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Lingming Zhang
张令明 Associate Professor  Department of Computer Science Grainger College of Engineering University of Illinois Urbana-Champaign
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Dr. Lingming Zhang's main research interests lie in Software Engineering, and its synergy with Machine Learning, Programming Languages, and Formal Methods. He has published over 80 research papers, winning the ACM SIGSOFT Early Career Researcher Award, four ACM SIGSOFT Distinguished Paper Awards, and one Best Industry Paper Award. His research has helped detect hundreds of bugs for open-source projects from Apache and GitHub, as well as software systems from eBay, eMetric, Google, Meta/Facebook, Microsoft, NVIDIA, OctoML, Oracle, and Yahoo!. His work on regression testing optimization has been run day-to-day in Google, while his work on automated program repair and unified debugging has been successfully deployed to the Alipay system with million lines of code and over 1 billion global users. More recently, his work on ML system fuzzing has been adopted by NVIDIA developers. To date, his research has been supported by National Science Foundation (including NSF CAREER Award and NSF CRII Award), Google, Samsung, NVIDIA, Amazon, Alibaba, Kwai Inc, and Meta/Facebook.
Positions: I am looking for several Fall'23 PhD students interested in PL/FM/SE and/or Machine Learning (such as Large Language Models for code and ML system reliability). Please apply to Illinois CS (with faculty interest) by Dec. 15th, and/or send me an email (with your CV). Recent Service: ISSRE 2022 (Program Co-Chair), ICSE 2022 Demo (Program Co-Chair), FSE 2022, ASE 2022, TACAS 2022, and ICST 2022. Looking forward to your high-quality submissions! |
News
Dean's Award for Excellence in Research, University of Illinois- Two papers on accepted to ISSTA'23. To our knowledge, TitanFuzz (formerly called LLMFuzz) is the first work demonstrating that LLMs can be directly applied for both generative and mutative fuzzing, while being fully automated, generalizable, and applicable to domains challenging for traditional approaches (such as DL systems)!
- Multiple papers accepted to ICSE'23, including an extensive study on directly leveraging modern LLMs for fixing real-world systems and the first DL system fuzzing technique specifically targeting the crucial automatic differentiation (AD) engines, which are the basis/foundation for recent advances in DL.
- Meta Research Award (AI4AI)
- Our work on neural bug seeding won the ACM SIGSOFT Distinguished Paper Award at ASE'22.
- NNSmith got accepted to ASPLOS 2023: NNSmith applies symbolic constraint solving and gradient-based search in tandem for DL model&input generation, and has found 50+ confirmed bugs for popular DL compilers/optimizers. Congratulations to Jiawei and Jinkun!
- UIUC List of Teachers Ranked as Excellent (Spring 2022)
- One paper on neural bug seeding accepted to ASE 2022.
- Two papers accepted to FSE'22: AlphaRepair is the first cloze-style (or infilling-style) program repair technique that does not rely on historical bug fixes for learning-based program repair; DeepREL leverages API relations for fuzzing popular DL libraries, and has found 100+ confirmed bugs (including 13.5% of all PyTorch high-priority bugs in a three-month period). Congratulations to Chenyuan, David, Steven, Yinlin!
- Google Research Scholar Award
- One paper on pre-trained code models accepted to ISSTA'22. Congratulations to Zhengran and Hanzhuo!
- Gift funding from Kwai Inc.
- One paper on tensor compiler fuzzing conditionally accepted to OOPSLA'22. Congratulations to Jiawei, Yuxiang, Sen, and Yinlin!
- Multiple papers on fuzz testing (of deep learning libraries, JVM implementations, and binaries) and program repair accepted to ICSE'22. Congratulations to all my students, interns, and collaborators!
- One paper on unified debugging accepted to TSE'22. Congratulations to Sam, Yiling, and Xia!
- Our work on configuration testing won the ACM SIGSOFT Distinguished Paper Award at ISSTA'21. Congratulations to Runxiang!
- One paper on learning to debug accepted to FSE'21. Congratulations to Yiling!
- Two papers on configuration testing and just-in-time defect prediction accepted to ISSTA'21. Congratulations to Runxiang and Zhengran!
- ACM SIGSOFT Early Career Researcher Award (Citation: “for outstanding contributions to mutation testing, regression testing, fault localization, and program repair”)
- UIUC List of Teachers Ranked as Excellent (with Outstanding rating, Fall 2020)
- One paper on fast and precise program repair accepted to ICSE'21. Congratulations to Lingchao and Yicheng!
- One paper on API bug detection accepted to ICST'21. Congratulations to Xia, Jiajun, and Sam!
Biography
Lingming Zhang is an Associate Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Dr. Zhang got his B.S. in Computer Science from Nanjing University (China) in 2007, and M.S. in Computer Science from Peking University (China) in 2010. He got his Ph.D. in May. 2014 from the Electrical & Computer Engineering Department at The University of Texas at Austin. He was very fortunate to work under the supervision of Prof. Sarfraz Khurshid in the Software Verification Validation and Testing Group. Before August 2020, he was an Assistant Professor in the Department of Computer Science at the University of Texas at Dallas. He received a NSF CRII Award in 2016, a Google Faculty Research Award in 2016, a Samsung GRO Award in 2017, a NVIDIA GPU Grant in 2018, an Amazon AWS Research Grant in 2019, an Alibaba Research Gift in 2019, a NSF CAREER Award in 2020, an ACM SIGSOFT Early Career Researcher Award in 2021, a Google Research Scholar Award in 2022, and a Meta Research Award in 2022.
Hobbies
- Climbing, Running, Basketball, Cycling, Reading...