Co-founder and Chief Scientific Officer at SuperMatics, accelerating superconductor R&D with quantum-mechanical simulation, machine learning and real laboratory data. Berkeley, California.
- Superconductor materials R&D: choosing materials and synthesis experiments with simulation, ML and measured data.
- Quantum hardware and cryogenics: dilution-refrigerator systems, heat budgets and thermal models for superconducting processors (previously at Rigetti Computing).
- Scientific software: Python, Rust and PyTorch for experimental data analysis and anomaly detection (previously at Berkeley Lab).
Small, reproducible fixes to the scientific tools I depend on: scientific plotting, numerical and dataframe libraries, and materials and simulation tooling. This table is regenerated daily from my public pull requests on other people's repositories.
- Start from issues a maintainer has already accepted, and check nobody else is on them.
- Reproduce first. Add a test that fails without the fix, then make the smallest change that passes it.
- Show before and after evidence, run the project's own checks, and report honestly which ones fail and why.
- I use AI coding tools for research and drafting. I review every change myself and disclose AI assistance in each pull request, following each project's policy.