Founder of DeepNeuro.dev. I design and ship agentic AI systems that combine LangChain orchestration, MCP tool integration, and RAG architectures with robust FastAPI backends and modern frontends. My work emphasizes reliability, observability, and scalability from prototype to production.
DeepNeuro.dev originated in healthcare AI, and I continue to draw on my neurobiology background. Today, I apply those foundations to broader applied AI problems across NLP, automation, analytics, and cloud-native applications—building multi-agent workflows, scalable RAG systems, and production-grade AI services.
Showcasing impactful AI/ML solutions in healthcare and beyond
Production-grade multi-agent system with RAG retrieval and contextual reasoning, featuring a Next.js chat UI and FastAPI backend.
End-to-end NLP microservice for real-time emotion classification with a React frontend and containerized cloud deployment.
Deep learning pipeline for medical imaging with interpretability—maintaining DeepNeuro’s healthcare roots.
TensorFlow, PyTorch, Keras, Neural Networks, CNNs, RNNs
Medical Imaging, DICOM, Bioinformatics, Clinical Data Analysis
Image Classification, Object Detection, Feature Engineering
Transformers, LangChain, RAG, Multi-Agent Workflows, MCP
Docker, Render, Vercel, Google Cloud Run, CI/CD
pandas, NumPy, scikit-learn, Statistical Analysis, Visualization
I'm currently open to opportunities in applied AI/ML, agentic systems, and platform engineering roles.