A one-day roundtable bringing together leaders from industry and academia to discuss the current capabilities, limitations, and evaluation of AI for software engineering, with a particular focus on trustworthiness.
The goal is to develop a shared understanding of trustworthy AI for code, including open technical challenges, evaluation criteria, and concrete opportunities for collaboration across research and practice.
Identify the most important unsolved problems and align on high-impact research directions.
Discuss meaningful criteria for trustworthiness, usefulness, and deployment readiness.
Lay the groundwork for an ongoing forum and potential joint publication on this topic.
The roundtable is co-organized by researchers at Columbia University and the National University of Singapore with deep expertise in software engineering and AI reliability.
Professor, National University of Singapore
School of Computing
Associate Professor, Columbia University
Dept. of Computer Science
Participants come from leading universities and technology companies working on AI for software engineering.
Individual participant list will be updated as confirmations are finalized.
The first edition of this roundtable (Singapore, January 2026) brought together more than 30 leaders from industry and academia to discuss trustworthy AI for code.