OpenVerifiableLLM maintainer · GSoC 2026 @ AOSSIE
Master of Computer Science student · University of Sydney
I build tools for verifiable training and autonomous research.
I care about the evidence behind a result: where the data came from, how the system ran, and whether someone else can reproduce it.
Language-model training that people can inspect and check. My work focuses on deterministic execution, data provenance, checkpoint verification, and reproducible releases.
The project reproduced all 37 training segments bit for bit on a second RTX 5090. These checks cover the training computation on matching GPU hardware.
Source code ↗ · Method and results ↗ · My contributions ↗
- Autonomous research. Agents that choose useful experiments, run them, and retain the evidence.
- Reliable execution. Observable runs, controlled actions, and recovery from failure.
- Complex systems. Emergence, information flow, and artificial life.
Small experiments. Clear failure records. Results others can reproduce.
Outside code, I write speculative fiction and read fantasy manhwa.



