Vivek Natarajan
Vivek Natarajan is a Research Scientist at Google DeepMind leading research at the intersection of AI, science and medicine.
In particular, Vivek was the lead researcher behind Med-PaLM and Med-PaLM 2, which were the first AI systems to obtain passing and expert level scores on US Medical License exam questions respectively. Med-PaLM was published in Nature in 2023 and has been featured in The Scientific American, Wall Street Journal, The Economist, STAT News, CNBC, Forbes, New Scientist among others.
Vivek co-leads Project AMIE with Dr Alan Karthikesalingam at Google, a research effort aiming to build and democratize conversational, multimodal, diagnostic and empathetic medical super intelligence. Two papers from Project AMIE were recently published in Nature with the AI system surpassing primary care physicians in performing medical consultations in simulated settings.
Finally, Vivek recently co-led the development of the AI co-scientist, a system designed to be a virtual AI collaborator for scientists.
Outside of Google, Vivek is also part of the faculty for executive education at Harvard T.H. Chan School of Public Health in a part-time capacity.
Authored Publications
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Google
Towards Conversational AI for Disease Management
Khaled Saab
David Stutz
Kavita Kulkarni
Sara Mahdavi
Joelle Barral
James Manyika
Ryutaro Tanno
Adam Rodman
arXiv (2025)
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)
Towards Conversational Diagnostic AI
Khaled Saab
Jan Freyberg
Ryutaro Tanno
Amy Wang
Brenna Li
Nenad Tomašev
Karan Singhal
Le Hou
Albert Webson
Kavita Kulkarni
Sara Mahdavi
Juro Gottweis
Joelle Barral
Kat Chou
Arxiv (2024) (to appear)
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
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
Enhancing diagnostic accuracy of medical AI systems via selective deferral to clinicians
Dj Dvijotham
Jim Winkens
Melih Barsbey
Sumedh Ghaisas
Robert Stanforth
Nick Pawlowski
Patricia Strachan
Zahra Ahmed
Yoram Bachrach
Laura Culp
Mayank Daswani
Jan Freyberg
Christopher Kelly
Atilla Kiraly
Timo Kohlberger
Scott Mayer McKinney
Basil Mustafa
Krzysztof Geras
Jan Witowski
Zhi Zhen Qin
Jacob Creswell
Shravya Shetty
Terry Spitz
Taylan Cemgil
Nature Medicine (2023)
Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation
Ryutaro Tanno
David Barrett
Sumedh Ghaisas
Sumanth Dathathri
Abi See
Johannes Welbl
Karan Singhal
Rhys May
Roy Lee
SiWai Man
Zahra Ahmed
Sara Mahdavi
Joelle Barral
Ali Eslami
Danielle Belgrave
Shravya Shetty
Po-Sen Huang
Ira Ktena
Arxiv (2023)
Towards Accurate Differential Diagnosis with Large Language Models
Daniel McDuff
Amy Wang
Karan Singhal
Yash Sharma
Kavita Kulkarni
Le Hou
Sara Mahdavi
Sushant Prakash
Anupam Pathak
Shwetak Patel
Ewa Dominowska
Juro Gottweis
Joelle Barral
Kat Chou
Jake Sunshine
Arxiv (2023)
Large Language Models Encode Clinical Knowledge
Karan Singhal
Sara Mahdavi
Jason Wei
Hyung Won Chung
Nathan Scales
Ajay Tanwani
Heather Cole-Lewis
Perry Payne
Martin Seneviratne
Paul Gamble
Christopher Kelly
Abubakr Abdelrazig Hassan Babiker
Nathanael Schaerli
Aakanksha Chowdhery
Philip Mansfield
Dina Demner-Fushman
Katherine Chou
Juraj Gottweis
Nenad Tomašev
Alvin Rajkomar
Joelle Barral
Nature (2023)
