About Me

I am an Assistant Professor at the Data Science and Analytics Thrust（数据科学与分析学域）, Information Hub （信息枢纽）, The Hong Kong University of Science and Technology (Guangzhou). Prior to this, I received my Ph.D. from the University of Waterloo. I extend my sincere gratitude to my great supervisor, Prof. Weiyi Shang, and my esteemed committee members: Prof. Shane McIntosh, Prof. Derek Rayside, Prof. Ladan Tahvildari, and Prof. Alexander Serebrenik. I received my B.Eng. degree in software engineering from Beijing University of Posts and Telecommunications. From June 2023 to September 2023, I was a visiting researcher of Prof. Federica Sarro in University College London (UCL).

My research primarily focuses on leveraging intelligent approaches (e.g., ML/DL/LLMs) to enhance various software engineering tasks. Specifically, my interests are twofold: 1) Optimizing natural language processing techniques for software engineering and 2) Software performance engineering for large-scale systems.

Selected Publications

• Towards a Robust Waiting Strategy for Web GUI Testing for an Industrial Software System
  Haonan Zhang, Lizhi Liao, Zishuo Ding, Weiyi Shang, Nidhi Narula, Catalin Sporea, Andrei Toma and Sarah Sajedi
  The 39th IEEE/ACM International Conference on Automated Software Engineering, Industry Showcase (ASE 2024 - Industry Showcase Track)
• 🏆 GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generation
  Jingzhi Gong, Sisi Li, Giordano d’Aloisio, Zishuo Ding, Ye Yulong, William Langdon, Federica Sarro
  Symposium on Search-Based Software Engineering (SSBSE 2024 - Challenge Track Winner)
• StableYolo: Optimizing Image Generation for Large Language Models
  Harel Berger, Aidan Dakhama, Zishuo Ding, Karine Even-Mendoza, David Kelly, Hector D. Menendez, Rebecca Moussa, Federica Sarro
  Symposium on Search-Based Software Engineering (SSBSE 2023 - Challenge Track)
• LoGenText-Plus: Improving Neural Machine Translation-based Logging Texts Generation with Syntactic Templates
  Zishuo Ding, Yiming Tang, Xiaoyu Cheng, Heng Li, Weiyi Shang
  ACM Transactions on Software Engineering and Methodology (TOSEM)
• CoMSA: A modeling driven sampling approach for configuration performance testing
  Yuanjie Xia, Zishuo Ding*, Weiyi Shang
  The 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023)
• IoPV: On Inconsistent Option Performance Variations
  Jinfu Chen, Zishuo Ding, Yiming Tang, Mohammed Sayagh, Heng Li, Bram Adams, Weiyi Shang
  The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2023)
• On the Temporal Relations between Logging and Code
  Zishuo Ding, Yiming Tang, Yang Li, Heng Li, Weiyi Shang
  The 45th International Conference on Software Engineering (ICSE 2023)
• Towards Utilizing Natural Language Processing Techniques to Assist in Software Engineering Tasks
  Zishuo Ding
  The 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion 2023)
• Towards Learning Generalizable Code Embeddings using Task-agnostic Graph Convolutional Networks
  Zishuo Ding, Heng Li, Weiyi Shang, Tse-Hsun Peter Chen
  ACM Transactions on Software Engineering and Methodology (TOSEM)
• LoGenText: Automatically Generating Logging Texts Using Neural Machine Translation
  Zishuo Ding, Heng Li, Weiyi Shang
  The 29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022)
• Can pre-trained code embeddings improve model performance? Revisiting the use of code embeddings in software engineering tasks
  Zishuo Ding, Heng Li, Weiyi Shang, Tse-Hsun Peter Chen
  Empirical Software Engineering (EMSE)
• 🏆 Towards the Use of the Readily Available Tests from the Release Pipeline as Performance Tests. Are We There Yet?
  ACM SIGSOFT Distinguished Paper Award
  Zishuo Ding, Jinfu Chen, Weiyi Shang
  The 42nd International Conference on Software Engineering (ICSE 2020)
(*: corresponding authors)

Honors and Awards

• ACM SIGSOFT Distinguished Paper Award, The 42nd International Conference on Software Engineering (ICSE 2020)
• SSBSE 2024 Challenge Track Winner
• Faculty of Engineering Graduate Scholarship, University of Waterloo
• Centre for Pattern Recognition and Machine Intelligence Graduate Scholarship, Concordia University
• Carolyn and Brian Neysmith Graduate Scholarship, Concordia University
• Dr. T. Radhakrishnan In-Course Graduate Bursary in Computer Science, Concordia University
• ACM SIGSOFT CAPS Travel Awards, ICSE 2020, FSE 2022, ICSE 2023, ASE 2023, FSE 2023

Academic Services

• Program committee member: ASE 2024 (Research Track), ASE 2023 (Research Track, Session Chair), MSR 2024 (Junior PC), AIWare 2024 (Challenge Track), ICPE 2024 (Data Challenge Track)
• Journal Reviewer: TOSEM, EMSE, JSS, ASE, STVR

Education

• Ph.D. in Electrical and Computer Engineering (ECE), University of Waterloo, 2024
• M.A.Sc. in Software Engineering, Concordia University, 2019
• B.Eng. in Software Engineering, Beijing University of Posts and Telecommunications, 2015

Invited Talks

• 2021.07, Shenzhen University, China, Towards the Use of the Readily Available Tests from the Release Pipeline as Performance Tests,
• 2021.05, Wind River, Canada, Towards the Use of the Readily Available Tests from the Release Pipeline as Performance Tests. From Research to Industry