I'm the kind of engineer who can't just use a tool — I have to build one.
My biggest project, SubTrack, processes 1.19M+ corporate subsidiary records across 22K+ public companies. I built the entire thing: async data pipeline, AI enrichment engine (Google Gemini + SEC EDGAR + Wikipedia), 3D network visualizations, real-time streaming search, Stripe billing. The classification system hits 94% accuracy and I'm currently pushing that higher with XGBoost + FinBERT.
What makes me different: I sit at the intersection of AI/ML and full-stack engineering. I can train a model in the morning, build the API to serve it in the afternoon, and push the frontend that displays it by evening. Most people specialize in one lane — I connect all three.
Every project below has a live demo. I don't do README-only projects.
MS Computer Science @ UCF | Research paper targeting ICAIF 2026 | Looking for teams that ship fast and think big
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SubTrack — Corporate Subsidiary Intelligence AI platform mapping 1.19M subsidiaries across 22K+ public companies using SEC filings. Three-tier AI enrichment pipeline with 94% accuracy. Full-stack SaaS with auth, billing, and real-time search.
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ResuMorph — Resume Tailoring Engine Open-source ATS optimizer that runs entirely in-browser. Smart keyword matching with 150+ skills, compatibility scoring, weak verb replacement. Zero data collection.
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StockVision AI — Stock Analysis Platform LSTM neural networks for price prediction, gradient boosting for directional signals, backtesting engine, portfolio analytics. 46/46 tests passing.
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Intelligent code review powered by fine-tuned LLMs. Real-time PR analysis via webhooks for GitHub/GitLab/Bitbucket. Team dashboard with metrics.
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Building something interesting? Let's talk.