Speaker Profile
Biography
Alyssa received her B.S. in Biological Engineering from Massachusetts Institute of Technology in 2016 and her Ph.D. in Bioengineering from Georgia Tech in 2023. Her research experience includes projects in neuroimmune signaling, proteomics, single cell and bulk tissue transcriptomics, microRNA biomarker discovery, and multivariate data analysis methods. Her current research focuses on applying machine learning and multimegavariate methods to multiomic and spatial data sets in support of precision oncology projects.
Session Abstract – PMWC 2026 Silicon Valley
Track Chair:
William Oh, Yale
PMWC Award Ceremony
• Nigam Shah, Stanford
• Thomas Fuchs, Lilly
Keynote
• Thomas Fuchs, Lilly
Keynote
• Nigam Shah, Stanford
Real-World Evidence & Clinical AI: Closing the Loop Between Data and Care
• Chair: Roxana Daneshjou, Stanford
• Aashima Gupta, Google
• Brigham Hyde, Atropos Health
• Michael Pfeffer, Stanford
• Thomas Fuchs, Lilly
From Data to Decisions: Building Regulatory-Grade RWE from EHR Systems in Oncology
• Chair: Kate Estep, Flatiron Health
AI and Real-World Evidence: Building a Learning Health System for Precision Care
• Rich Gliklich, OM1
AI for Clinical Decision Support: From Models to Bedside
• Chair: Amrita Basu, UCSF
• Anurang Revri, Stanford
• Emily Alsentzer, Stanford
• Okan Ekinci, Roche
AI for CDS: From Models to Bedside
• Zachary Ziegler, OpenEvidence
Operationalizing AI in Health Systems: Trust, Adoption & Outcomes
• Chair: Danton Samuel Char, Stanford
• Matthew Solomon, Sutter Health
• Karan Singhal, OpenAI
• Sina Bari, iMerit Technology
• Shashi Shankar, Novellia
• Hal Paz, Khosla Ventures
Safe, Scalable AI in Clinical Practice: What’s Working and What’s Not
• Chair: Vincent Liu, Kaiser
• David Entwistle, Stanford Health Care
AI for Precision Psychiatry: Integrating Multimodal Data Into Clinical Decision Support
• Erwin Estigarribia, HEADLAMP health
Workflow-First Clinical AI: Integration Patterns, Guardrails & Change Management
• Jorge Duran, Klick Health
From Patient-Generated Data to Regulatory-Grade RWE: Design, Bias & Outcome Linkage
• Greg Bowyer, Evidation




