I'm an AI/ML Engineer & Full-Stack Developer with an MS in CS (Machine Learning) from George Mason University (GPA: 3.87). I don't just build models — I ship production AI systems that handle real users and real data.
- 🔭 Currently building Bridgette, a production RAG pipeline at BridgeNow AI — matching users to domain experts at scale using LangChain + semantic vector search
- 🤖 Specialties: RAG pipelines, LLM agents, multi-agent orchestration, AI-powered full-stack apps
- 🧪 Obsessed with inference reliability, latency optimization, and measurable real-world impact
- 📍 Based in New York, NY — available for full-time roles
| Project | What it does | Stack |
|---|---|---|
| Sonus 🏥🎙️ | AI clinical voice intake — conducts a structured pre-consultation voice interview with hospital patients, then auto-generates a physician-ready SOAP note using Claude Sonnet; supports 6 simulated patient cases + custom clinical context upload | Next.js, Vapi, Claude Sonnet, Tavily, Framer Motion |
| DryRun 🎙️ | Voice AI workplace simulator — practice hard conversations (raises, resignations, feedback) against an AI that plays the other person with real-time tactic detection and post-session debrief scoring | Next.js, Vapi, GPT-4o, Cartesia voice cloning, Tavily |
| ClearCare 🏥 | AI Medicare cost navigator — 8-node LangGraph pipeline maps symptoms → procedures → real out-of-pocket costs across 2.8M+ CMS providers | Next.js 14, FastAPI, LangGraph, GPT-4o, Supabase |
| MediConnect ⚡ | AI healthcare platform matching patients to providers in <500ms via custom stream processing over a 704MB dataset | React, FastAPI, Gemini API |
| CitationSleuth 🔍 | Dual-layer RAG fact-checking system using Neo4j graph retrieval + semantic similarity to detect LLM hallucinations on 1,000+ HaluEval samples | Python, Neo4j, HuggingFace, Streamlit |
| Hospital Readmissions ML 📊 | Classification pipeline on 100K+ patient records — 9% accuracy boost via PCA + Decision Tree optimization | Python, Scikit-learn, PCA |
| Car Temp Analysis 🚗 | Hardware-free in-car temperature forecasting — R² = 0.9997 with Random Forest + thermal imaging | Python, KNN, Random Forest |
AI / ML
Backend & APIs
Frontend
Databases & Vector Stores
🏅 Microsoft Fabric Analytics Engineer Associate — Microsoft, Jan 2026
🏅 Generative AI with LLMs — NVIDIA, Jan 2026
🏅 Agentforce Specialist — Salesforce, Dec 2025
🏅 OCI 2024 AI Foundations Associate — Oracle, Oct 2024
🏅 Generative AI Fundamentals — Databricks, Aug 2024
🏅 Prompt Engineering for Everyone — IBM, Aug 2024