Speaker Profile
Lead, Epic
Biography
Rahul Shah is a healthcare data and artificial intelligence leader at Epic whose work spans the company’s Cosmos, genomics, and AI infrastructure. He has contributed to efforts that use large-scale, deidentified longitudinal health records to develop and evaluate models for clinical prediction, research, and decision support. Recent work from Epic has explored generative medical-event models trained on Cosmos data to learn patterns across diagnoses, medications, procedures, laboratory results, and other events in the patient journey. Mr. Shah has also discussed the opportunities and governance challenges involved in building health AI at population scale, including privacy, validation, clinical relevance, and responsible use. His work sits at the intersection of electronic health records, real-world evidence, genomics, and machine learning, with an emphasis on moving analytical capabilities closer to routine care. By connecting large clinical datasets with tools that clinicians and researchers already use, he helps advance practical applications of AI for personalized health prediction and evidence generation.
AI and Data Sciences Showcase:
AtaraxisAI
Session Abstract – PMWC 2027 Silicon Valley
Track Chair:
Vincent Liu, Kaiser Permanente
PMWC Award Ceremony
• Ziad Obermeyer, UC Berkeley (Luminary)
Featured Speakers
• Ziad Obermeyer, UC Berkeley
• John Halamka, Mayo Clinic Platform
• Ashley Beecy, Sutter Health
• Shiv Rao, Abridge
• Munjal Shah, Hippocratic AI
• Vivek Natarajan, Google Health
• Vincent Liu, Kaiser Permanente
• Mark Sendak, Duke Health
• Joshua Denny, NIH
• Chris Lunt, Critical Path Institute
• Ida Sim, UCSF
• Travis Zack, OpenEvidence
• Danton Char, Stanford
• Brian Anderson, CHAI
• Julia Adler-Milstein, UCSF
The Year in Clinical AI
What shipped, what failed, and what should change next.
AI Agents in Clinical Workflows
Ambient documentation, patient-facing agents, and operational agents in real care.
Foundation Models in Healthcare
What makes a clinical foundation model useful, deployable, and trusted.
AI, Human Cohorts, Trials & RWE
Turning clinical data into stronger trials and decision-grade evidence.
AI Safety, Governance & Evaluation
Avoiding harm at scale when algorithms move into production.
AI + Pharmacogenomics
How decision support and drug-response data can make each other more useful.
Davos of Precision Medicine
PMWC 2027 Program
January 27–29, 2027 · Santa Clara Convention Center
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In a few words.
PMWC is indeed The Davos of Biotech
PMWC Hall of Impact
Previous Speakers Include
Nobel laureates, technology founders, regulators, CEOs and scientific pioneers who have taken the PMWC stage.
