Section · Students

Working with students.

Research opportunities & mentorship.

Looking for motivated students interested in software engineering research and applications. Join our team to explore code analysis, testing, and software quality.

Research topics

Ten research lines that collectively capture my research interests — strong empirical methodology, deep roots in code analysis and clone detection, and an expanding frontier into AI-generated code quality and LLM trustworthiness. Pick a line, or bring your own.

  • Code Clone Detection and Code Similarity

    Scalable clone search, clone configuration as optimization, and how clones emerge in human–AI collaborative development.

    Siamese · IWSC · BigCloneBench
  • Coding Proficiency Assessment

    Apply CEFR-style proficiency frameworks to programming. Measure code quality across OSS, textbooks, and LLM output.

    pycefr · jscefr · PyGress
  • AI-Generated Code Analysis & Detection

    Detect, explain, and assess the quality, comprehensibility, and trustworthiness of code produced by LLMs.

    NPC · Autorepairability
  • Metamorphic Testing & LLM Trustworthiness

    Use software-testing principles as a rigorous lens for evaluating LLM behavior and in-context learning.

    PromptOps · NLDB
  • Mining Software Repositories & Empirical SE

    Large-scale analysis of software artifacts — Jupyter notebooks, Gitcoin issues, social-media signals around OSS projects.

    MSR · Sprint2Vec
  • Software Engineering Practice in Thailand

    Understand and improve SE adoption in the Thai industry — SMEs, knowledge transfer, and the lasting effects of remote work.

    EMSE '24 · JSS '26
  • Software Security & Dependency Management

    Vulnerability reporting on GitHub, SECURITY.md adoption, and visualizing transitive risk across dependency graphs.

    V-Achilles · SANER '25
  • Code Review Analysis

    What code review actually achieves — architectural impact, convention enforcement, and LLM-augmented review experiences.

    AILinkPreviewer · TSE
  • Software Engineering for Data Science (SE4DS)

    Bridge classical SE methodology with data-science workflows, with a focus on Jupyter Notebook practices.

    Typhon · Notebooks
  • Technical Debt & SATD

    Automate detection, classification, and management of (self-admitted) technical debt across codebases.

    FixMe · ASE '21

What you'll get

  • Publish. Top SE venues — ICSE, FSE, ASE, ICSME, MSR, EMSE, TSE.
  • Collaborate. Active joint work with UCL, NAIST, Osaka, UECE, JAIST.
  • Mentor. Regular 1:1 supervision and a supportive lab culture.
  • Travel. Conference presentations and research visits abroad.

How to apply

Send a short email — no formal template needed. Include:

  • Your background, level, and timeline
  • Why software engineering — and which topic(s) above interest you
  • Any relevant projects, code, or papers