insideLLMs is a Python library and CLI for comparing LLM behaviour across models using shared probes and datasets. The harness is deterministic by design, so you can store run artefacts and reliably diff behaviour in CI.
Multi‑agent AI security testing framework that orchestrates red‑team analyses, consolidates findings with an arbiter, and records an immutable audit ledger—plus a deterministic demo mode for repeatable results.
Context engineering toolkit for LLMs — pack, cache, debug, red-team, and orchestrate context windows. Council of Experts, adversarial testing, immune system, context compiler, drift detection, multi-agent entanglement. TypeScript + Python.
Professional open-source platform for statistical mineral prospectivity mapping (MPM) in Western Australia. Enterprise-grade features: provenance, uncertainty, CV, CLI, QGIS, 2.5D depth, ML explainability, sensitivity analysis, project
PhD in Cognitive Neuroscience & AI · 15+ years in human-centred AI · 14 publications · h-index 12 · Learning · Unlearning · Intelligence · Behavioural Control · Latent Measuremnent · 40/30/30 Applied/Academic/Managerial
Hyperpriors · Culture Amp · NEOS Life Insurance · Source Localisation · Woolcock Institute of Medical Research · University of Sydney · Murdoch University · University of Cambridge University of Western Australia