Zhe Zhou (周喆)

LWSN 3133 (#55) · Purdue University, West Lafayette, IN 47907 · zhou956@purdue.edu

I am a postdoctoral researcher at Purdue University, working with Prof. Suresh Jagannathan. I received my Ph.D. in Computer Science from Purdue University, where I was advised by Prof. Suresh Jagannathan and Prof. Benjamin Delaware. Prior to my doctoral studies, I worked as a full-time software engineer at Megvii (Face++) from 2017 to 2018. I earned my bachelor's degree from Peking University in 2017, where I was advised by Prof. Guangyu Sun.

My research interests are in programming languages (PL), with a particular focus on automated program verification and synthesis, property-based testing, and refinement types. My work aims to advance automated program verification and testing tools along three dimensions: increasing expressiveness, providing stronger guarantees, and reducing the need for expert intervention. I am also interested in the intersection of machine learning (ML) and PL—both applying ML techniques to PL problems and using PL insights to enhance ML.

Here is my CV.

Publications

We’ve Got You Covered: Type-Guided Repair of Incomplete Input Generators

Patrick LaFontaine, Zhe Zhou, Ashish Misra, Suresh Jagannathan, and Benjamin Delaware

ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2025)

(full version) (artifact)

Derivative-Guided Symbolic Execution

Yongwei Yuan, Zhe Zhou, Julia Belyakova, and Suresh Jagannathan

Proceedings of the ACM on Programming Languages (POPL 2025)

(doi) (full version) (artifact)

A HAT Trick: Automatically Verifying Representation Invariants Using Symbolic Finite Automata

Zhe Zhou, Qianchuan Ye, Benjamin Delaware, and Suresh Jagannathan

ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2024)

(doi) (draft) (full version) (artifact)

Covering All the Bases: Type-Based Verification of Test Input Generators

Zhe Zhou, Ashish Mishra, Benjamin Delaware, and Suresh Jagannathan

ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2023)

(Distinguished Paper Award) (doi) (draft) (full version) (artifact)

Data-Driven Abductive Inference of Library Specifications

Zhe Zhou, Robert Dickerson, Benjamin Delaware, and Suresh Jagannathan

ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2021)

(Distinguished Artifact Award) (doi) (full version) (artifact) (talk)