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 Speaker Profile

M.D., Professor, UCSF

Biography
Rajesh Shah, MD, earned his medical degree at The University of Chicago Pritzker School of Medicine in 2004, followed by a diagnostic radiology residency at University of Illinois Medical Center in Chicago (2009) and a vascular and interventional radiology fellowship at Stanford University Hospital in 2010. Since 2023 he has been Director of Interventional Radiology at the California Pacific Medical Center, Clinical Associate Professor at Stanford University, and an Interventional Radiologist at the VA Palo Alto Health Care System, where he has served in various leadership roles. Prior experience includes private practice and faculty roles at Weill Cornell Medical College and Memorial Sloan-Kettering Cancer Center in New York City. As an educator, Dr. Shah has mentored junior IR faculty at the VA Palo Alto, Stanford University, and at the California Pacific Medical Center. He has mentored trainees on research grants and created the VA resident rotation and mini-fellowship for IR-bound residents. Dr. Shah serves as the Society for Interventional Radiology (SIR) Division Councilor for Quality and Performance Improvement overseeing several committees dedicated to quality. In this role, he developed the Quality Improvement program for the SIR, and launched the VIRTEX Clinical Data Analytics Platform. Dr. Shah was appointed as affiliated faculty at the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI) and was awarded an AIMI grant to investigate machine learning in radiomics which has led to publications on machine learning in radiomics for lung cancer. He has published research on hepatocellular carcinoma, small-cell lung cancer, and embolic therapies. He is a Fellow of the Society of Interventional Radiology and active in the Society of Interventional Radiology and the American College of Radiology.


 Session Abstract – PMWC 2026 Silicon Valley

Track 2: AI - March 4 9.00 A.M.-5.00 P.M.


Track Chair:
Sharat Israni, UCSF

PMWC Award Ceremony
• Regina Barzilay, MIT
• Joe Petro, Microsoft
• Curtis P. Langlotz, Stanford University

Keynote: The Future of AI in Medical Imaging
• Curtis P. Langlotz, Stanford University

From Foundation Models to Digital Twins: AI Reshaping Clinical Imaging
• Chair: Alexander Weir, Canon Medical
• Regina Barzilay, MIT
• Joe Petro, Microsoft
• Curtis P. Langlotz, Stanford University

Fireside Chat
• Eric Horvitz, Microsoft
• Curtis P. Langlotz, Stanford University

Building Biological Digital Twins: Computational Models Linking Data to Disease Mechanisms
• Martin Stumpe, Danaher

Core AI Methods for Precision Medicine Foundations
• Chair: Sharat Israni, UCSF
• James Zou, Stanford University
• Regina Barzilay, MIT
• Olivier Gevaert, Stanford University

AI & Omics Foundation Models Powering Translational Research
• Chair: Janusz Dutkowski, Data4Cure
• Alex Moreau, Champions Oncology
• Jadwiga Bienkowska, Pfizer

Radiomics & Radiogenomics: Precision Imaging for Oncology
• Chair: Chris Hare, Canon Medical
• Ángel Alberich-Bayarri, Quibim
• Kevin Blyth, University of Glasgow
• Maria del Mar Alvarez Torres, Columbia University

Clinical Workflow Integration & Decision Support in Imaging
• Chair: Sharat Israni, UCSF
• David S. Liebeskind, UCLA
• Rajesh Shah, UCSF
• Roxana Daneshjou, Stanford University

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