Thanh Le-Cong

Research

Our research focuses on trustworthy automated programming — building reliable and secure software systems through AI. We work at the intersection of software engineering and artificial intelligence, combining formal reasoning with modern machine learning techniques to make software development safer and more productive.

Research Areas

Trustworthy LLMs for Code

Evaluating and improving the reliability, security, and correctness of large language models used for code synthesis and analysis.

LLMscode generationmembership inferenceevaluation

Automated Program Repair

Developing AI-driven techniques for automated bug detection and repair, including patch correctness assessment and fault localization.

program repairpatch correctnessfault localization

Software Security

Analyzing vulnerabilities in modern software systems, including vulnerability-fixing commit classification and security testing.

vulnerability detectionsecurity testingbackdoor detection

Software Engineering for AI

Applying software engineering principles to improve AI systems — testing, debugging, and formal verification of ML models.

formal specificationML testingrobustness evaluation