I build AI systems, secure data pipelines, and self-hosted infrastructure.
Currently focused on:
- π§ LLM systems: RAG, local inference, multimodal AI
- π Privacy & security: PHI redaction, audit logging, safe AI
- βοΈ Backend & infrastructure: FastAPI, Docker, Proxmox, Linux networking
- π Full-stack apps: React, TypeScript, API-driven systems
An end-to-end system for querying synthetic patient records with a local LLM while enforcing privacy and security controls.
Planned components:
- FHIR-based synthetic data (OpenEMR + Synthea)
- PHI detection & redaction (Microsoft Presidio)
- Vector search (Qdrant / Chroma)
- Local LLM inference (Ollama / llama.cpp)
- FastAPI gateway with:
- prompt injection protection
- output filtering
- rate limiting
- audit logging
- Self-hosted AI + security lab (Proxmox, VLANs, DNS, monitoring)
- Backend services with FastAPI (auth, logging, system design)
- Frontend apps with React + TypeScript (Refine, MUI)
- Earlier data science and ML projects
Frontend
- React, TypeScript
- MUI (Material UI), Refine
- Vite
Backend
- Python, FastAPI, Flask
- REST APIs, authentication, rate limiting
AI / ML
- LLMs (Ollama, llama.cpp)
- Embeddings, vector databases
- PyTorch, NLP
Data
- SQL, MySQL, Microsoft SQL Server
- Pandas, NumPy, R
Infrastructure
- Linux, Docker, Proxmox
- Networking, VLANs, DNS
- Git, Bash
Coming soon:
- Secure Clinical AI Inference Pipeline
- Self-hosted AI + Security Lab
- FastAPI Security Gateway
Older repositories reflect my earlier work in data science and analytics.