I turn messy clinical and research data into practical models, reproducible workflows, and decisions people can actually use.
My work sits at the intersection of clinical AI, biostatistics, real-world evidence, and research workflow design. I started in environmental systems and sustainability analytics, which gave me a useful habit: follow the data, respect the mechanism, and be suspicious of overly neat stories.
These days, I am especially interested in:
- Clinical AI: EHR prediction, clinical NLP, model evaluation, and deployment-minded analytics
- Research workflows: Table One, statistical analysis plans, reviewer responses, literature synthesis, and AI-assisted scientific work
- Systems analytics: complex data problems in healthcare, environment, energy, and sustainability
- Readable science: turning technical work into clear notes, papers, and tools
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