Building intelligent systems at the intersection of deep learning and scalable engineering. From CNN-BiLSTM models to production-grade Rails platforms — I ship end-to-end.
LangGraph · Gemini · Qdrant · MCP · End-to-end evidence synthesis
A multi-agent system that answers clinical questions by orchestrating six specialized agents — PICO decomposition, semantic cache lookup, multi-source search, relevance screening, evidence synthesis, and deterministic citation fact-checking. Queries PubMed, ClinicalTrials.gov, and the FDA in parallel, then produces a GRADE-Lite quality-rated report with verified citations. Includes a custom MCP server exposing clinical tools to Claude Desktop and other MCP clients, plus full Langfuse observability across every agent run.
CNN-BiLSTM · MIT-BIH Arrhythmia Database · Production-grade pipeline
A production-grade MLOps pipeline detecting cardiac arrhythmias from ECG signals. Covers the full ML lifecycle — data versioning with DVC, experiment tracking with MLflow, containerized inference with FastAPI and Docker, live Gradio demo, GitHub Actions CI/CD, and Evidently AI drift monitoring. Achieves 0.98 macro F1 and 99% weighted accuracy across 5 arrhythmia classes.
YOLOv8-powered traffic density analysis that optimizes signal durations for smarter urban traffic management.
Decode the emotional tone of any text instantly using a spaCy NLP model — turns paragraphs into emotions.
Open to full-time roles and freelance in ML Engineering and Full Stack Development.