Applied AI researcher with a physics background.
Selected Work
- Estimation of Nitrogen Concentrations in Single Crystal Diamonds — Spectroscopic characterisation and defect modelling — 2025
- RAG by a Thousand Metrics — Retrieval-augmented generation evaluation — 2025
- The Dense Fog of RAG — Navigating dense retrieval blind spots — 2024
Recent Writing
Writing coming soon.
Jordan Moshcovitis is an applied AI researcher and engineer based in San Francisco and Melbourne. His work spans retrieval-augmented generation, agentic LLM systems, and robust evaluation methodology. Before moving into AI, he studied physics at the University of Melbourne, with research in computational materials science and diamond spectroscopy.
MSc Physics, University of Melbourne. BSc (Hons) Physics, University of Melbourne. Diploma in Mathematical Sciences.