GitHub’s model for secret detection: Finding more secrets with less noise
GitHub’s context-aware secret classifier improves detection quality, raises weighted acceptance by 11.5%, and reduces median scan execution time by 86%.
As a Senior Research Scientist in Microsoft CoreAI, I develop agentic model orchestration and routing techniques for GitHub Copilot. My research focuses on adaptive model selection, multi-model coordination, long-horizon agentic workflows, and developer security.
GitHub’s context-aware secret classifier improves detection quality, raises weighted acceptance by 11.5%, and reduces median scan execution time by 86%.