Education & Affiliations
Biography
About Professor Wang
I received my Bachelor’s degree in Physics from Tsinghua University, China, in 2019. I then pursued my doctoral studies at the University of California, Los Angeles, where I obtained a Ph.D. in Computer Science in 2025. My research area is software engineering and systems, with a particular focus on testing and debugging techniques for heterogeneous computing platforms, including FPGAs, GPUs, and quantum computing. My works span topics such as multi-layer compiler debugging, full-stack compiler testing, and fuzz testing for heterogeneous applications. They have been published in ASE, ICSE, ESEC/FSE, and ASPLOS. Prior to joining Tulane, I worked as an Applied Scientist at Amazon Web Services, focusing on program analysis and formal verification for cloud systems. My research has been recognized by the SIGSOFT Research Highlight.
Research Interests
Software Engineering, Quantum Computing, Heterogeneous Computing, Big Data
Publications
• J. Wang, Y. Qiu, B. Limpanukorn, H. J. Kang, Q. Zhang, and M. Kim, “DuoReduce: Bug Isolation for Multi-Layer Extensible Compilation,” in Proceedings of ESEC/FSE 2025, Trondheim, Norway.
• B. Limpanukorn, J. Wang, H. J. Kang, Z. Zhou, and M. Kim, “Fuzzing MLIR Compilers with Custom Mutation Synthesis,” in Proceedings of ICSE 2025, Ottawa, Canada.
• J. Wang, Q. Zhang, H. Rong, G. H. Xu, and M. Kim, “Leveraging Hardware Probes and Optimizations for Accelerating Fuzz Testing of Heterogeneous Applications,” in Proceedings of ESEC/FSE 2023, San Francisco, California, USA.
• Q. Zhang, J. Wang, G. H. Xu, and M. Kim, “HeteroGen: Transpiling C to Heterogeneous HLS Code with Automated Test Generation and Program Repair,” in Proceedings of ASPLOS 2022.
• J. Wang, Q. Zhang, M. Kim, and G. H. Xu, “QDiff: Differential Testing of Quantum Software Stacks,” in Proceedings of ASE 2021 (SIGSOFT Research Highlight).
• Q. Zhang, J. Wang, and M. Kim, “HeteroFuzz: Fuzz Testing to Detect Platform Dependent Divergence for Heterogeneous Applications,” in Proceedings of ESEC/FSE 2021.
• J. Wang, F. Ma, and Y. Jiang, “Poster: Fuzz Testing of Quantum Program,” in Proceedings of ICST 2021 (Best Poster Award).
• Q. Zhang, J. Wang, M. A. Gulzar, R. Padhye, and M. Kim, “BigFuzz: Efficient Fuzz Testing for Data Analytics Using Framework Abstraction,” in Proceedings of ASE 2020.
Courses Taught
CMPS-4660-01 & CMPS-6660-01 Quantum Computing
