Static Program Analysis Professors and Supervisors in Germany

Gian Luca Scocciaمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Gian Luca Scoccia is an Assistant Professor at the Gran Sasso Science Institute (GSSI) in Italy, where he also completed his PhD in 2019. He maintains active roles in major software engineering conferences as a program committee member for ASE (2024-2025) and SANER (2026). His academic background includes: PhD from Gran Sasso Science Institute, Italy (2019) Scoccia's research centers on empirical software engineering with specialized focus areas including mobile app security , software repository mining , and program analysis . His recent work increasingly integrates artificial intelligence into software development practices, particularly examining ethical implications in autonomous systems and energy efficiency in LLM-driven applications. He employs rigorous empirical methodologies across all research domains. Analysis of his 2023-2025 publications reveals strong convergence between traditional software engineering and AI innovation, with significant emphasis on mobile contexts, developer tooling, and ethical frameworks. His work consistently combines theoretical architecture design with empirical validation through user studies and systematic assessments. Scoccia demonstrates deep community engagement through program committee service for ASE and SANER conferences, contributing to the advancement of software engineering research standards and discourse.

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He Yeمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

He Ye serves as an Assistant Professor at University College London (UCL), specializing in AI-driven software engineering solutions. His work bridges academic research and industry applications through EuniAI, a startup transforming research into developer tools. Research focuses on code agents for automating software tasks, with three core thrusts: Codebase context retrieval to enhance LLM capabilities Automated issue resolution systems Code agent memory construction His publications (2021-2025) demonstrate consistent innovation in fault localization and program repair. Current advising includes PhD students Zhaoyang Chu and Xiang Li (starting Fall 2025), alongside research assistants Yue Pan, Jiayi Xu, and Han Li. He co-founded EuniAI to commercialize research solutions for practical developer challenges. He actively shapes the field through workshop organization ( LMPL@SPLASH 2025 , APR@ICSE 2025 ) and program committee roles across major conferences including ASE, ICSE, and ESEC/FSE.

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Haofeng Liمشاهده پروفایل

پژوهشگر

Max Planck Institute for Security and PrivacyGermany

Haofeng Li is a Researcher affiliated with the Institute of Computing Technology, Chinese Academy of Sciences and the University of Chinese Academy of Sciences in China. His primary research focuses on advancing program analysis techniques, with specializations in static analysis, taint analysis, and pointer analysis. His work demonstrates consistent innovation in optimizing data flow algorithms. Li's research centers on improving the scalability and efficiency of program analysis frameworks. Key themes include: Developing customized context-sensitive analysis for modern programming paradigms Enhancing computational efficiency of the IFDS algorithm through sparsification Addressing memory constraints via disk-based computation approaches Practical applications in security-oriented taint analysis His publications appear in premier venues including ASE (2019), CGO (2021), and ESEC/FSE (2022), demonstrating sustained contributions to software engineering and compiler research. Current information doesn't specify educational background, supervised students, research grants, or laboratory affiliations.

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Lian Liمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Lian Li is a Professor in the Institute of Computing Technology at the Chinese Academy of Sciences, where he leads the program analysis research group. He holds a PhD from the University of New South Wales, Australia, and a Bachelor's degree from Tsinghua University in Engineering Physics. His research focuses on developing innovative program analysis techniques and tools to enhance software reliability and security. His educational background includes a PhD in Computer Science from the University of New South Wales (2003-2007) with a thesis on "ScratchPad Management for Static Data Aggregates" under Professor Jinling Xue, and a Bachelor's degree in Engineering Physics from Tsinghua University (1993-1998). Lian Li's research primarily centers on program analysis techniques, particularly static analysis methods for software security and reliability. His group developed Wukong, a static analysis and detection system capable of identifying deep security vulnerabilities across functions, components, and complex dependencies in C/C++, Java, and Android applications. This tool has discovered thousands of errors in popular open-source software including Google Chromium, Bash, sed, and Hadoop, with hundreds confirmed by developers and over 50 CVEs assigned. His publication record shows a strong focus on program analysis, particularly context-sensitive pointer analysis, taint analysis, and vulnerability detection. His recent work (2021-2024) demonstrates continued innovation in context-free language reachability, efficient IFDS algorithms, and specialized analysis for generics and authorization vulnerabilities. His research spans cybersecurity, programming languages, and software engineering domains, with emphasis on practical applications for real-world software systems. ASE 2019 Distinguished Paper Award CCS 2022 Best Paper Honorable Mention Lian Li has guided numerous PhD and Master's students in computer system architecture and software theory. His research group maintains active collaborations across various software analysis domains, with funding supporting their work on tools like Wukong. They have developed significant intellectual property including multiple patents related to program analysis techniques. The program analysis research group he leads focuses on developing practical tools for software reliability and security. Their work bridges theoretical program analysis with real-world applications, particularly through the Wukong analysis system which has been successfully applied to major open-source projects.

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Saba Alimadadiمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Saba Alimadadi is an Assistant Professor in the School of Computing Science at Simon Fraser University, specializing in software engineering with focus on program analysis, debugging, and testing for dynamic languages including JavaScript, TypeScript, and Python. Her research develops practical tools to improve developer productivity through semi-automated comprehension and analysis techniques. Her research interests include: JavaScript program analysis for asynchronous code Debugging methodologies for web applications Testing techniques for dynamic languages Developer productivity tooling Code optimization for server-side JavaScript Dr. Alimadadi's publication record shows consistent contributions to top software engineering venues, with recent work focusing on asynchronous JavaScript analysis, code coverage criteria, and JavaScript application optimization. Her research bridges theoretical program analysis with practical tool development for real-world developer challenges. She serves on program committees for major conferences including ICSE (2021-2026), ASE (2019-2025), and ISSTA (2018-2025), and has held organizational roles such as SPLASH/ISSTA 2026 Poster/Demo/SRC Co-Chair and ASE 2022 Proceedings Chair. At Simon Fraser University, Dr. Alimadadi teaches CMPT 276: Introduction to Software Engineering and CMPT 982/479: Special Topics on Web Engineering, while actively recruiting graduate students for her research group.

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Song Wangمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Song Wang is an Associate Professor in the Department of Electrical Engineering and Computer Science at York University's Lassonde School of Engineering since May 2024. Previously, he served as an Assistant Professor at the same institution from July 2019 to May 2024. He earned his Ph.D. in Computer Engineering from the University of Waterloo in December 2018 under Prof. Lin Tan, an MS degree from the Chinese Academy of Sciences in June 2014 under Profs. Ye Yang and Wen Zhang, and BE and BHRM degrees from Sichuan University in June 2011. Dr. Wang's research focuses on the intersection of Software Engineering and Artificial Intelligence, with two main thrusts: 1) leveraging AI technologies to address software reliability challenges (AI for SE), and 2) developing software reliability techniques to improve AI infrastructure systems (SE for AI). His specific interests include software testing, program analysis, software reliability, and machine learning applications in software engineering. His research has led to tools that have detected hundreds of true bugs across various open-source projects. His recent publications reveal a strong focus on applying large language models to software engineering tasks, analyzing vulnerabilities in deep learning libraries, and developing techniques for software testing and reliability. The research spans multiple subfields including API testing, vulnerability detection, bias analysis in generated code, and automated assurance case generation. TOSEM Distinguished Reviewer Award 2023 APSEC'23 Distinguished Paper Award ACM SIGSOFT Distinguished Paper Award (ICPC 2022) ACM SIGSOFT Distinguished Paper Award (ICSE 2020) Best Paper Award at PROMISE 2019 Dr. Wang actively mentors students at all levels, currently supervising multiple PhD and MASc students. His research group has produced numerous publications in top-tier software engineering venues, including ICSE, FSE, ASE, and TOSEM. He also serves on the editorial board of ACM TOSEM and has been involved in organizing major conferences like ASE and CASCON.

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Michael Kaliskeمشاهده پروفایل

استاد

Bochum University of Applied SciencesGermany

Professor Michael Kaliske is a leading researcher at Dresden University of Technology's Institute of Statics and Dynamics of Structures, where he conducts cutting-edge research in computational mechanics and structural engineering. His work bridges theoretical developments with practical applications across civil, mechanical, and materials engineering disciplines. Professor Kaliske's research focuses on computational mechanics with particular expertise in finite element methods, multiscale modeling, and material behavior under various loading conditions. His work spans diverse application areas including concrete technology, wooden structures, elastomeric materials (particularly tires), and uncertainty quantification in structural design. He has developed sophisticated numerical frameworks for analyzing complex structural behaviors, especially in contexts where traditional analytical methods fall short. His research demonstrates strong interdisciplinary connections between civil engineering, mechanical engineering, and computational science with practical applications in infrastructure durability and material design. His publication record shows consistent advancement in computational methods for structural analysis, with recent work emphasizing multiscale approaches, uncertainty quantification, and experimental validation. The research themes demonstrate progression from fundamental material modeling to increasingly complex system-level analysis, particularly in infrastructure durability and tire-road interaction phenomena. His work increasingly incorporates data-driven approaches and uncertainty modeling to address real-world engineering challenges. Professor Kaliske actively leads multiple research projects funded by the German Research Foundation (DFG), including ongoing Priority Programs and Material Grants. His project portfolio demonstrates significant contributions to both theoretical developments in computational mechanics and practical applications in civil infrastructure and industrial manufacturing. His research has particularly strong connections to industrial applications in tire manufacturing and road infrastructure design.

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