Xin Zhang

Registered user since Fri 26 Jun 2015

Name: Xin Zhang

Bio: Xin Zhang is an Assistant Professor at the Department of Computer Science and Technology, the School of Electronics Engineering and Computer Science, Peking University. While he is broadly interested in topics related to programming languages (PL) and software engineering (SE), his current focus is on program analysis and its interplay with machine learning (ML) and artificial intelligence (AI). On one hand, he leverages ideas from ML/AI to build better program analyses. On the other hand, he develops program analyses and languages for improving intepretability, fairness, robustness, and safety of ML/AI systems.

Country: China

Affiliation: Peking University

Personal website: http://xinpl.github.io/

Research interests: Programming Languages, Operating Systems, and Software Engineering

Contributions

PLDI 2021Committee Member in Program Committee within the PLDI Research Papers-track
PLDI 2020Committee Member in External Review Committee within the PLDI Research Papers-track
SPLASH 2019Author of Probabilistic Verification of Fairness Properties via Concentration within the OOPSLA-track
PLMW @ PLDI 2018Presenter of Poster Session within the PLMW @ PLDI 2018-track
VMCAI 2018Author of Maximum Satisfiability in Program Analysis: Applications and Techniques within the VMCAI 2018-track
MAPL 2017Author of Combining the Logical and the Probabilistic in Program Analysis within the MAPL 2017-track
PLDI 2018Session Chair of Synthesis and Learning (part of PLDI Research Papers)
Committee Member in Program Committee
SPLASH 2017Author of Effective Interactive Resolution of Static Analysis Alarms within the OOPSLA-track
PLDI 2017Committee Member in External Review Committee
SPLASH 2016Committee Member in Program Committee within the Posters-track
Programme Committee in Program Committee within the OOPSLA Artifacts-track
Author of Accelerating Program Analyses by Cross-Program Training within the OOPSLA-track
POPL 2016Author of Query-Guided Maximum Satisfiability within the Research Papers-track