- 🎓 B.S. in Computer Science & Data Science @ Rutgers University, Class of 2028 (GPA: 3.82, Dean's List)
- 🔬 Software Engineer & ML Research Assistant at the Rutgers School of Environmental and Biological Sciences, building agentic pipelines and forecasting models
- 🤖 AI/ML Fellow at Break Through Tech - Cornell Tech, selected from 4,000+ applicants
- ✍️ First author on a manuscript forecasting dollar spot disease outbreaks in turfgrass
- 💡 Interested in multi-agent LLM systems, applied ML, and full-stack products that put models into people's hands
🌾 Turfgrass Pathology Lab — Agentic Forecasting Platform Orchestrating 10 parallel LLM agents (Anthropic/OpenAI) across weather, disease, pest, herbicide, and news domains to deliver ZIP-specific spray guidance, plus a 19-node LangGraph pipeline that automates the lab's weekly newsletter. Shipped a subscriber platform (React, TypeScript, FastAPI, PostgreSQL) covering 11,000+ ZIP codes across the Northeast and Midwest.
📊 Dollar Spot Outbreak Forecasting A two-stage hybrid ensemble (Random Forest + XGBoost/LightGBM via Darts) built to outperform the industry-standard Smith-Kerns model — 93.8% recall / 0.987 AUC on outbreak detection, plus a progression regressor (R² = 0.70) enabling non-calendar, targeted spray timing.
🛠️ Data Analytics & AI Skills Playbook A 21-skill AI-assisted engineering library that automates dataset-quality audits (from ~15–20 minutes down to under a minute) and applies model-comparison/overfitting-detection tooling to real ML projects.
🎓 StudyBuddy A multi-agent tutoring system (LangGraph, pgvector, React, FastAPI) with 6 specialized LLM agents delivering context-grounded Q&A and adaptive practice, deployed across Vercel, Railway, and Supabase.
Languages
AI / ML / Data
Web / Cloud
Tools
Let's build something — reach out at massad.raza@outlook.com