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Xin Zhang's Homepage
Assistant Professor | Co-Appointed Research Professor
Programming Languages Lab
Department of Computer Science and Technology
School of Electronics Engineering and Computer Science
Peking University
Programming Languages Lab
Department of Computer Science and Technology
School of Electronics Engineering and Computer Science
Peking University
Address: Room 1809, Science Building # 1, Peking University
E-mail: xin AT pku.edu.cn
E-mail: xin AT pku.edu.cn
Hello, I am Xin Zhang (pronunciation ≈ "shin chang"), an assistant professor at Peking University.
Before joining Peking, I was a postdoctoral associate at MIT CSAIL working with Prof. Armando Solar-Lezama.
I received my Ph.D. from Georgia Tech under the supervision of Prof. Mayur Naik.
I am broadly interested in topics related to programming languages and software engineering.
For details, please see Research.
Students
Ph.D.
- Zhenyu Yan
- Junhao Liu
- Yuanfeng Shi
- Tianchi Li
- Yifan Zhang
- Zhentao Ye (co-adivised with Yingfei Xiong)
- Haonan Yu
- Haoran Lin
- Haoyu Feng
- Zhiyi Li
- Zirui Zhou
- Ziyue Jin
- Yaoxuan Wu (Ph.D. Student@UCLA)
- Yifan Chen (co-adivised with Yingfei Xiong)
Teaching
- Introduction to Probabilistic Programming (Spring 2025)
- Introduction to Discrete Mathematics (Fall 2024)
News
Oct 2025
Two papers conditionally accepted at POPL'26.
Oct 2025
Two new papers at OOPSLA'25. One on how to combine informal information and formal information in program analysis. The other on how to apply CEGAR to find good representations for Bayesian program analyses.
Aug 2025
New paper at ASE'25 on how to exploit logical structures in constraints to accelerate probabilistic inference.
June 2025
New TSE paper on how to apply Bayesin reasoning to fault localization.
Dec 2024
New paper on adding temporal information to machine learning model explanations at AAAI'25.
June 2024
Two new papers at OOPSLA'24. One on how to combine graph neural networks and constraint solving to scale precise program analyses. The other on how to find good representations for program analyses based on Bayesian learning.
March 2022
I have two openings for Ph.D. students this year. If you're interested in topics related to program analysis, program synthesis, and reliable machine learning, please apply to our program and contact me!
Feb 2022
New paper on applying Bayesian methods to semantics-based fault localization at ICSE'22.
July 2021
New paper on accelerating static analyses at SAS'21.
May 2021
New paper on supporting causal inference in probabilistic programming at ICML'21.
Sep 1, 2020
Oct 1, 2019
New paper at OOPSLA'19 on scalable verification of algorithmic fairness.
Aug 15, 2019
I will serve on the external review committee of PLDI'20. Please consider submitting.
Feb 15, 2019
I will serve on the program committee of SAS'19. Please consider submitting.
Sep 4, 2018
Aug 8, 2018
I have been selected as a winner of the 2015-2016 Facebook Fellowship. Thank you, Facebook!