Beiqi Zhang
Ph.D. Student at Monash University
Room 223, 20 Exhibition Walk
Clayton, VIC 3800, Australia
I am a Ph.D. student (2025-) in Information Technology at Monash University, where I am fortunate to be advised by Prof. John Grundy, Dr. Xiaoning Du, Dr. Kla Tantithamthavorn, and Dr. Tingting Bi (External Supervisor).
My research focuses on Trustworthy AI and Automated Software Engineering, with a particular emphasis on autonomous code agents and the quality assurance of LLM-generated code. I am passionate about exploring how to enhance the security, reliability, and robustness of these agentic systems through rigorous scientific benchmarking and methodological innovation.
Prior to my Ph.D. journey, I earned my Bachelor’s (2018-2022) and Master’s (2022-2025) degrees from Wuhan University, where I was a member of CSTAR (Centre of Software Testing, Analysis, and Reliability) and supervised by Prof. Peng Liang. I have been deeply involved in research projects exploring the intersection of Software Engineering and Artificial Intelligence.
I am always open to academic collaborations and discussions with researchers and students who are passionate about Trustworthy AI, AI4SE & SE4AI, and Automated Software Engineering. If you share these research interests, please feel free to reach out for potential collaboration!
News
| Mar 27, 2026 | 📄 Great news! My first-author paper on PEFT for code smell detection has been accepted by ACM TOSEM. This is a collaborative work with Prof. David Lo, started during my visit to SMU in 2024. |
|---|---|
| Nov 28, 2025 | 🎉 I arrived in Melbourne, Australia, and started my Ph.D. journey at Monash University! |
| Jul 1, 2024 | 🇸🇬 From July to December 2024, I was a visiting student at Singapore Management University (SMU), supervised by Prof. David Lo. |
Selected Publications [view all]
2026
- TOSEMA Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Code Smell DetectionACM Transactions on Software Engineering and Methodology, 2026
2025
- TOSEMUsing LLMs in generating design rationale for software architecture decisionsACM Transactions on Software Engineering and Methodology, 2025
2024
- ASECopilot-in-the-loop: Fixing code smells in copilot-generated python code using copilotIn Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, 2024
2023
- SEKEPractices and challenges of using github copilot: An empirical studyIn Proceedings of the 35th International Conference on Software Engineering and Knowledge Engineering, 2023🏆 Best Paper Award: First Place
Services
Invited Reviewer
- TOSEM