Engineer and business consultant in the energy sector, working at the intersection of industrial decarbonization, clean hydrogen and AI for materials discovery. My background is in electrochemistry (MSc thesis on electrodeposited catalysts for the hydrogen evolution reaction), and I now build ML and agentic tools that speed up R&D for low-carbon technologies, from catalyst screening to closed-loop optimization.
- ⚡ Specialized in electrochemistry, green hydrogen and catalyst discovery & optimization
- 🤖 Building local-first agentic AI: RAG, evals, memory, MCP and prompt/context engineering
- 🎯 Goal-driven generalist who enjoys collaborative teams and creative solutions to hard problems
- 🌍 Here to contribute to the green transition
| Project | What it does |
|---|---|
| 🧪 catalyst-kg-agent | Knowledge-graph-grounded, cost-aware multi-agent system for green hydrogen catalyst screening on Materials Project data. Uses MACE & CGCNN surrogates, Bayesian optimization, pydantic-ai agents and MLflow tracking. |
| 🧠 notion-second-brain | Fully local RAG agent over my Notion workspace. Hybrid dense + sparse retrieval, cross-encoder reranking, Qdrant, quantized Ollama models and an eval harness with anchored rubrics. |
Languages
Data Science & ML
Materials Informatics
Bayesian Optimization
AI / LLMs & Agents - Context & harness engineering · RAG pipelines · Evals · Agent memory · MCP, Skills & Prompt optimization
Databases
Tools & IDEs
