Jialu Zhang

Jialu Zhang

Tenure-Track Assistant Professor

University of Waterloo


I am an Assistant Professor at Waterloo ECE. I obtained my CS PhD from Yale in 2023, advised by Ruzica Piskac. Previously, I worked at the RiSE and PROSE team at Microsoft Research (MSR), collaborating with Shuvendu Lahiri, Sumit Gulwani, Jose Cambronero, Todd Mytkowicz and Vu Le. I coached the Yale ICPC Team.

I am looking for 3+ highly self-motivated Master, PhD, and remote interns. If you are excited about LLM/PL/SE research, send me an email to initiate exciting projects together!

!! NEWS !! PyDex to appear at OOPSLA 2024! For the first time, a fully automated tool to repair both syntactic and semantic errors in real-world students’ Python programming assignments.

My research combines Large Language Models (LLM), Programming Languages and Software Engineering to develop practical tools for automatically preventing, detecting, and repairing crucial errors in programs, with minimum to no human effort. Check it out:

  • Clef (ASE 2022) : first paper in the PL/SE community on competitive programming, able to automatically repair very interesting and challenging competitive-level programs.

  • Gmerge (ISSTA 2022) : using GPT-3, automatically resolved 300+ real-world merge conflicts in Microsoft Edge (currently under productization).

  • ConfigX (OOPSLA 2021) : analyzing the semantics of system source code using customized static analysis, detected 2233 real silent misconfigurations in Apache, VSFTPD and PostgreSQL.

  • Machine-Aided Programming
  • Automated Feedback Generation for CS Education
  • Programming Languages
  • Software Engineering
  • PhD in Computer Science, 2023

    Yale University

  • BS in Electrical and Computer Engineering (IEEE Honor Class), 2017

    Shanghai Jiao Tong University

Recent Publications

(2024). Repairing Bugs in Introductory Python Assignments Using Large Language Models. To appear at OOPSLA 2024.

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(2022). Automated Feedback Generation for Competition-Level Code. In ASE 2022.

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(2022). Using pre-trained language models to resolve textual and semantic merge conflicts (experience paper). In ISSTA 2022.

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(2022). Static Detection of Silent Misconfigurations with Deep Interaction Analysis. In OOPSLA 2021.

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(2022). Learning CI Configuration Correctness for Early Build Feedback. In SANER 2022.

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(2020). Succinct Explanations with Cascading Decision Trees. In Submission.

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