Brandon Duplantier

I’m a bioinformatics student with demonstrated experience designing and validating computationally intensive biological workflows in Python. I bring a practical, results-focused approach to turning messy biological and healthcare data into systems that can be checked and trusted.

In my projects, I built an organ rejection risk scoring system that ingests patient dose CSV data and computes adherence rates, timing errors, and a weighted risk score. I classify patients into low, moderate, and high risk tiers using threshold logic and statistical analysis, then generate clinical recommendations as structured text validated against edge cases.

I also developed an AI-driven data pipeline that produces structured JSON output with schema validation to ensure correctness. My goal is to make outputs programmatically verifiable—essentially combining problem-answer-validation loops with real pipeline automation.

Alongside my coursework, I’ve worked as a freelance data analyst handling healthcare claims analysis and utilization data. Using SQL, I deliver dashboard reporting and written summaries while keeping my workflows reproducible and documented for non-technical stakeholders.