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CS at UC San Diego. I've spent the last year building things at the intersection of AI and healthcare — a local LLM triage tool for disaster zones, CNN models for skin cancer detection, and whatever comes next.

Most of what I build starts as a problem I couldn't find a clean solution to. I figure it out from there.


🔨 What I've Built

MeDAKit — Offline AI medical triage assistant for disaster zones. Runs fully on-device via Ollama + Gemma, returns analysis in under 1.5s, handles 100 simultaneous hotspot connections. Built at a hackathon. Zero internet required.

Sports Betting Predictive Engine — XGBoost + scikit-learn pipeline forecasting NBA player stat lines with 75% accuracy. Pulls live matchup data, runs daily predictions, serializes models for game-day inference.

IP Protection & Copycat Detection — ORB + SSIM image comparison pipeline that autonomously scrapes and flags counterfeit listings. Custom scoring algorithm to minimize false positives.


🧠 Experience

  • Software Intern @ YCrest — B2B revenue intelligence startup; building on the revenue data and integrations stack
  • Software Intern @ Vivid Computing — AI recommendation system using neural networks and clustering
  • ML Research Intern @ ASDRP — CNN models for skin cancer detection; presented findings to faculty panel

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AI / ML

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