About Me

I am currently a Postdoctoral Fellow at University of Waterloo. Prior to this, I received my Ph.D. from Software Analysis and Intelligence Lab (SAIL) at Queen’s University (Kingston, ON) under the supervision of Prof. Ahmed E. Hassan. I obtained my Master’s degree from Concordia University under the supervision of Prof. Weiyi Shang.

My research interests include empirical software engineering, software log management, log mining, performance engineering, and mining software repositories. Contact me at kundi.yao@uwaterloo.ca

Publications

• Finding associations between natural and computer languages: A case-study of bilingual LDA applied to the bleeping computer forum posts

  Kundi Yao, Gustavo A Oliva, Ahmed E Hassan, Muhammad Asaduzzaman, Andrew J. Malton, Andrew Walenstein

  Journal of Systems and Software (JSS)

• Improving state-of-the-art compression techniques for log management tools

  Kundi Yao, Mohammed Sayagh, Weiyi Shang, and Ahmed E. Hassan

  IEEE Transactions on Software Engineering (TSE)

• A study of the performance of general compressors on log files

  Kundi Yao, Heng Li, Weiyi Shang, Ahmed E. Hassan

  Empirical Software Engineering (EMSE)

• Log4Perf: Suggesting and updating logging locations for web-based systems’ performance monitoring

  Kundi Yao, Guilherme B. de Pádua, Weiyi Shang, Catalin Sporea, Andrei Toma, Sarah Sajedi

  Empirical Software Engineering (EMSE)

• Log4perf: Suggesting logging locations for web-based systems’ performance monitoring

  Kundi Yao, Guilherme B. de Pádua, Weiyi Shang, Catalin Sporea, Andrei Toma, Sarah Sajedi

  The 9th ACM/SPEC International Conference on Performance Engineering (ICPE 2018). Best paper nomination.

Teaching

Guest Lecturer at University of Waterloo

• Software Design and Architectures (2024 Fall)

  Title: Nonfunctional Requirements \& Twitter Design Excercise

Guest Lecturer at North Carolina State University

• Generative AI for Software Engineering (GAI4SE) (2024 Fall)

  Title: Improving analytical capabilities and storage efficiencies of modern log management solutions

Teaching Assistant at Queen’s University

• CISC 326: Software/Game Architecture (2021 Winter)
• CISC 235: Data Structures (2021 Winter)
• CISC 351: Advanced Data Analytics (2020 Winter)
• CISC 102: Discrete Mathematics For Computing (2019 Winter)

Academic Services

• Program committee member: SANER 2025 (Tool Demo Track)
• Reviewer: ASE, SPE, ICPE, SANER

Educations

• Ph.D. in Software Engineering, Queen’s University, 2024
• M.A.Sc in Software Engineering, Concordia University, 2018
• B.Eng. in Internet of Things (IoT) Engineering, Wuhan University of Technology, 2015

Industrial experiences

• Research Collaborator (2024.04 - Now)

  Aptiv PLC (Remote)

  Topics: Large language model (LLM), Requirement Engineering

• Research Intern (2023.01 - 2023.08)

  Blackberry Ltd, Waterloo, ON, Canada

  Topics: Large language model (LLM), RAG-based Code Generation, Predictive Analytics, Personally Identifiable Information (PII) Detection

• Research Intern (2020.05 - 2020.08)

  Blackberry Ltd (Remote)

  Topics: Natural Lanugage Processing (NLP), Log Analysis

• Research Intern (2017.01 - 2018.08)

  ERA Environmental Management Solutions, Montreal, QC, Canada

  Topics: Performance Modeling, Performance Testing

Invited Talks

• Consortium for Software Engineering Research (CSER 2024), Kingston, Canada. Improving state-of-the-art compression techniques for log management tools
• Blackberry Ltd, Waterloo, Canada (2021). Log Compression Techniques: Evaluation of Compression Options and New Approach to Preprocessing for Improved Compression
• The 9th ACM/SPEC International Conference on Performance Engineering (ICPE 2018), Berlin, Gemany. Log4perf: Suggesting logging locations for web-based systems’ performance monitoring