and UCSF PhD students: If you have already been admitted and are looking for potential advisors, please email me directly.

Other PhD students (UC Berkeley, UCSF, and beyond): I’m generally very happy to collaborate – please email me!

UC Berkeley Undergraduate and Masters Students: Please send me an email with your interests, resume and your transcript. Coursework in machine learning, NLP, advanced statistics, or advanced math is strongly preferred, including CS189, CS182, CS285, CS288, CS294-158, Stat134, Data140, or CS126.

Suggested (but not required) ideas:

• Complete Part 1 of this problem set and send me a 2-3 page report about your findings
• Read this list of projects with openings and email me with relevant skills or why you’re interested.

Students outside of UC Berkeley: We currently do not have specific research openings for students outside of UC Berkeley. If you have a specific project in mind that you would like to collaborate on, please feel free to email me.

Suggested (but not required) ideas:

• Read through some of my work or other research in ML and healthcare, and send me your thoughts about what next research steps that are of interest to you might be.
• Bonus points for any analysis or preliminary models that you’ve been working on.
• More specific details are helpful. We receive a lot of very general emails (potentially LLM-generated) that make it hard to understand your research interests and relevant skillset.

Postdocs: We welcome applications from PhD holders (or soon-to-be PhD holders) in computer science, biostatistics, biomedical informatics, computational medicine, or related fields. Candidates with research experience applying machine learning to medical data are especially encouraged to apply. Competitive applicants will have a strong publication record in top machine learning, medical, biomedical informatics, or statistics venues.

Postdocs with external funding sources such as the Miller Fellowship, President’s Fellowship, BIDS Data Science Fellowship, or Chancellor’s Fellowship are encouraged to get in touch.

Other Collaborators: The lab has had several successful collaborations, including with clinicians, community health workers, insurance providers, and public policy makers. Please email Irene with a detailed description of the project, the data available, and the current challenges.