Yuekang Li

Yuekang has developed testing techniques that helped open-source communities and companies find hundreds of bugs, including in widely used software such as Bitbucket. Research publications also address testing large language models for answers that conflict with facts. These contributions support software quality by exposing faults in existing products and investigating ways to assess newer systems.

Yuekang Li is an AI Research Engineer at Common Defense, having joined the organisation in January 2026 after serving as a Senior Lecturer in the School of Computer Science and Engineering at UNSW Sydney. Earlier career appointments include working as a Research Assistant Professor in the Continental-NTU laboratory at Nanyang Technological University, where Yuekang completed a bachelor’s degree in 2016 and a PhD in 2020.

Focusing on dynamic program analysis and automated fuzz testing to expose software faults, Yuekang developed testing techniques that have helped open-source communities and commercial organisations uncover hundreds of bugs in production systems, including Bitbucket. One fuzz testing tool also earned first award in the Search-Based Software Testing’23 competition.

Subsequent research extends to protocol fuzzing and the evaluation of machine learning systems, including methods to detect fact-conflicting answers in large language models. These projects connect core software testing principles with practical fault detection in emerging technologies.