Yun Liu
Yun is a senior staff research scientist in Google Research. In this role he focuses on developing and validating machine learning for medical applications across multiple fields: pathology, ophthalmology, radiology, dermatology, and more. Yun completed his PhD at Harvard-MIT Health Sciences and Technology, where he worked on predictive risk modeling using biomedical signals, medical text, and billing codes. He has previously also worked on predictive modeling for nucleic acid sequences and protein structures. Yun completed a B.S. in Molecular and Cellular Biology and Computer Science at Johns Hopkins University.
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Google
Unprecedented Insights into Maternal Sleep: A Large-scale Longitudinal Analysis of Real-world Wearable Device Data Before, During, and After Pregnancy
Nichole Young-Lin
Conor Heneghan
Logan Schneider
Logan Niehaus
Ariel Haney
Karla Gleichauf
Jacqueline Shreibati
Belen Lafon
Lancet eBioMedicine (2025)
Performance of a Deep Learning Diabetic Retinopathy Algorithm in India
Arthur Brant
Xiang Yin
Lu Yang
Jay Nayar
Divleen Jeji
Sunny Virmani
Anchintha Meenu
Naresh Babu Kannan
Florence Thng
Lily Peng
Ramasamy Kim
JAMA Network Open (2025)
Passive Heart Rate Monitoring During Smartphone Use in Everyday Life
Shun Liao
Paolo Di Achille
Jiang Wu
Jonathan Wang
Eric Teasley
Lawrence Cai
Daniel McDuff
Hao-Wei Su
Brent Winslow
Anupam Pathak
Shwetak Patel
Jim Taylor
Jamie Rogers
(2025)
Validation of a Deep Learning Model for Diabetic Retinopathy on Patients with Young-Onset Diabetes
Tony Tan-Torres
Pradeep Praveen
Divleen Jeji
Arthur Brant
Xiang Yin
Lu Yang
Tayyeba Ali
Ilana Traynis
Dushyantsinh Jadeja
Rajroshan Sawhney
Sunny Virmani
Pradeep Venkatesh
Nikhil Tandon
Ophthalmology and Therapy (2025)
Oculomics: Current Concepts and Evidence
Zhuoting Zhu
Yueye Wang
Ziyi Qi
Wenyi Hu
Xiayin Zhang
Siegfried Wagner
Yujie Wang
An Ran Ran
Joshua Ong
Ethan Waisberg
Mouayad Masalkhi
Alex Suh
Yih Chung Tham
Carol Y. Cheung
Xiaohong Yang
Honghua Yu
Zongyuan Ge
Wei Wang
Bin Sheng
Andrew G. Lee
Alastair Denniston
Peter van Wijngaarden
Pearse Keane
Ching-Yu Cheng
Mingguang He
Tien Yin Wong
Progress in Retinal and Eye Research (2025)
An intentional approach to managing bias in embedding models
Atilla P. Kiraly
Jungyeon Park
Rory Pilgrim
Charles Lau
Heather Cole-Lewis
Shravya Shetty
Krish Eswaran
Leo Anthony Celi
The Lancet Digital Health, 6 (2024), E126-E130
Searching for Dermatology Information Online using Images vs Text: a Randomized Study
Jay Hartford
Natalie Salaets
Kimberley Raiford
Jay Nayar
Dounia Berrada
Harsh Kharbanda
Lou Wang
Peggy Bui
medRxiv (2024)
General Geospatial Inference with a Population Dynamics Foundation Model
Chaitanya Kamath
Prithul Sarker
Joydeep Paul
Yael Mayer
Sheila de Guia
Jamie McPike
Adam Boulanger
David Schottlander
Yao Xiao
Manjit Chakravarthy Manukonda
Monica Bharel
Von Nguyen
Luke Barrington
Niv Efron
Krish Eswaran
Shravya Shetty
(2024) (to appear)
Towards Generalist Biomedical AI
Danny Driess
Andrew Carroll
Chuck Lau
Ryutaro Tanno
Ira Ktena
Basil Mustafa
Aakanksha Chowdhery
Simon Kornblith
Philip Mansfield
Sushant Prakash
Renee Wong
Sunny Virmani
Sara Mahdavi
Bradley Green
Ewa Dominowska
Joelle Barral
Karan Singhal
Pete Florence
NEJM AI (2024)
Conversational AI in health: Design considerations from a Wizard-of-Oz dermatology case study with users, clinicians and a medical LLM
Brenna Li
Amy Wang
Patricia Strachan
Julie Anne Seguin
Sami Lachgar
Karyn Schroeder
Renee Wong
Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, pp. 10
