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.
Talk
Transparent AI Causal Reasoning + Genomics for Personalized Prevention
Genetic vulnerabilities predispose us to environmental biotoxin sensitivity, hormonal treatments side effects, reduced hormone conversion or detox capacity, inform our disease-risk profile and individual response to treatments. We explore how causal AI reasoning across genetics and labs creates clinical priorities, environmental epigenetic and pharmacogenomic insights that reduce trial-and-error in complex cases, up-skilling clinicians in weeks.
AI for Clinical Decision Support Systems Showcase:
Diadia Health
Diadia Health is epigenetics-informed root-cause reasoning AI - closing the gap in preventative and personalized care at scale. Safe and transparent medical reasoning AI that turns lab and genomics into effective protocols. We help clinicians solve complex cases with 60% less trial-and-error at the fraction of the cost.
Session Abstract – PMWC 2026 Silicon Valley
The PMWC 2026 AI for Clinical Decision Support Showcase will provide a 15-30 minute time slot for selected organizations, including commercial companies, clinical testing labs, and medical research institutions, to present their latest advancements, insights, applications, and technologies to an audience of clinicians, leading investigators, academic institutions, pharma and biotech, investors, and potential clients. We will learn about new technologies and findings that promise expedited, cost-effective, and accurate clinical diagnosis for early disease detection, treatment decisions, and disease prevention.
