Associate Professor · AI Researcher · Speaker
I study how AI systems produce decisions — and whether the humans orchestrating them can explain and defend those decisions. My research practice is built on Process Provenance: the principle that AI output is only defensible when the orchestration behind it is transparent and documented.
Deep research briefs generated by Rook (AI research engine) and curated for public release. Full archive in the vault.
How AI systems are reshaping trial design, endpoint selection, and statistical reporting — and what rigor looks like in that context.
Fabrication risk, citation hallucination, and what it takes for AI-assisted research to meet publication standards.
Practical frameworks for using AI tools in academic workflows without compromising intellectual ownership or institutional policy.
AI talks for academic, clinical, and professional audiences. Available for conferences, workshops, and institutional training.
Workshop · 2026
Hands-on workshop: when to use AI, how to document it, and what institutional accountability looks like in practice.
Seminar · 2025–2026
For graduate students and faculty: evidence quality, LLM limitations, and building defensible AI-assisted workflows.
Full talks archive and bookings: contact below
Provenance Labs is the hub. These four sites are the body of work it ties together.
AI-assisted work frameworks for organizations building with limited resources.
bootstrappers-playbook.netlify.app →Scientific integrity and the role of AI in biomedical research.
horizon-mandate.netlify.app →Responsible AI policy guide for researchers and institutional leaders.
stewards-schema.netlify.app →Workshop guide: AI integrity and intent for academics.
practitioners-compass.netlify.app →Available for talks, workshops, consulting engagements, and media appearances on AI in academic and clinical contexts.