Medical Multimodal Models | Field

Research scientist and engineer focused on biomedical AI. He is a Member of Technical Staff at OpenAI, was previously a Research Scientist at Google DeepMind, and completed a Stanford PhD on accelerating biomedical intelligence.

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.

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.

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.

Armand Joulin is a research scientist at Google whose work spans natural language processing, machine learning, deep learning, and computer vision.

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.

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.

Research scientist at Meta working on multimodal machine learning and AI. Previously worked on multimodal learning at Google DeepMind and earned a PhD in computer vision and machine learning from Ecole des Ponts ParisTech.

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

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

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.

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.

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

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

Edouard Yvinec is a research scientist at the Allen Institute for AI working on language models, active learning, and sequence modeling. He previously completed a postdoctoral appointment at FAIR in Paris and earned a PhD from Sorbonne Universite, where he worked on active learning under Guillaume Lample.

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.

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.

Nino Vieillard is a Research Scientist at OpenAI. Previously, he worked on Gemini at Google and on multimodal models at Mistral AI.

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.

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

Tiam Jaroensri

Mercy Asiedu

Alan Karthikesalingam

Aishwarya Kamath

Dmitry (Dima) Lepikhin

Howard Hu

Robert Dadashi

Armand Joulin

Olivier Bachem

Timo Kohlberger

Andrew Sellergren

James C. Maron

Léonard Hussenot

Jean-Baptiste Alayrac

Vivek Natarajan

Pablo Liskowski

Thomas Mesnard

Bernardino Romera-Paredes

Katherine Heller

Sahar Kazemzadeh

Samuel Schmidgall

Spyridon Monachos

Susanna Maria Baby

Alek Andreev

Alexandre Ramé

Edouard Yvinec

Elena Buchatskaya

Fereshteh Mahvar

Greg S. Corrado

Junaid Maqbool

Kenneth Philbrick

Luca Biggio

Reagan Wetscherek

Scott Mayer McKinney

S. M. Ali Eslami

Vlad Feinberg

Yingzhen Li

Nino Vieillard

Demis Hassabis

Sebastian Borgeaud

Yossi Matias

Ali Karthikesalingam

Atilla Kiraly

Bram Sterling

Charles Lau

Christopher Kelly

Cían Hughes

Derek Oakden-Rayner

Geoffrey Cideron

Howard Yang

Jean-Bastien Grill

Jeremy Lai

Juraj Gottweis

Liron Yatziv

Louis Rouillard

Madeleine Traverse

Michelle Xu

Miriam J. Vogel

Paul Hughes

Per Bjornsson

Ramona Merhej

Richa Tiwari

Rose McNerney

Ryan Brush

Sarah Perrin

Sercan O. Arik

Stefanie Anna Baby

Sunny Jansen

Tatiana Matejovicova

Yori Zwols

Yun Liu