Medical Multimodal Models | Field

Member of Technical Staff at OpenAI focused on accelerating biomedical intelligence. He was previously a Research Scientist at Google DeepMind.

DeepMind researcher working on machine learning, computer vision, and structured learning from video and language.

Shekoofeh Azizi is a staff research scientist and research lead at Google DeepMind. Her Google Research profile says she works on biomedical super-intelligence to accelerate scientific discovery, with a particular focus on cancer, and helps lead efforts behind Med-PaLM, Med-Gemini, TxGemma, Tx-LLM, and C2S-Scale. UBC's Centre for Internet Computing profile says she earned a bachelor's degree in electrical engineering from Sharif University of Technology and a PhD in computer science from the University of British Columbia.

Claire Cui is a Google Fellow in the Google Brain team, where she leads research on deep generalist learning, large language models, multimodal learning, and interpretable AI. During her tenure at Google she helped found AdSense for Content and co-founded Google Health Research and Medical Brain; she holds a Ph.D. in computer science from Stanford and a B.S. in computer science from Tsinghua University.

Postdoctoral associate at MIT CSAIL working at the intersection of machine learning and healthcare. He earned a PhD in computer science from Cornell University and studies multimodal medical AI.

Postdoctoral research scientist at Google Research working on machine learning for healthcare, medical imaging, and responsible AI.

Head of AI at Google Health in London and a practising NHS vascular surgeon whose work focuses on safe, effective and equitable medical AI.

UCLA's official profile says Charles Tseng-Chun Lau is an HS Clinical Professor of Radiological Sciences, a cardiothoracic radiologist at the VA Greater Los Angeles Healthcare System, and has worked on assignment at Google since 2019 in artificial intelligence.

Works on information extraction, tabular data, and NLP for healthcare, and previously completed an MS in Robotics at Carnegie Mellon University.

Anil Palepu is a research scientist at Google Research working on LLM-based systems for medical and biomedical applications, including the AMIE project. Public sources also show a 2025 PhD from Harvard-MIT Health Sciences and Technology and earlier biomedical engineering degrees from Johns Hopkins.

Chunjong "CJ" Park says he works at the intersection of multimodal LLMs and health at Google DeepMind, after a Ph.D. in computer science and engineering from the University of Washington.

Michelle Casbon has a Google Research profile in machine intelligence and software systems, and a QCon speaker page that identifies her as a software engineer at Google Brain. The QCon bio says she worked on Swift for TensorFlow and MLIR and studied computer science and mathematics at the University of Illinois at Urbana-Champaign.

Bashir Sadjad's public site says he is a software engineer at Google focused on healthcare data infrastructure; his public resume also lists long-running Google work including Cloud Healthcare efforts.

Richa Tiwari is a program manager in the Health AI team under Google Research, where she leads research implementation and deployment of AI solutions in healthcare in the APAC region. She has a Ph.D. in Molecular Biology from the University of Texas at Austin and a B.S. in Biology from Brandeis University.

Research scientist at Google DeepMind working on multimodal AI and embodied agents. Her work spans vision-language learning, robotics, and using large models for perception and action.

Google DeepMind researcher working on machine learning, hardware accelerators, and distributed computing, and a co-author of the MedGemma technical report.

Research scientist at Google DeepMind working on multimodal large models and efficient deployment. His public work focuses on building practical AI systems and interfaces.

Senior staff research scientist at Google DeepMind working on machine learning, computer vision, and computational photography.

Robert Dadashi is a Senior Staff Research Scientist at Google DeepMind in Paris, where he has led post-training work on Gemma models. His published work spans reinforcement learning, imitation learning, offline RL, and factually consistent summarization.

Staff research scientist at Google DeepMind in Zurich working on machine learning and large language models. His research interests include deep learning and practical foundation model systems.

Stanford Medicine lists David Steiner as an adjunct clinical assistant professor in pathology with research interests in somatic mutations, aging, and cancer. He is also listed as an author of the MedGemma 1.5 Technical Report.

Yun Liu is a senior staff research scientist at Google Research whose official profile describes work on machine learning across pathology, ophthalmology, radiology, dermatology, and other medical applications.

Works on deep learning, medical imaging, and medically tuned LLM applications to improve patient outcomes.

Public Google sources describe Joelle Barral as a senior research leader at Google DeepMind in Paris. Institutional biographies also note earlier work at Verily and HeartVista and degrees from Ecole Polytechnique and Stanford.

Sunny Virmani is a product manager with Google Health focused on product development and global marketing of medical imaging technologies, and is listed as a coauthor of the MedGemma 1.5 Technical Report.

Olivier Bachem is a director and research scientist at Google DeepMind working on reinforcement learning from human feedback, language model post-training, and machine learning at scale. He earned his PhD at ETH Zurich, where he studied coresets and sampling methods for large-scale machine learning.

Staff Research Scientist at Google DeepMind based in Zurich, focusing on multimodal medical foundation models and trustworthy AI for health.

Public research profiles show Armand Joulin as an author on work in natural language processing, information retrieval, and computer vision.

Senior research scientist at Google DeepMind whose public work focuses on reinforcement learning from human feedback, alignment, and large language model evaluation.

Google DeepMind researcher whose public work includes MedGemma and multimodal learning for medical imaging and reasoning.

Physician-scientist and pediatric emergency medicine specialist at Harvard Medical School and Boston Children's Hospital. His research spans machine learning in healthcare, medical decision-making, and AI for improving pediatric care.

Léonard Hussenot is a research scientist at Google DeepMind whose public homepage highlights machine learning research and publications.

Andrew Sellergren's public pages identify him as a software engineer at Google, and his Google Research profile shows publications in health AI, pathology, and medical imaging.

Google's public materials identify Avinatan Hassidim as VP Research at Google Research. His Google Research profile covers algorithms, economics and electronic commerce, and machine intelligence.

Yossi Matias leads Google Research and is publicly associated with work spanning foundational ML, health AI, generative AI, and large-scale data systems.

Research scientist at Google DeepMind working on multimodal medical AI and personalized health applications.

Edouard Yvinec maintains a public academic webpage with publications, teaching materials, and a one-page CV, and it links public Google Scholar and LinkedIn profiles.

Researches multimodal foundation models and evaluation for healthcare, working with James Zou after prior research engineering work in Nigam Shah's lab.

Senior staff research scientist at Google DeepMind and Turing AI Fellow at the University of Cambridge working on deep learning and its applications to medicine.

VP of AI Research at Google and a senior director at Google Research whose work spans responsible AI, probabilistic machine learning, and health applications.

Software engineer in Research at Google DeepMind interested in large-scale and multimodal models, especially for health applications.

Samuel Schmidgall is a researcher whose work focuses on large-scale multimodal and medical AI, generative models, and machine learning for healthcare. He was an author on the MedGemma technical report and maintains a public research homepage with publications and talks.

Spyridon Monachos is a researcher at Google DeepMind working on multimodal applications in medical AI. His background spans natural language processing, medical AI, and large multimodal models, with prior research at King's College London and the University of Cambridge.

Research scientist at Google and member of the Med-Gemma team working on multimodal AI and generative AI for healthcare.

Google Research posts in January and March 2026 identify Fereshteh Mahvar as a software engineer working on MedGemma and related health AI releases.

Google Research's people page describes Tris Warkentin as a Product Management Director at Google DeepMind who previously led product efforts for Google Brain and TensorFlow tooling.

Katherine Chou focuses on technologies that improve health outcomes and remove friction in care delivery. Public speaker materials describe product leadership experience across Google X, Verily, and Google Research.

Public sources list Kat Black as "Labs Strategy & Operations, Senior PgM" on a Google I/O speaker page and as a coauthor on the MedGemma 1.5 Technical Report.

Public sources identify Can Kirmizibayrak as a coauthor on Health AI Developer Foundations and MedGemma 1.5, and DBLP lists earlier publications in medical data visualization and surgical imaging.

Preeti Singh has a Google Research profile that places her work in health and bioscience applications, data management, and data mining and modeling. The page lists publications on representation learning for cancer applications and coauthorship on the MedGemma technical report, supporting a conservative first-pass profile tied to medical and bioscience ML work at Google.

Yong Cheng has an official Google Research people page with publications in machine intelligence, machine translation, and natural language processing, and is a coauthor of the MedGemma 1.5 technical report.

Research scientist at Google DeepMind working on multimodal and generative AI for healthcare.

Google's public research directory lists Tao Tu with publications in health and bioscience, machine intelligence, and natural language processing, including MedGemma-related work.

Public workshop materials list Madhuram Jajoo as a Software Engineer on Open Health Stack and Health AI at Google, and as a coauthor of the MedGemma 1.5 technical report.

Elena Buchatskaya is a research scientist at Google DeepMind whose public profile and Google Scholar page highlight work on machine learning for healthcare, multimodal models, and medical AI.

Research scientist at Google DeepMind focused on multimodal learning and vision-language models for healthcare.

Senior research scientist at Google whose work spans large-scale machine learning and computational neuroscience.

Junaid Maqbool is a research scientist at Google DeepMind whose work focuses on machine learning, large language models, and medicine.

Research scientist whose work focuses on multimodal machine learning and medical image analysis.

Research scientist at Google DeepMind working on machine learning for healthcare, trustworthy AI, and multimodal foundation models.

Research scientist at Google DeepMind working on multimodal medical AI and generative models for healthcare.

Research scientist at Google DeepMind working on multimodal AI, generative models, and world models; previously held research roles at the University of Cambridge and the Alan Turing Institute.

Research scientist at Google DeepMind working on machine learning and language models.

Reader in Machine Learning at Imperial College London, long-term visitor at Google DeepMind, and AI for Science theme lead at the UKRI AI Centre for Doctoral Training in Foundational AI.

Daniel Golden is publicly credited by Google Research as an engineering manager on MedGemma and related Health AI Developer Foundations work.

Kenneth Philbrick is publicly described as leading ML externalization for Google Research's Health AI Developer Foundations digital pathology program and appears on related Google Research publications.

A Google Research blog post identifies Madeleine Traverse as a software engineer and coauthor of CT Foundation work in medical imaging; she is also listed on the MedGemma technical reports.

President's Cancer Panel materials publicly listed Shravya Shetty as Engineering Director at Google Health in 2021. Google Research publication pages and the MedGemma 1.5 technical report identify her as an author on health AI developer foundations, multimodal health LLM work, and MedGemma medical model research.

Founder and CEO of Google DeepMind, leading AI research and product development; his work spans AI, neuroscience, game playing, and structural biology.

Research scientist at Google DeepMind in London working on agentic reasoning, efficient inference, and large-scale post-training, with a background in high-dimensional statistics and theory.

Vice President of Engineering and Research at Google and site lead for the Google Center in Israel; he also leads Search, Research, and AI for Crisis Response.

Google public sources identify Preeti Singh on Google Research, with research areas in health and machine intelligence, and list her as Senior Technical Program Manager, Google Research on a 2024 Google blog post. The MedGemma 1.5 Technical Report lists her as a coauthor.

Public sources tie Fayaz Jamil to Google medical AI technical reports spanning multimodal clinical models and health foundation-model infrastructure.

Public sources identify Swapnil Vispute as a coauthor on the MedGemma 1.5 Technical Report and on public-health research studying mobility and COVID-19 case growth in the United States.

Dale R. Webster is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Harshad Purandare is publicly listed on the MedGemma 1.5 technical report and on a Google Health workshop program as Product Manager, Health AI India. No official personal profile page was found, so the summary is kept narrow.

Jeremy Lau is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Public Google sources identify Kavi Goel on Google's structured-data and AdWords product work, and the MedGemma 1.5 technical report credits Kavi Goel as an author.

Moein Shakeri is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Neel Singhal is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Nino Vieillard is listed as an author of the Google technical report MedGemma Technical Report.

Nishanth Sastry is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Pooja Singhal is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Rohit Shetty is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Sebastian Tellex is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Shravya Shekar is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Suzan Khoubyari is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Tobias Gerstenberg is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Vivien Mielke is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Xin Wang is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Yinxiang Zhang is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Yuan Liu is listed as an author of the Google technical report Advancing Multimodal Medical Capabilities of Gemini.

Scott Mayer McKinney is a coauthor on medical-imaging AI studies published through Google Research and biomedical venues, including work on breast cancer screening and mammography triage.

VP and Lead for Health at Google DeepMind, and a clinical scientist and engineer focused on machine learning for health.

Google researcher whose public profile lists work across natural language processing, machine learning, multimodal models, and computer vision.

Research scientist at Google DeepMind focused on multimodal machine learning, healthcare, and responsible AI.

Google researcher whose publications include the PaLM 2 technical report.

VP and Chief Scientist of Google Health, and a physician-engineer working on machine learning for healthcare.

Google DeepMind researcher and MedGemma coauthor with a verified Google Scholar profile.

Radiologist, researcher, and data scientist at Google DeepMind based in Sydney.

Research scientist at Google DeepMind who contributed to MedGemma and public work on medical AI models.

Howard Yang is a Research Scientist at Google DeepMind whose work spans multimodal systems, language models, and human-centered AI. He has contributed to medical and multimodal foundation-model research including MedGemma.

Research scientist and team lead at Google DeepMind in Canada whose work spans foundational AI, multimodal learning, and applications of AI in the sciences.

Researcher working on medical multimodal AI and foundation models, including MedGemma.

Juraj Gottweis is a software engineer at Google DeepMind working on medical AI, with interests in multimodal medical applications and large language models.

Postdoctoral researcher at Google DeepMind working on machine learning for medical applications and responsible AI.

Louis Rouillard is a research scientist at Google whose public homepage highlights work on health AI and machine learning.

Research scientist at Google DeepMind working on vision-language models; her public OpenReview profile also lists prior study at University College London.

Michelle Xu is a software engineer at Google DeepMind interested in multimodal large language models and biomedical applications.

Researcher working on medical AI and multimodal foundation models, including Gemini-based health applications.

Research scientist at Google DeepMind working on multimodal AI, including medical applications of Gemini.

Per Bjornsson is a Research Scientist at Google DeepMind working on natural language processing and machine learning.

Research scientist at Google DeepMind working on multimodal machine learning for healthcare, AI for clinical support, and large multimodal medical models such as Med-PaLM M and MedGemma.

Program manager on the Google Health AI team focused on healthcare and life sciences, with a stated goal of improving healthcare quality and access through AI.

Google DeepMind researcher working on medical AI, multimodal systems, large language models, and human-computer interaction, and a co-author of work on Gemini's multimodal medical capabilities.

Research scientist at Google Research and Google DeepMind focused on multimodal foundation models for medicine and their safe, equitable use, according to his official author page.

Software engineer and research scientist at Google DeepMind working on multimodal foundation models for health applications, according to her personal site.

Sercan O. Arik is a Research Scientist at Google DeepMind working on vision-language and multimodal foundation models, with prior work across Google Cloud AI and Google Health.

Senior technical program manager at Google with experience spanning software engineering, distributed systems, and AI product delivery.

Researcher working on medical multimodal AI and foundation models, including MedGemma.

Research scientist at Google DeepMind working on machine learning for healthcare and multimodal medical AI.

Researcher working on medical AI and multimodal learning, with publications on Gemini medical capabilities and related health modeling.

AI researcher at Google Research focused on biomedical AI and medical imaging; her arXiv author results include the MedGemma technical report.

Khaled Saab

Jean-Baptiste Alayrac

Shekoofeh Azizi

Claire Cui

Tiam Jaroensri

Mercy Asiedu

Alan Karthikesalingam

Charles Lau

Chufan Gao

Anil Palepu

Chunjong Park

Michelle Casbon

Bashir Sadjad

Richa Tiwari

Aishwarya Kamath

Dmitry (Dima) Lepikhin

Howard Hu

Pablo Liskowski

Robert Dadashi

Thomas Mesnard

David F. Steiner

Yun Liu

Dale Webster

Joelle Barral

Sunny Virmani

Olivier Bachem

Timo Kohlberger

Armand Joulin

Alexandre Ramé

Andrew Sellergren

James C. Maron

Léonard Hussenot

Andrew Sellergren

Avinatan Hassidim

Yossi Matias

Vivek Natarajan

Edouard Yvinec

Rahul Thapa

Bernardino Romera-Paredes

Katherine Heller

Sahar Kazemzadeh

Samuel Schmidgall

Spyridon Monachos

Susanna Maria Baby

Fereshteh Mahvar

Tris Warkentin

Katherine Chou

Kat Black

Can Kirmizibayrak

Preeti Singh

Yong Cheng

Alek Andreev

Tao Tu

Madhuram Jajoo

Elena Buchatskaya

Fereshteh Mahvar

Greg S. Corrado

Junaid Maqbool

Kenneth Philbrick

Luca Biggio

Reagan Wetscherek

S. M. Ali Eslami

Vlad Feinberg

Yingzhen Li

Daniel Golden

Kenneth Philbrick

Madeleine Traverse

Shravya Shetty

Demis Hassabis

Sebastian Borgeaud

Yossi Matias

Preeti Singh

Fayaz Jamil

Swapnil Vispute

Dale R. Webster

Harshad Purandare

Jeremy Lau

Kavi Goel

Moein Shakeri

Neel Singhal