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1. irenechen.netIrene Y. Chen - UC Berkeley and UCSF

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   Irene Chen is a computational health researcher who develops machine learning tools for healthcare applications. She works on statistical inference, noisy data, and algorithmic bias, and is interested in making ML systems more robust, impactful, and equitable.

   • About Me

     Bio: Irene Chen is an assistant professor at UC Berkeley and...

   • Talks

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

   • Resources

     Advice for aspiring and current ML researchers Enormous list...

   • Reading List

     I like to share what I’m reading to keep me motivated. For...

   • Join the Lab

     We are actively recruiting research assistants/engineers,...

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3. scholar.google.com › citations‪Irene Y. Chen‬ - ‪Google Scholar‬

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   Articles 1–20. ‪Assistant Professor, UC Berkeley and UC San Francisco‬ - ‪‪Cited by 2,815‬‬ - ‪machine learning‬ - ‪healthcare‬ - ‪equity‬ - ‪precision health‬.

4. chenlab.ioC.H.E.N. Lab

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   Led by Prof. Irene Chen, the Computational Healthcare for Equity and iNclusion (CHEN) Lab is an interdiscplinary research group in Computational Precision Health, EECS, and Berkeley AI Research.

5. www.chemistry.ucla.edu › directory › chen-ireneChen, Irene A. – UCLA - University of California, Los Angeles

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   Irene A. Chen is an associate professor in the Department of Chemical and Biomolecular Engineering at the University of California, Los Angeles. Previously, she was an assistant and then associate professor at the University of California, Santa Barbara.

6. irenechen.net › about-meBio | Irene Y. Chen - UC Berkeley and UCSF

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   Bio: Irene Chen is an assistant professor at UC Berkeley and UCSF in Computational Precision Health and EECS. She studies machine learning systems for healthcare to be more robust, impactful, and equitable.

7. scholar.google.com › citations‪Irene A. Chen‬ - ‪Google Scholar‬

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   Cited by. Year. Dissecting temporal and spatial control of cytokinesis with a myosin II Inhibitor. AF Straight, A Cheung, J Limouze, I Chen, NJ Westwood, JR Sellers, ... Science 299 (5613),...

8. People also ask

   Who is Irene Chen?

   • Irene Chen is an assistant professor at UC Berkeley and UCSF’s Computational Precision Health program with a joint appointment in UC Berkeley EECS. Her work centers on machine learning methods for improving clinical care and making it more equitable, as well as auditing and addressing bias in algorithmic models.

   Irene Chen | EECS at UC Berkeley

   www2.eecs.berkeley.edu/Faculty/Homepages/iychen.html

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   Who is IR Chen?

   • Prior to joining the Construction Industry Council, Ir CHENG was the Head of the Hong Kong-Zhuhai-Macao Bridge Hong Kong Project Management Office of the Highways Department and the Head of the New Territories East Development Office of the Civil Engineering and Development Department.

   CITAC - Management Board

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   How to contact Irene Chen lawyer?

   • Irene Chen Tel:301-760-7393中文English Scroll WELCOME Law Offices of Irene H. Chen Dedicated, Experienced and Resourceful Experienced Attorneys Licensed in Maryland + Virginia + District of Columbia Business and Personal Litigation Business Formation International Trade

   Irene Chen

   www.chenlawgroup.com/

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   How do I apply for a PhD at Chen?

   • 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.

   Irene Y. Chen - UC Berkeley and UCSF

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9. www2.eecs.berkeley.edu › Faculty › HomepagesIrene Chen | EECS at UC Berkeley

   www2.eecs.berkeley.edu › Faculty › Homepages

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   Irene Chen is an assistant professor at UC Berkeley and UCSF’s Computational Precision Health program with a joint appointment in UC Berkeley EECS. Her work centers on machine learning methods for improving clinical care and making it more equitable, as well as auditing and addressing bias in algorithmic models.