CV

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Education

• Ph.D in Computer Science, the University of Melbourne, Jan 2023 – Nov 2026 (Expected)
  • Supervisors: A/Prof. Christoph Treude and Dr. Mansooreh Zahedi
  • Research Topic: Mitigating Knowledge Barriers in Traditional and AI-Based Software Development
• M.S. in Information Technology, the University of Melbourne, Feb 2021 – Dec 2022
  • WAM: 86.7/100
• B.S. in Mathematics and Applied Mathematics, Fuzhou University, Sep 2016 – July 2020
  • WAM: 86.6/100

Experience

• Visiting Postgraduate Research Student, Singapore Management University, Sep 2025 – Feb 2026
  • Visiting Professor: A/Prof. Christoph Treude
• Teaching Assistant, the University of Melbourne, Oct 2023 – Present
  • Tutored: COMP90041 Programming and Software Development; SWEN90017 Masters Advanced Software Project
  • Marked: COMP90041, SWEN90016 Software Processes and Management, COMP90049 Introduction to Machine Learning, COMP90051 Statistical Machine Learning
• Research Assistant, the University of Melbourne, Dec 2023 – May 2024
  • Skills: Mining software repositories, Qualitative analysis, Ethics in Machine Learning
• Machine Learning Intern, Haier Group Corporation, Oct 2021 – Feb 2022
  • Skills: Machine Learning, Data analysis

Publications

From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintained

Haoyu Gao, Jai Lal Lulla, Hong Yi Lin, Sebastian Baltes, Christoph Treude, and Mansooreh Zahedi. 2026. From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintained. arXiv:2607.00911.

On Autopilot? An Empirical Study of Human-AI Teaming and Review Practices in Open Source

Haoyu Gao, Peerachai Banyongrakkul, Hao Guan, Mansooreh Zahedi, and Christoph Treude. 2026. On Autopilot? An Empirical Study of Human-AI Teaming and Review Practices in Open Source. Short Paper in MSR 2026: 23rd International Conference on Mining Software Repositories.

When AI Models Become Dependencies: Studying the Evolution of Pre-Trained Model Reuse in Downstream Software Systems

Peerachai Banyongrakkul, Mansooreh Zahedi, Christoph Treude, Haoyu Gao, and Patanamon Thongtanunam. 2026. When AI Models Become Dependencies: Studying the Evolution of Pre-Trained Model Reuse in Downstream Software Systems. arXiv:2604.17940.

Fine-grained Approaches for Confidence Calibration of LLMs in Automated Code Revision

Hong Yi Lin, Chunhua Liu, Haoyu Gao, Patanamon Thongtanunam, and Christoph Treude. 2026. Fine-grained Approaches for Confidence Calibration of LLMs in Automated Code Revision. arXiv:2604.06723.

Does My README File Need To Be Updated? Exploring LLM-Based README Maintenance

Haoyu Gao, Hong Yi Lin, Christoph Treude, Gregory Gay, and Mansooreh Zahedi. 2026. Does My README File Need To Be Updated? Exploring LLM-Based README Maintenance. arXiv:2603.00489.

From Release to Adoption: Challenges in Reusing Pre-trained AI Models for Downstream Developers

Purit Banyongrakkul, Mansooreh Zahedi, Patanamon Thongtanunam, Christoph Treude, and Haoyu Gao. 2025. From Release to Adoption: Challenges in Reusing Pre-trained AI Models for Downstream Developers. In ICSME 2025: 41st International Conference on Software Maintenance and Evolution.

CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models

Huili Lin, Changlin Liu, Haoyu Gao, Patanamon Thongtanunam, and Christoph Treude. 2025. CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models. In Findings of ACL 2025: The 63rd Annual Meeting of the Association for Computational Linguistics.

AI Failures in the Eyes of the Downstream Developer: A First Look at Concerns, Practices, and Challenges

Haoyu Gao, Mansooreh Zahedi, Wenxin Jiang, Hong Yi Lin, James C. Davis, and Christoph Treude. 2025. AI Failures in the Eyes of the Downstream Developer: A First Look at Concerns, Practices, and Challenges. arXiv:2503.19444.

Adapting Installation Instructions in Rapidly Evolving Software Ecosystems

Haoyu Gao, Christoph Treude, and Mansooreh Zahedi. 2025. Adapting Installation Instructions in Rapidly Evolving Software Ecosystems. IEEE Transactions on Software Engineering.

Documenting Ethical Considerations in Open Source AI Models

Haoyu Gao, Mansooreh Zahedi, Christoph Treude, Sarita Rosenstock, and Marc Cheong. 2024. Documenting Ethical Considerations in Open Source AI Models. In ESEM 2024: 18th International Symposium on Empirical Software Engineering and Measurement.

Evaluating Transfer Learning for Simplifying GitHub READMEs

Haoyu Gao, Christoph Treude, and Mansooreh Zahedi. 2023. Evaluating Transfer Learning for Simplifying GitHub READMEs. In Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023). Association for Computing Machinery, New York, NY, USA, 1548–1560.

Services and Activities

Journal Review

• Automated Software Engineering Journal

Conference Review

• PC member for ICSME’26 Demo and Data Showcase Track
• PC member for ICSE’26 Artifact Evaluation Track
• Junior PC member for MSR’25

Sub-reviewer

• TOSEM, ICSE’25, ESEM’24, APSEC’24

Student Volunteer

• ICSE 2023 — International Conference on Software Engineering

(Co)-supervised Students

• Hao Guan — Master of Software Engineering, the University of Melbourne

Skills

• Programming: Python, Java, JavaScript, R
• Research: Data mining, Interview-based study, Qualitative analysis, Machine learning, HPC cluster
• Languages: Mandarin (Native), English (Full professional proficiency)

Awards and Scholarships

• Dean’s Honours List, the University of Melbourne, July 2023
  • Recognises outstanding academic performance, representing the top 5% of students in engineering or IT master programs.
• Melbourne Research Scholarship, the University of Melbourne, Jan 2023
  • Rewarded to high-achieving students participating in research activities.
• Melbourne Graduate Scholarship, the University of Melbourne, Jan 2022
  • Rewarded to coursework students in recognition of their academic achievements.