Physician building AI systems that help clinicians make better decisions. My background in medicine, biomimicry, and machine learning shapes how I think about designing transformative health solutions that are both safe and effectve.
Current Work
As Chief Medical AI Officer at Scienza Health, I lead development of conversational AI systems for healthcare—digital humans that can screen patients, conduct assessments, and support clinical workflows. We're focused on ambient cognitive screening, working with partners like Samsung Health and PointClickCare, along with pharmaceutical companies on AI-powered remote patient monitoring.
Previously at Cortechs.ai, I helped develop FDA-cleared brain imaging tools for Alzheimer's, multiple sclerosis, and brain tumor assessment. I also advise companies and academic groups on healthcare AI, such as EpiFocus (seizure prediction via connectivity and chaos theory) and the Pitt HexAI Lab at the University of Pittsburgh.
Background
I completed my MD at Mayo Clinic, where I helped build and scale an NLP-based patient portal message triage system called Domi (previously R00T). As a dual degree, I earned an MS in Biomimicry at Arizona State University. As a research fellow at the NIH, I studied NK cell protein receptor modeling under Sumati Rajagopalan and Eric O. Long. For undergraduate training, I studied biochemistry & genetic bioinformatics at University of Illinois at Urbana-Champaign, focusing on tRNA and mycobacteria under the mentorship of Susan Martinis. I had the privilege to work under Ronnie Berntsson and Pål Stenmark as part of an exchange program with Stockholm University to study structural biology and crystallography for evaluating nucleotide-based cancer drug targets.
Born and raised in Orland Park, Illinois.
Currently based in Scottsdale, Arizona 🏜️
What I'm Thinking About
"Whoever cannot seek the unforeseen sees nothing, for the known way is an impasse."
- Voice AI in healthcare — Real-time speech understanding enabling natural patient interactions, ambient documentation, and scalable screening.
- Healthcare operations automation — Agentic systems that handle scheduling, prior authorizations, and clinical workflows end-to-end.
- Decentralized clinical trials — Remote monitoring and digital endpoints that bring trials to patients rather than patients to sites.
- Ambient clinical intelligence — Passive sensing through voice, gait, sleep, and facial micro-expressions for continuous health monitoring.
- Biological foundation models — Large-scale models trained on protein sequences, genomics, and molecular data to predict biological function.
- Theragnostic platforms — Photoacoustic and bioelectric systems that diagnose and treat simultaneously at the molecular level.
- Quantum biology — Understanding quantum effects in photosynthesis, enzyme catalysis, and magnetoreception as inspiration for new sensing approaches.
- Alternative computing paradigms — Neuromorphic, photonic, and quantum architectures that move beyond traditional von Neumann constraints.
More in this talk.