Liqian Chen is a Full Professor and PhD Supervisor in the College of Computer Science and Technology at the National University of Defense Technology (NUDT) in Changsha, China. With a prolific research career spanning over a decade, Professor Chen has established himself as a leading expert in program analysis, verification, and automated program repair. His work bridges theoretical foundations with practical applications, particularly in the areas of abstract interpretation and numerical program analysis. Professor Chen's primary research interests include: Program analysis and verification Abstract interpretation Automated program repair Floating-point analysis Neural network verification His research focuses on developing rigorous theoretical frameworks for program analysis while ensuring practical applicability to real-world software systems. A significant portion of his work addresses the challenges of numerical accuracy in software, particularly in floating-point computations, and has extended these techniques to the emerging domain of neural network verification. Analysis of Professor Chen's recent publications reveals several key trends in his research trajectory. His work has evolved from foundational abstract interpretation techniques to address increasingly complex software systems, including neural networks. There's a clear progression from theoretical developments in abstract domains to practical applications in software verification and repair. His recent work demonstrates a growing emphasis on the intersection of traditional program analysis with machine learning systems, particularly in verifying neural network behavior and addressing numerical instability in AI systems. Professor Chen has received notable recognition for his contributions to the field: ACM SIGSOFT Distinguished Paper Award (ISSTA 2024) Best Paper Award (APSEC 2017) Best Paper Award Nomination (EMSOFT 2015) As an academic advisor, Professor Chen supervises numerous PhD and Master's students working on cutting-edge research in program analysis and verification. His team has developed several influential tools including AutoRNP (for automatically detecting and repairing floating-point errors), Software Apron (a library for numerical abstract domains), and F-IKOS (a static analyzer for Fortran programs). Professor Chen has secured substantial research funding to support his work, though specific grant details are not provided in the available information. He actively serves the research community through program committee roles for major conferences including ASE, SAS, and VMCAI, and as a guest editor for journals such as Automated Software Engineering Journal and Journal of Systems Architecture. Professor Chen leads a vibrant research group focused on high-confidence software technologies. His team, comprising PhD students, Master's students, and research engineers, collaborates closely on projects spanning from theoretical foundations of program analysis to practical tool development. The group maintains strong connections with both academic institutions and industry partners, facilitating the transfer of research innovations to real-world applications. Their work is characterized by rigorous theoretical underpinnings combined with practical validation on real software systems.
