PhD Candidate @ UniMelb

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Hi, I am Thanh Le-Cong (Lê Công Thành in Vietnamese).

I am a third-year Ph.D. student at CIS, The University of Melbourne, working with Dr. Bach Le and Prof. Toby Murray. Before joining UniMelb, I worked as a research engineer at Singapore Management University, working with Prof. David Lo. I was also an PhD intern of at Amazon Web Services and a visiting PhD student with Prof. Cristian Cadar and Prof. Michael Pradel at CISPA Helmholtz Center for Information Security.

My research aims to build trustworthy AI-powered solutions for developing reliable and secure software systems. To achieve this goal, I am mainly working on two orthogonal research directions:

Understanding and improving the trustworthiness of AI techniques for code synthesis and analysis, especially large language models for code.
Developing AI-driven techniques for automated software debugging, particularly focusing on bug detection and repair.

My research has been supported by Melbourne Research Scholarship, Google PhD Fellowship and published at premium venues of software engineering (ICSE, FSE, ASE, TOSEM, TSE) and natural language processing (ACL).

Recent Posts

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PhD Completion Seminar

I’m thrilled to share that after three incredible years at The University of Melbourne, I have presented my PhD completion seminar! 🎓 This has been a journey of massive growth. Thank you to my supervisors, Dr. Bach Le and Prof. Toby Murray, for being not just mentors but true role models. And to my family and friends–thank you for keeping me grounded and celebrating the small wins. I’m really excited for what comes next!

Nov 18, 2025

Invited Talk at SUTD

Last week, I’m honored to be giving my talk ‘From Smart Tools to Trusted Teammates: Towards Trustworthy Automatic Programming’ at the Singapore University of Technology and Design (SUTD). Thank you to faculty and staff members of SUTD for this incredible opportunity and your generous hospitality. It’s a privilege to share my latest work and learn from yours during my visit.

Nov 7, 2025

Accepted Paper by ICSE 2026

I am excited to share that FLAMES has been accepted by Research Track of ICSE 2026. FLAMES is a memory-efficient LLM-based APR with semantic-guided patch generation. If you are interested in FLAMES, please read our pre-print and explore the tool.

Oct 16, 2025

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