Hong Jin Kang

Hong Jin Kang is a Lecturer in the School of Computer Science at The University of Sydney. His research focuses on improving developer productivity through human-centric AI tools, particularly in Active Learning and AI-driven Software Engineering. Prior roles include postdoctoral fellowships at UCLA and a PhD at Singapore Management University (SMU), advised by Prof. David Lo. His work spans vulnerability detection, program transformation, and software supply chain security, with practical industry impact through CVE discoveries and deployed techniques.

Education:

• PhD in Computer Science, Singapore Management University (2023)
• Postdoctoral Research, University of California, Los Angeles (UCLA)

Research Interests:

• Active Learning for code analysis and vulnerability management
• AI and ML integration into software development tools
• Cybersecurity in software supply chains
• Program transformation and legacy code modernization

His publications address challenges in automated tool development, including vulnerability identification (e.g., CHRONOS), code model compression, and adversarial specification mining. Recent work emphasizes sustainability in AI and human-in-the-loop systems.

Awards:

• Distinguished Reviewer Award for ICSE 2025

Advising & Grants:

Actively mentoring PhD students in software engineering and AI, with a focus on curiosity-driven candidates. His research is supported by collaborations with industry and academic institutions.

Labs/Teams:

Pioneers tools like Coccinelle4J for Java program transformation and collaborates on projects such as VulCurator and HERMES for vulnerability analysis.