Biomedical scientist building evidence-based health intelligence. From molecular pharmacology to deployed AI, with published methodology at every layer.
"I turn clinical evidence into health products people can use. Then I publish the methodology so you can verify it."
RIGOR framework. Healthcare, automotive, municipal. FDA digital health. EU AI Act. Post-deployment monitoring.
Tire sidewall extraction. Dual-VLM consensus architecture. Edge deployment. NHTSA integration. Published methodology.
Multi-dimensional safety databases. Evidence tiers. Published methodology with DOIs. API design. Consumer product safety at scale.
hDAO enzyme modeling. Mast cell activation. Dietary trigger mapping. HS and rosacea connection. DAO deficiency prevalence.
Tyrosinase-TYRP1-TYRP2 melanogenic complex. Pregnancy and breastfeeding skincare safety. OCA genotype-phenotype.
Lactation pharmacology. CMPA cross-reactivity. Infant formula analysis. Postpartum safety. 18 formulas, 15 dimensions.
AlphaFold modeling. Molecular docking. In silico mutagenesis. Polypharmacology. Chemometrics and analytical validation.
Prompt Ladder methodology. IRB-filed study. Faculty workshop design. ACS CHED 2026.
Health AI was selected over Amazon, Microsoft, IBM, SAS, NTT Data, Dell, and Oracle for a major enterprise AI governance engagement.
Strategic advisory · Clinical AI validation · Evidence architecture · Research collaboration · Partnerships.
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