Jingling Xue, IEEE Fellow (Computer Society)
Scientia Professor
School of Computer Science and Engineering
UNSW
Sydney, NSW 2052, Australia


Office: Room 501L, K-17
Phone: +61 (2) 9385 4889
Email: j.xue@unsw.edu.au

Open-Source ToolsAwardsPublicationsTeam FundingProfessional ActivitiesTeaching

Short Biography Jingling Xue is a Scientia Professor in the School of Computer Science and Engineering at UNSW Sydney where he leads the Programming Languages and Compilers group. He received his B.Eng and M.Eng degrees in Computer Science and Engineering from Tsinghua University in 1984 and 1987, respectively, and his PhD degree in Computer Science and Engineering from Edinburgh University in 1992. He has been elevated to IEEE Fellow (of IEEE Computer Society) in recognition of his contributions to compiler optimisation and program analysis.

Research Interests Jingling Xue's research spans programming languages, compiler technology, and program analysis. He strives to achieve the practical relevance of his research by focusing on developing innovative solutions and open-source tools for real-world software applications. He is interested in sharing the outcomes of his research projects in the form of open-source tools, by supporting scientific replicability and reproducibility. His current research projects include compiler techniques for improving parallelism and locality, pointer/alias analysis techniques and tools for million-line-scale programs, and static and dynamic program analysis techniques and tools for detecting bugs and security vulnerabilities in real-world software applications (e.g., web browsers and Android apps). He has published a research monograph on loop tiling (one of the most important loop transformations for improving parallelism and locality), 70+ journal articles, and 170+ conference papers, with many in prestigious IEEE/ACM journals and conferences in his field.

Awards Jingling Xue's papers have been selected for best/distinguished/test-of-time paper/artifact awards at a number of prestigious conferences in programming languages, compiler technology, and software engineering. These include (1) the Best Paper Award at CGO'13, (2) the Best Paper Award at CGO'16, (3) a Distinguished Paper Award at ECOOP'16, (4) a Distinguished Paper Award at ICSE'18, (5) a Distinguished Paper Award at ISSTA'19, (6) a Distinguished Paper Award at ASE'19, (7) a Distinguished Artifact Award at ISSTA'23, (8) the Best Artifact Award at FSE'23, and (9) a Distinguished Paper Award at ASE'23. In addition, he has also received the Test-of-Time award at CGO'21 (for his CGO'10 paper on pointer/alias analysis, selected as a paper that was published 10 -- 12 years prior and has had a lasting impact on the field).

Services Jingling Xue served as the Program/General Chair of a number of major conferences in his field, including the Program Chair of LCTES'13, the Program Chair of CC'18, the Program Chair of CGO'20, the General Chair of LCTES'20. In addition, he has also served on the program committees of a number of major conferences in programming languages, compiler technology, and software engineering, including PLDI (ERC), POPL (ERC), OOPSLA, ECOOP, PPoPP, SC, CGO, CC, ICPP, ICS, IPDPS, PACT, ICSE, ASE, ISSTA, LCTES, CASES, and EMSOFT. He served as an Associate Editor for IEEE TC, and is currently serving on the editorial boards of IEEE TETC and SP&E (among others).

Prospective PhD Students Jingling Xue has supervised successfully 29 PhD students to completion in his research areas with his students now working as professors in academia and researchers/engineers/practitioners in industry. He is a recipient of Research Supervisor Award (Arc Postgraduate Council, UNSW Sydney) in 2020. Currently, he is looking for self-motivated people to join his research group. If you are interested in pursuing a PhD degree under his supervision, please contact him by sending your CV, copies of your publications and your academic transcripts. Some exciting research areas include memory safety in Rust, smart contract analysis and verification, AI compilers, and adversarial attacks and defences in deep Learning.