CVPR 2026 Workshop on Medical Reasoning with Vision Language Foundation Models

Introduction

Vision-language foundation models demonstrate strong performance in pattern recognition, but lack robust reasoning capabilities, limiting their application in specialized domains. Medical imaging highlights this critical limitation: diagnosis requires connecting visual findings with clinical knowledge through explicit reasoning processes. While foundation models excel at visual recognition, medical decision-making demands interpretable chain-of-thought diagnosis, multimodal grounding of visual features in clinical knowledge, comprehensive evaluation frameworks for reasoning quality, and probabilistic reasoning for clinical decisions. Given the rapid advancements in foundation models over the past three years, addressing these reasoning gaps has become essential for deploying AI systems in high-stakes healthcare applications where explainability and trustworthiness are paramount.

The CVPR 2026 Workshop on Medical Reasoning with Vision Language Foundation Models (Med-Reasoner) aims to bring together computer vision researchers, medical AI experts, imaging scientists, and practicing clinicians to discuss state-of-the-art advancements, applications, and challenges in reasoning capabilities for medical vision-language models. The workshop will foster discussions that inspire innovation in interpretable medical AI and address real-world deployment challenges including privacy constraints, workflow integration into healthcare systems, and ensuring fairness across patient populations. Through invited talks from leading researchers at Google DeepMind, Stanford, MIT, and University of Toronto, contributed paper presentations, interactive poster sessions, and expert panel discussions, we will establish reasoning architectures and evaluation frameworks that advance healthcare applications with the potential to impact millions of patients globally.

Invited Speakers

Michael Moor, MD, PhD

Assistant Professor
ETH Zurich

Tanishq Mathew Abraham, PhD

Founder & CEO, Sophont

Shekoofeh Azizi, PhD

Senior Research Scientist
Google DeepMind

TBA

 

Organizers

Anas Zafar

Research Associate
UT MD Anderson Cancer Center

Muhammad Waqas, PhD

Postdoctoral Fellow
UT MD Anderson Cancer Center

Jia Wu, PhD

Associate Professor
UT MD Anderson Cancer Center

David A. Jaffray, PhD

Sr VP, Chief Tech & Digital Officer
UT MD Anderson Cancer Center

Tianlong Chen, PhD

Assistant Professor
UNC Chapel Hill

Nouha Dziri, PhD

Research Scientist
Allen Institute for AI (Ai2)

Xiaoxiao Li, PhD

Associate Professor
University of British Columbia

Alejandro Lozano

PhD Candidate
Stanford University

Technical Program Committee

Call for Reviewers: If you are interested in contributing to our paper review process, please complete the sign-up form. We will publicly acknowledge our program committee members. Your expertise and time dedicated to this effort are greatly appreciated and crucial to the success of the workshop.

📅 Important Dates

Contact

If you have any questions, please contact:
AZafar2@mdanderson.org
anaszafar98@gmail.com

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