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 Speaker Profile

Ph.D., CEO & Co-Founder, Diadia Health

Biography
For nearly two decades, I’ve worked at the intersection of academic research and real-world AI systems. I hold a PhD in AI and have spent my career building and deploying machine learning in high-stakes environments, including leading AI at Change.org and working at Google and Reddit. Over time, I kept seeing the same pattern: in complex endocrine, hormonal, and precision medicine cases, even excellent clinicians were forced to rely on fragmented data, personal heuristics, and trial-and-error. Genetics, various labs, and biomarkers were available, but rarely connected in a way that made decision-making truly systematic. That gap is what led me to co-found Diadia. At Diadia Health, we’re building an explainable clinical reasoning layer that helps clinics turn complex biological data into clear, defensible insights and protocols. Unlike generic AI tools or wrappers, our systems reason explicitly and transparently, using evidence chains and convergence, finding causal relationships with zero hallucinations.


 Session Abstract – PMWC 2026 Silicon Valley

Track 2: AI - March 5 9.00 A.M.-5.00 P.M.


Track Chair:
William Oh, Yale

PMWC Award Ceremony
• Nigam Shah, Stanford
• Thomas Fuchs, Lilly

Keynote: Responsible AI in Healthcare: From RWE to Agentic Systems
• Nigam Shah, Stanford

Keynote: Scaling Trusted AI: From Computational Pathology to Next-Gen Medicines
• Thomas Fuchs, Lilly

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: Nadia Poluhina, Mayo Clinic
• Kate Estep, Flatiron Health
• Alyssa Pybus, Moffitt Cancer Center
• Julie Stein Deutsch, Johns Hopkins
• Jeremy Jones, Mayo Clinic

Predicting Outcomes: An AI Model Trained on RWE 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

Keynote: AI for CDS-From Models to Bedside
• Zachary Ziegler, OpenEvidence

Operationalizing AI in Health Systems: Trust, Adoption & Outcomes
• Chair: Danton Samuel Char, Stanford
• Karan Singhal, OpenAI
• Sina Bari, iMerit Technology
• Shashi Shankar, Novellia
• Hal Paz, Khosla Ventures • Syed Mohiuddin, Anthropic

Safe, Scalable AI in Clinical Practice: What’s Working and What’s Not
• Chair: Vincent Liu, Kaiser
• Richard Milani, Sutter Health

Transforming Transplant Care Through AI: From Predictive Insights to Precision Decisions
• Jing Huang, CareDx

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 Durand, Klick Health

From Patient-Generated Data to Regulatory-Grade RWE: Design, Bias & Outcome Linkage
• Phil Johnson, Evidation

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