AI/ML Research Engineer | Embedded Systems Engineer @ Boston Engineering
I build production AI systems across the full stack—from low-level embedded code to high-level intelligent behavior. My work spans multi-agent orchestration, ensemble learning, and knowledge-augmented generation.
Published at ACM ICMI 2025 with research on multimodal pain classification using physiological signals.
Multi-Agent AI Systems: Production-grade LangGraph orchestration with hybrid database architecture (MySQL + Neo4j + FAISS) for intelligent query routing and collaborative filtering
Multimodal ML Research: Ensemble learning achieving 1.0 binary accuracy on pain classification from physiological signals (EDA, BVP, RESP) using Catch22 feature extraction
Embedded Systems Engineering: Zephyr RTOS hardware migration, static analysis integration, and acoustic communications at Boston Engineering
Languages: Python, C/C++, Rust, TypeScript, SQL
AI/ML: PyTorch, LangGraph, Scikit-Learn, Hugging Face, FAISS
Infrastructure: Docker, Neo4j, MySQL, Git, CI/CD, Zephyr RTOS
Frontend: React, Node.js, Streamlit