I build systems powered by AI for environments where regulation, scale, reliability, and operational constraints shape every architectural decision. From research to production systems — where architecture matters more than frameworks.
Engineering under real constraints, delivered under real deadlines.
An on-device computer vision system, trained locally on Apple Silicon with MLX and YOLO26. Built for offline casualty triage — locally trained models, zero cloud dependency, designed for environments where connectivity cannot be assumed.
A research platform for peptide protocol tracking and real-world-evidence generation, built in 72 hours and designed around interoperable research data from day one.
Some engineering work is published in full. Some is intentionally published later — after the engineering reaches the standard I expect from public artifacts.
Constraints define the architecture, not the other way around.
Reproducibility beats intuition. Measure before optimizing.
Publish the reasoning, not only the code.
Some industries optimize for growth. I build for correctness.
BM25, dense retrieval, and Reciprocal Rank Fusion for Portuguese clinical text. Documented as an engineering lab — the decisions (ADRs), the experiments, and the architecture behind them, not just the code.
A clinical AI platform for regulated healthcare, shown here as an architecture case — by choice. The engineering reasoning is public; the implementation that constitutes the product is not.
BM25 and dense retrieval are complementary, not competing, for Portuguese clinical retrieval. Evaluated across 500 clinical queries.
The first benchmark for detecting Brazilian PII in Portuguese clinical text — seven identifier types with mod-11 checksum validation.
I build AI systems for problems where the engineering is the hard part. I train and evaluate models — including on-device inference on Apple Silicon — design retrieval and data pipelines, and publish the reasoning behind the systems whenever I can.
Before that, I founded and exited a technology company, then spent seven years in venture investing across healthcare, fintech, and SaaS. I also run an independent research capability (Cortexa) — computational pipelines, model training, and real-world-evidence work built from public data sources.