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.
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, including SVF (https://svf-tools.github.io/SVF) and Qilin (https://qilinpta.github.io/Qilin).
His current research projects include compiler techniques for improving parallelism and locality for modern computer architectures, compiler techniques for improving the performance of graph processing applications on hardware accelerators (e.g., CPUs, GPUs and FPGAs), 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.
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.
He is an IEEE fellow elected for contributions to compiler optimisation and program analysis.