Speaker Profile
PMWC LUMINARY AWARD
Advanced AI for drug discovery and clinical risk prediction
Ph.D., Professor, MIT
Biography
Regina Barzilay is a pioneering leader in developing machine learningmethods for drug discovery and clinical AI. . Her groundbreaking work hasproduced AI models for early cancer detection and therapeutic discoverythat have redefined what is possible in clinical diagnostics and biomedicalinnovation. At MI Ts Computer Science and Artificial Intelligence Laboratory and as AI Faculty Lead for the Jameel Clinic, she has advancedmethods that detect breast and lung cancer earlier and more accurately, forecast adverse drug effects before human trials, and accelerate thedesign of novel therapeutics. Her research blends cutting-edge machine learning with a commitment toresponsible integration of AI into precision medicine, ensuring thesetechnologies are safe, equitable, and impactful for patients worldwide. Barzilays contributions have earned her numerous honors, including the Mac Arthur Fellowship, election to the National Academy of Medicine, the National Academy of Engineering and recognition as one of the mostinfluential voices shaping the future of AI in healthcare.
Talk
Session Abstract – PMWC 2026 Silicon Valley
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
Getting Real Results with AI: Better Molecules, Smarter Devices, Faster Innovation
• Martin Stumpe, Danaher
Keynote: AI Tools for Cancer Diagnostics and Treatment
• Regina Barzilay, MIT
Core AI Methods for Precision Medicine Foundations
• Chair: Sharat Israni, UCSF
• James Zou, Stanford University
From Multimodal Data to Clinical Digital Twins: Linking Imaging, Omics, and Decisions
• Stephen Quake, Stanford
AI & Omics Foundation Models Powering Translational Research
• Chair: Janusz Dutkowski, Data4Cure
• Alex Moreau, Champions Oncology
• Jadwiga Bienkowska, Pfizer
AI-Enhanced Imaging: Radiomics, Radiogenomics, and Simulation
• 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
• Mohammad Alexanderani, U Pitt
AI-Powered Serverless HPC for Scientific Discovery
• Fengbo Ren, Fovus
