Beiqi Zhang
Beiqi Zhang
Beiqi received Bachelor’s and Master’s degrees from Wuhan University, Wuhan, China.
During her research career, she has been actively involved in the Software Engineering (SE) research community, with a background exploring the intersection of AI and SE.
Currently, her research focuses on Trustworthy AI and Automated Software Engineering, with a special emphasis on the quality of LLM-generated code.
Supervisors
Prof John Grundy, Dr Xiaoning Du, Dr Kla Tantithamthavorn, Dr Tingting Bi
Publications
Beiqi Zhang, Tianyang Liu, Peng Liang, Chong Wang, Mojtaba Shahin, Jiaxin Yu. Architecture Decisions in AI-based Systems Development: An Empirical Study. In Proceedings of the 30th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Macao, China, pp. 616-626, 2023
Beiqi Zhang, Peng Liang, Xiyu Zhou, Aakash Ahmad, Muhammad Waseem. Practices and Challenges of Using GitHub Copilot: An Empirical Study. In Proceedings of the 35th International Conference on Software Engineering and Knowledge Engineering (SEKE), South San Francisco, USA, pp. 124-129, 2023 (Best Paper Award: First Place)
Beiqi Zhang, Peng Liang, Qiong Feng, Yujia Fu, Zengyang Li. Copilot-in-the-Loop: Fixing Code Smells in Copilot-Generated Python Code using Copilot. In Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering (ASE), The New Ideas and Emerging Results Track, Sacramento, California, 2024
Connect
Email: beiqi.zhang@monash.edu
Personal Website: https://beiqi-zhang.github.io
LinkedIn: https://www.linkedin.com/in/beiqi-zhang-056278394
Google Scholar: https://scholar.google.com/citations?user=6u6BLrQAAAAJ&hl=en