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.

Education and Postdoctoral Training

2017-2020, Postdoctoral Associate, MIT CSAIL

2011-2017, Ph.D., Georgia Tech

2007-2011, Bachelor, Shanghai Jiao Tong University

Selected Awards

Distinguished Paper Award, FSE 2015

Distinguished Paper Award, PLDI 2014

Selected Services

Program Committee: PLDI 2021, SAS 2019, PLDI 2018

External Review Committee: PLDI 2020, PLDI 2017

Selected Publications

1. Osbert Bastani, Xin Zhang, Armando Solar-Lezama. Verifying Fairness Properties via Concentration. ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), 2019.

2. Xin Zhang, Armando Solar-Lezama, Rishabh Singh. Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections. Conference on Neural Information Processing Systems (NeurIPS), 2018.

3. Xin Zhang, Ravi Mangal, Mayur Naik, and Aditya Nori. Query-Guided Maximum Satisfiability. ACM Symposium on Principles of Programming Languages (POPL), 2016.

4. Ravi Mangal, Xin Zhang, Mayur Naik, and Aditya Nori. A User-Guided Approach to Program Analysis. ACM Symposium on Foundations of Software Engineering (FSE), 2015. Distinguished Paper Award.

5. Xin Zhang, Ravi Mangal, Radu Grigore, Mayur Naik, Hongseok Yang. On Abstraction Refinement for Program Analyses in Datalog. ACM Conference on Programming Language Design and Implementation (PLDI), 2014. Distinguished Paper Award.

6. Xin Zhang, Ravi Mangal, Mayur Naik, Hongseok Yang. Hybrid Top-down and Bottom-up Interprocedural Analysis. ACM Conference on Programming Language Design and Implementation (PLDI), 2014.

7. Xin Zhang, Mayur Naik, Hongseok Yang. Finding Optimum Abstractions in Parametric Dataflow Analysis. ACM Conference on Programming Language Design and Implementation (PLDI), 2013.