Marco Gario is a Research Engineer with 14 years of experience at the intersection of formal methods, reliable AI, and software engineering, having led architecture and research efforts for Siemens, GitHub (working on CodeQL), and now XBOW. He brings a rare blend of academic depth—a PhD in Formal Methods applied to fault detection and temporal epistemic logic—and hands-on engineering, contributing to high-impact open-source tooling for code analysis. Marco has delivered results on publicly funded programs (DARPA, NASA, ESA) and translated formal verification techniques into production-ready developer tools and DevOps integrations. Curious and solution-oriented, he thrives on tackling problems that span infinite-state formal reasoning to scalable backend and build systems. An often-overlooked strength is his ability to bridge interdisciplinary audiences: he communicates complex verification results to engineers, product teams, and non-technical stakeholders alike.
15 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Formal Methods and Diagnosis, Doctor of Philosophy (Ph.D.) Formal Methods and Diagnosis at Università di Trento
Master's Degree Computer Science - Computational Logic, Master's Degree Computer Science - Computational Logic at Technische Universität Dresden
Master's Degree Computer Science - Computational Logic, Master's Degree Computer Science - Computational Logic at Free University of Bozen-Bolzano
Bachelor's Degree Computer Engineering, Bachelor's Degree Computer Engineering at Politecnico di Torino
Contributions:1 release, 53 reviews, 58 commits in 2 years 6 months
Contributions summary:Marco primarily contributed to the project's backend infrastructure and build processes. Their commits demonstrate modifications to the build system, platform-specific configurations, and updates to core libraries. They were responsible for integrating platform-specific bundle and refining the process of bundling the code scanning tools. Furthermore, the user added checks and preferences in the codebase.
pySMT: A library for SMT formulae manipulation and solving
Contributions:20 releases, 60 reviews, 838 commits in 7 years 9 months
manipulationformulaepythonsolvingsmt
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