Sankalp Gilda is a Staff ML Engineer and independent researcher focused on epistemic accountability and structured reasoning for AI-assisted workflows in regulated and high-stakes domains. He holds a PhD in Astronomy and has six-plus years of production data science experience spanning time-series analysis, uncertainty quantification, and MLOps -- most recently driving AI for electric-vehicle systems in greentech as well as in oil and gas.

He created tsbootstrap, an open-source Python library for bootstrapped time-series resampling (87+ stars, sktime-integrated), and gave its tutorial at SciPy 2024. His other public OSS spans the security and developer-safety ecosystem -- idna-ip-literal-smuggle-rules, a CodeQL/Semgrep ruleset and gopatch auto-fix codemod for a Go IDNA-canonicalization bug class (UTS-46 digit-fold IP-literal smuggling) he privately disclosed to the Go team in April 2026, and mcp-keyring-injector for session-scoped credential safety in MCP environments. Recent research includes workshop papers at ICLR 2026 -- Logical Reasoning of LLMs (algebraic invariants for LLM reasoning chains and weakest-link reliability propagation) and AI in Finance (epistemic accountability and generator-ratifier disjointness for agentic financial AI). He builds Verity, a reasoning-layer system for AI coding assistants in regulated environments, currently in private development.

Outside work he's drawn to high-commitment activities -- skydiving, scuba diving, kitesurfing -- that reward the same combination of careful preparation and decisive action that good engineering does. He consults across industries through DeepThought Solutions on AI governance, structured reasoning, and ML-for-regulated-domains problems.