Yiran Wang

Yiran Wang, Ph.D. student, Linköping University

yiran.wang@liu.se

Education

  • 2023.2 – now
    Ph.D. Linköping University in Sweden.

    Thesis: Early bug detection and resolution for machine learning programs.

  • 2020.8 – 2022.6
    M.Sc. Statistics and Machine Learning, Linköping University in Sweden.

    Thesis: Multivariate time series prediction, a first step to fault prediction of the CI servers.

  • 2009.9 – 2013.7
    B.Eng. Digital Media Technology, BLCU in Beijing, China.

    Thesis project: Stop motion "Super M".

Employment

  • 2022.9 – 2023.2
    Research assistant, Linköping University (Campus US), Sweden.
  • 2022.1 – 2022.6
    Master thesis student, Veoneer, Linkoping, Sweden.
  • 2017.7 – 2020.8
    Game developer, Perfect world entertainment, Beijing, China.
  • 2013.7 – 2017.5
    Product manager, Fun Plus Game, Beijing, China.

Research Publications

  1. Yiran Wang, Jakob Hoffmann, Jürgen Cito, and Dániel Varró. 2026. Beyond Crash Resolution: Evaluating LLM Agents for Repairing Machine Learning Notebooks. Submitted.
  2. Yiran Wang, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2026. CRANE-LLM: Runtime-Augmented LLMs for Crash Prediction and Diagnosis in ML Notebooks. Accepted to SCAM2026. arXiv: 2602.18537
  3. Yiran Wang, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2026. JunoBench: A Benchmark Dataset of Crashes in Python Machine Learning Jupyter Notebooks. In Proceedings of the 3rd ACM International Conference on AI-Powered Software (AIware '26), Montreal, QC, Canada, pp. 406–413. doi: 10.1145/3805760.3814934
  4. Yiran Wang, Willem Meijer, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2025. Why Do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks. IEEE Transactions on Software Engineering, vol. 51, no. 7, pp. 2181–2196. doi: 10.1109/TSE.2025.3574500
  5. Yiran Wang, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2024. Using Run-Time Information to Enhance Static Analysis of Machine Learning Code in Notebooks. In Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering (FSE 2024), Porto de Galinhas, Brazil, pp. 497–501. CORE rank: A*. doi: 10.1145/3663529.3663785
  6. Yiran Wang. 2023. Early Detection of Defects in Machine Learning Programs by Semi-Static Analysis. Accepted for presentation at Doctoral Forum at the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE'23), Luxembourg, 11-15 September, 2023. doi: 10.5281/zenodo.20793551

Projects

  • 2023.2 – now
    WASP (Wallenberg AI, Autonomous Systems and Software Program) Graduate School, Sweden.
  • 2023.2 – now
    Software Center (Project 61), Sweden.

Talks

  • 2026.4
    Quality Assurance for ML Software, presented and hosted Software Center online workshop together with Dániel Varró, Kristian Sandahl, and Willem Meijer in Linköping, Sweden.
  • 2025.11
    Why do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks, ASE Conference 2025 in Seoul, South Korea.
  • 2025.1
    Why ML notebooks Crash, WASP Software Engineering Technology Cluster meeting in Norrköping, Sweden.
  • 2024.12
    Why ML Code Crashes and What We Are Going to Do About It, Software Center Reporting Workshop in Gothenburg, Sweden.
  • 2024.7
    Using Run-Time Information to Enhance Static Analysis of Machine Learning Code in Notebooks, FSE Conference 2024 in Porto de Galinhas, Brazil.
  • 2024.5
    An Empirical Study of ML Bugs in Notebooks, Software Center online workshop.
  • 2024.5
    Using Run-Time Information to Enhance Static Analysis of Machine Learning Code in Notebooks, WASP Software Engineering Technology Cluster Workshop in Linköping, Sweden.
  • 2024.1
    Using Run-time Information in Static Analysis for ML Bug Detection, Software Center Ericsson Workshop in Linköping, Sweden.
  • 2023.12
    Early Detection of Defects in Machine Learning Programs by Semi-Static Analysis, Software Center Reporting Workshop in Gothenburg, Sweden.
  • 2023.9
    Early Detection of Defects in Machine Learning Programs by Semi-Static Analysis, ASE 2023 Doctoral Forum in Luxemburg.
  • 2023.3
    Quality Assurance of ML Programs, Software Center online workshop.

International Activities

  • 2026.1 – 4
    Research visit to TU Wien, Vienna, Austria.
  • 2024.9
    WASP study trip, Germany.
  • 2024.9
    Summer school on security testing and verification at the VUB, Brussels, Belgium.
  • 2023.9
    WASP study trip, Boston, US.

Academic Service

  • 2025.12
    PC member, MSR'26 Mining Challenge track.
  • 2025.11
    Junior PC member, MSR'26, received Best Reviewer Award.
  • 2025.11
    Subreviewer, FASE'26.
  • 2025.5 – 2026
    Reviewer, Elsevier Journal of Systems and Software.