Software Model Checking Professors and Supervisors in Germany

Ulrich Eiseneckerمشاهده پروفایل

استاد

Leipzig UniversityGermany

Professor Ulrich Eisenecker serves as the Director of the Institute for Business Informatics at Leipzig University's Faculty of Economics and Business Administration. He holds the Chair of Business Informatics with specialization in software development for business and administration, a position he has maintained since October 2004. Prior to this, he served as Dean of the Faculty (2012-2016) and Pro-Dean (2008-2012). His academic journey includes professorships at Kaiserslautern University of Applied Sciences (1999-2004) and Heidelberg University of Applied Sciences (1995-1999), following research positions at Daimler-Benz Research Institute and Mannesmann Kienzle GmbH. Professor Eisenecker's research focuses on Generative Software Development , Software Product Lines , Software Visualization (including 2D, 3D, AR and VR applications), and E-Assessment systems . His work bridges theoretical computer science with practical business applications, particularly evident in his application of set theory to software features and product lines. He leads the ongoing 'Visual Software Analytics' project and has previously directed projects funded by the European Social Fund and German Federal Ministry of Education and Research. His publication record spans over two decades, highlighted by the influential 2000 book 'Generative Programming' co-authored with K. Czarnecki and the 2017 Most Influential Paper Award from the Software Product Line Conference. Recent work (2023-2025) continues to advance software engineering and educational technology, particularly in automated assessment systems using AI techniques. Notable recognition: Most Influential Paper Award from Software Product Line Conference 2017 (SPLC 2017) Professor Eisenecker supervises doctoral and master's students, with numerous successful completions including Dr. Richard Müller, Dr. Max Lillack, and Dr. Johannes Kristan. His research group includes several scientific staff members and regularly publishes with student co-authors. He teaches 'Introduction to Computer Science' for economics students, 'Programming,' and 'Software Engineering' courses, integrating his research in automated feedback systems into his pedagogy. His research group maintains strong connections between academic research and practical applications, particularly through open source initiatives and industry collaborations focused on software analytics and educational technology.

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Peter Georg Pichtمشاهده پروفایل

استاد

Max Planck Institute for Social Law and Social PolicyGermany

Peter Georg Picht is Professor for Commercial Law at the University of Zurich's Institute of Law, where he conducts research at the intersection of competition law, digital regulation, and intellectual property. His work focuses on the rapidly evolving legal landscape governing digital markets, with particular expertise in Standard Essential Patents (SEPs), FRAND licensing, and the regulatory implications of artificial intelligence. Professor Picht's research interests span several interconnected domains: Digital market regulation under the Digital Markets Act (DMA), Digital Services Act (DSA), and Data Act Competition law implications of algorithms and artificial intelligence Standard Essential Patents and FRAND licensing frameworks Data governance and access requirements in competitive markets The intersection of intellectual property law with emerging AI technologies His recent publications reveal a consistent focus on the practical implementation challenges of EU digital regulations and the adaptation of competition law frameworks to address algorithmic markets. Professor Picht has published extensively on FRAND licensing disputes, contributing to the scholarly discourse on how courts should determine fair, reasonable, and non-discriminatory royalty rates for standard-essential patents. Professor Picht maintains active research collaborations with leading institutions including the Max Planck Institute for Innovation & Competition, ETH Zurich Center for Law and Economics, and the Swiss Federal Institute of Intellectual Property. His work bridges theoretical legal scholarship with practical regulatory challenges facing digital markets today, making significant contributions to both academic discourse and policy development in European competition law.

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Yang Liuمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Yang Liu is a Full Professor and University Leadership Forum Chair at the School of Computer Science and Engineering, Nanyang Technological University (NTU) in Singapore. He serves as Programme Director for HP-NTU Digital Manufacturing Corp Lab, Deputy Director of the National Satellite of Excellence of Singapore, and Cluster Director in Cybersecurity at Energy Research Institute @NTU. His research spans Cybersecurity , Software Engineering , and Artificial Intelligence . He leads research in malware modeling and detection, vulnerability analysis using machine learning and program analysis, formal verification of security systems, program specification learning, performance analysis, Android system security, and AI security, robustness, fairness, and explainability. His notable work includes the Process Analysis Toolkit (PAT) for model checking and the Deep-Series tools for deep learning testing. Professor Liu has published extensively in top-tier conferences including ASE, ICSE, FSE, ISSTA, and S&P. His research demonstrates strong trends toward integrating AI/ML techniques with traditional software engineering and security approaches, particularly focusing on large language models for code analysis, vulnerability detection, and program repair. Recent publications show a growing emphasis on blockchain security, smart contract analysis, and addressing security challenges in AI systems. NRF Investigatorship (Class 2020) ACM's Distinguished Speaker Nanyang Research Award (Young Investigator) Microsoft Asia Research Fellowship 20 Year ICFEM Most Influential System Award for PAT Multiple ACM SIGSOFT Distinguished Paper Awards Professor Liu actively advises students and has seen notable student achievements, including Singapore Data Science Consortium research award winners and AISG PhD Fellowship recipients. His research is supported by numerous grants including a $900,000 NTU-NAP grant for Formal Verification on Cloud and a $471,000 grant for Vulnerability Detection in Binary Code. He leads the HP-NTU Digital Manufacturing Corp Lab and contributes to RollsRoyce@NTU Corporate Lab research on complex business systems simulation.

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Minxue Panمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Minxue Pan is a Professor and PhD supervisor at the Software Institute, State Key Laboratory for Novel Software Technology, Nanjing University, China. His research focuses on the dependability of complex software systems, with expertise spanning software modeling and verification, software analysis and testing, cyber-physical systems, mobile computing, and intelligent software engineering. Ph.D. in Computer Science and Technology from Nanjing University (2014), supervised by Prof. Xuandong Li B.Sc. from Nanjing University Studied at UC Berkeley's Department of Electrical Engineering and Computer Sciences (2009-2010) under Prof. Edward A. Lee Professor Pan's research interests center on improving software dependability through innovative approaches to modeling, analysis, and testing. His work spans traditional software systems, mobile applications (particularly Android), cyber-physical systems, and the application of AI techniques to software engineering problems. He has made significant contributions to GUI testing, vulnerability detection, and deep learning applications in software engineering. His recent publications (2024-2025) demonstrate a strong focus on applying advanced machine learning techniques to software testing and security challenges. Key trends include leveraging large language models for test migration, enhancing fault localization with graph learning and contrastive learning, developing specialized frameworks for Android security analysis, and improving test efficacy through GUI and functional equivalence. His work consistently targets real-world industrial settings and addresses practical challenges in mobile and complex software systems. ISSTA 2020 Distinguished Paper Award ICSE 2025 Best Artifact Award Professor Pan actively advises graduate students and has developed several notable tools including Q-testing (reinforcement-learning based Android testing), ISDChecker (model checking for interrupt-driven systems), PREFEST (preference-wise testing for Android), Sketchoid (GUI code search), and PI-REC (hand-drawn draft conversion). His research is supported by extensive publication records in top-tier software engineering venues including ASE, ICSE, FSE, ISSTA, and TOSEM. He teaches undergraduate courses in Advanced Programming with C++, Software System Design, and Software Construction, as well as graduate courses in Advanced Software Design. His laboratory work focuses on developing practical solutions for real-world software dependability challenges through the State Key Laboratory for Novel Software Technology.

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Marian Lingsch-Rosenfeldمشاهده پروفایل

پژوهشگر

Max Planck Institute for Security and PrivacyGermany

Marian Lingsch-Rosenfeld is a researcher at the Department of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), affiliated with the Software and Computational Systems Lab. Based in Office Room F 012 at Oettingenstraße 67, Munich, they actively contribute to software verification research and mentor graduate students through thesis projects. Research interests focus on software verification , program analysis , and model checking , with specific expertise in predicate abstraction, constrained horn clauses, and deductive verification techniques. Their work bridges theoretical foundations with practical verification tools, particularly CPAchecker. Recent publications demonstrate significant contributions to verification witnesses, program transformations, and loop abstraction techniques. Conference participation includes active roles in ASE, ECOOP, and VMCAI as both author and committee member for artifact evaluation. As a thesis supervisor, they guide students through advanced topics including: Constrained-Horn-Clause export for CPAchecker BMC algorithm performance improvements Software Verification Witnesses extensions Deductive verifier development Compiler optimizations impact analysis Available for consultation via office hours by appointment through meet.lrz.de, with communication primarily via university email channels.

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Zhiyun Qianمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Zhiyun Qian is the Everett and Imogene Ross Professor in the Department of Computer Science and Engineering at the University of California Riverside. His research bridges academic security research with practical hacking techniques, focusing on vulnerability discovery and analysis across operating systems, networks, and mobile platforms. His primary research interests include: System security: Automated cyber attacks/defenses, kernel vulnerability discovery, and security tool development Network security: TCP side channels, multi-path TCP flaws, and firewall evasion techniques AI/ML applications for security: LLM-integrated static analysis and reinforcement-learning-based fuzzing His work has led to critical discoveries including unfixable TCP side channel vulnerabilities (CVE-2016-5696) recognized with GeekPwn awards. His research methodology combines program analysis, reverse engineering, fuzzing, model checking, and machine learning to build practical security systems. Notable scientific awards include: GeekPwn 2016 most creative idea award Geekpwn 2017 winner award Applied Networking Research Prize Professor Qian actively mentors students in security competitions including Pwn2Own and GeekPwn. He serves on prestigious program committees including IEEE Security and Privacy (Oakland), ACM CCS, and USENIX Security. His teaching portfolio includes graduate courses CS 254 (Network Security) and CS 255 (Computer Security), along with undergraduate courses CS 153 (Operating Systems) and CS 165 (Computer Security). He leads the SecLab research group at UCR (GitHub: seclab-ucr, 3824★) developing security tools for kernel and Android ecosystems. Current projects focus on LLM-enhanced static analysis, precise vulnerability detection, and automated patch testing.

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Gary Tanمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Gang (Gary) Tan is a Professor in the Computer Science and Engineering Department at Pennsylvania State University, co-directing the Institute for Networking and Security Research (INSR). His research bridges computer security, formal methods, and programming languages to develop practical solutions for software vulnerabilities and AI fairness. Education: B.E. in Computer Science from Tsinghua University Ph.D. in Computer Science from Princeton University Dr. Tan specializes in applying compiler techniques and formal verification to security challenges, with seminal work on cache side-channel attacks and fairness in machine learning. His Security of Software (SOS) Group develops frameworks that integrate theoretical guarantees into real-world systems, emphasizing measurable security outcomes and ethical AI. Recent projects focus on quantifying bias in neural networks and mitigating speculative execution vulnerabilities. Analysis of his 2021-2025 publications reveals a strategic pivot toward AI security, where he pioneers methods for fairness testing (e.g., information-theoretic debugging) and repair (e.g., NeuFair). Concurrently, his security work evolves from foundational side-channel research (SpecSafe, 2021) toward hardware-software co-design solutions, demonstrating consistent innovation across theoretical and applied domains. Scientific Awards: James F. Will Career Development Professorship NSF CAREER Award Google Research Award (two instances) Distinguished Reviewer Award at 2018 IEEE Symposium on Security and Privacy Outstanding Research Award at Penn State Ruth and Joel Spira Excellence in Teaching Award Best Paper Award at PLDI 2024 Dr. Tan leads the SOS Group with funding from NSF (including CAREER), DARPA (ISAT study group membership), and industry partners like Google. His grants support interdisciplinary projects spanning secure compilation, fairness engineering, and hardware security, while his teaching excellence award reflects commitment to pedagogy in core systems courses. He co-directs Penn State's Institute for Networking and Security Research (INSR), fostering collaboration between systems, security, and AI researchers. The SOS Group maintains active partnerships with industry security teams and contributes to open-source tools for vulnerability detection, with recent work expanding into fairness certification for machine learning pipelines.

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Lars Grunskeمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Lars Grunske is a Professor in the Department of Computer Science at Humboldt University of Berlin, Germany. His academic career spans multiple institutions across Germany, Australia, and internationally, with a strong focus on research and conference participation in software engineering. His educational background includes a PhD in computer science from the University of Potsdam (Hasso-Plattner-Institute for Software Systems Engineering) in 2004. Professor Grunske's research interests center on modeling and verification of systems and software, with particular emphasis on automated analysis techniques. His work primarily focuses on probabilistic and timed model checking and model-based dependability evaluation of complex software intensive systems. He has made significant contributions to software testing, program repair, formal methods, and the application of machine learning techniques to software engineering problems. His publication record shows consistent contributions to top software engineering conferences over the past decade, with recent work exploring the intersection of AI/ML with traditional software engineering challenges. His research demonstrates an evolution from foundational model checking techniques toward more practical applications in software testing and repair. Boeing Postdoctoral Research Fellow Professor Grunske actively mentors through conference activities including chairing mentoring circles at ICSE 2021. He serves on numerous program committees for major software engineering conferences including ASE, ICSE, ESEC/FSE, and others, demonstrating his standing in the academic community. His involvement spans multiple roles from committee member to track chair and award committee positions. He maintains an active research laboratory focused on software verification and testing, as indicated by his departmental affiliation and research website.

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Shiva Nejatiمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Software Testing and Verification
Cyber Physical Systems
Applications of AI to Software Engineering
+۴ مورد دیگر

Shiva Nejati is a Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, where he leads research in software engineering with a focus on verification and analysis of cyber-physical systems. Previously, he served as a senior scientist (2012-2019) at the SnT Center, University of Luxembourg, and as a scientist (2009-2012) at the Simula Research Laboratory. He earned his M.Sc. and Ph.D. from the University of Toronto in 2003 and 2008, respectively. His research interests span Software Testing and Verification, Cyber Physical Systems, Applications of AI to Software Engineering, and Search-based Software Engineering. Nejati's work draws on techniques from formal software modeling, meta-heuristics optimization, machine learning, system engineering, and empirical methods. He has extensively worked on testing and fault localization of cyber physical systems, particularly applied to autonomous vehicles and IoT systems, while also exploring requirements traceability, automated configuration of product line systems, and simulation modeling of CPS. His recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional software verification techniques, particularly for complex cyber-physical systems. His work bridges search-based testing with formal verification methods to address the challenges of testing compute-intensive models in domains like autonomous vehicles and satellite systems. The research shows increasing focus on applying machine learning to solve longstanding problems in software testing and requirements engineering. Nejati serves in significant leadership roles across major software engineering conferences, including PC Chair for ASE 2026, General Chair for CASCON 2026, and various program committee and organizing committee roles for ICSE, ISSTA, MODELS, and other top-tier conferences. He is also an Associate Editor for EMSE Journal and ASE Journal, and previously served on the IEEE Transactions on Software Engineering editorial board. He teaches advanced courses including 'AI-enabled Software Verification and Testing' and 'Software Construction' at the University of Ottawa, while leading the Sedna lab which focuses on verification, analysis, and testing of complex systems. His research is conducted in close collaboration with industry partners across telecommunication, maritime, energy, automotive, and aerospace sectors.

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Wei Chenمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Wei Chen is a Research Fellow at the Institute of Software, Chinese Academy of Sciences, where he serves as a PhD and Master's supervisor. He leads the Software Engineering Technology R&D Center and maintains affiliations with the University of Chinese Academy of Sciences and its Nanjing College. Dr. Chen has established himself as a leading figure in intelligent software engineering research within China's academic community. His primary research focuses on four interconnected areas: intelligent code maintenance and quality assurance (particularly Python ecosystem compatibility based on domain knowledge), reliability assurance of complex IoT systems in human-machine-object convergence scenarios, cloud-native system development with emphasis on Function-as-a-Service optimization, and quality assurance of deep learning frameworks in resource-constrained environments. Dr. Chen's work consistently bridges theoretical advances with practical applications, maintaining strong industry collaborations with major Chinese technology companies. Analysis of Dr. Chen's recent publications reveals a strategic integration of AI techniques with traditional software engineering challenges. His research shows increasing emphasis on leveraging large language models for IoT component synthesis, sophisticated dependency management solutions for Python ecosystems, and innovative approaches to testing autonomous systems. The work demonstrates both theoretical depth and practical utility, with many publications leading to implemented tools and systems. Second Prize of Science and Technology Progress Award of China Institute of Electronics (2022) First Prize of Science and Technology Progress Award of China Institute of Electronics (2021) ACM SIGSOFT Distinguished Paper Award (2023) Special Prize of the 4th China Software Open Source Innovation Competition (2021) First Prize in the 4th China Software Open Source Innovation Competition (2021) OW2 Programming Contest First Prize (2016) Dr. Chen has mentored over ten graduate students who have achieved notable success in academic competitions and industry placements. His laboratory (TCSE, http://tcse.cn/) currently manages multiple significant research projects including 'Complex IoT System Reliability Assurance Key Technology Research' (2025-2028), 'Intelligent Development, Testing, and Maintenance of Cloud-native Software Ecosystems' (2024-2027), and 'Traffic Infrastructure Digital Industrial Software Architecture and Core Technology Standard System' (2021-2024). The lab maintains active collaborations with Huawei, Alibaba, Tencent, and other leading technology enterprises.

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Sallam Abualhaijaمشاهده پروفایل

پژوهشگر

Max Planck Institute for Security and PrivacyGermany

Dr. Sallam Abualhaija serves as a Researcher at the Interdisciplinary Centre for Security, Reliability, and Trust (SnT) at the University of Luxembourg, where she applies cutting-edge AI technologies to software engineering challenges with emphasis on requirements engineering and regulatory compliance. Her work bridges academic research and industry applications through extensive collaboration with corporate partners. She earned her PhD in Computer Science from Hamburg University of Technology (Germany) in 2016, establishing her expertise in computational approaches to software requirements. Her research centers on leveraging natural language processing and large language models for regulatory compliance, particularly GDPR implementation in software systems. Key focus areas include automated compliance checking of privacy policies, data processing agreements, and financial regulations through techniques like question-answering systems and ambiguity resolution. This work directly addresses the critical need for trustworthy AI systems that adhere to legal frameworks while improving software development efficiency. Analysis of her recent publications reveals a strong trend toward practical tool development (e.g., CompAi) and multi-solution studies for GDPR compliance across mobile applications, financial services, and general software systems. Her research consistently integrates industry collaboration, with growing emphasis on LLM-driven approaches since 2023. Dr. Abualhaija actively contributes to the academic community through program committee roles at ASE, ICSE, and RE conferences, and as co-organizer of workshops including MO2RE (Multi-Disciplinary Requirements Engineering) and FinanSE. She has chaired tutorials on replication in NLP for requirements engineering and AI applications in regulatory compliance, demonstrating commitment to knowledge transfer and community building. As a core member of SnT, she contributes to Luxembourg's leading research hub for security, reliability, and trust in ICT systems. Her work aligns with SnT's mission through projects that develop verifiable, privacy-preserving technologies with real-world regulatory impact, particularly in European data protection contexts.

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Zhenbang Chenمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Zhenbang Chen is a Professor in the College of Computer at National University of Defense Technology (NUDT), China. His academic career spans over a decade with significant contributions to software engineering, particularly in program analysis and formal methods. He has served on program committees for major conferences including ASE, ICSE, and FSE, and has been actively involved in research that bridges theoretical formal methods with practical software engineering applications. Dr. Chen received his Ph.D. and Bachelor degrees in computer science from National University of Defense Technology (NUDT) in June 2009 and July 2002, respectively. His educational background from NUDT has provided a strong foundation for his research in software engineering and formal methods. Ph.D. in Computer Science, National University of Defense Technology (NUDT), 2009 Bachelor's Degree in Computer Science, National University of Defense Technology (NUDT), 2002 Zhenbang Chen's research primarily focuses on program analysis, with special emphasis on symbolic execution techniques. His work extends to formal methods and their practical applications in software engineering. He investigates constraint solving approaches to improve the efficiency of program analysis and explores program synthesis techniques to automate software development tasks. His research bridges theoretical foundations with practical software engineering challenges, particularly in the areas of software verification and testing. His recent work has increasingly focused on optimizing symbolic execution through novel constraint solving techniques and exploring multi-modal approaches to behavior tree synthesis. This demonstrates his commitment to advancing both the theoretical underpinnings and practical applications of software analysis techniques. Professor Chen's publication record shows a consistent focus on symbolic execution and constraint solving, with a clear progression toward more sophisticated optimization techniques. His recent work demonstrates a shift toward multi-objective optimization for floating-point constraints and multi-modal approaches to program synthesis. The research spans both theoretical foundations and practical implementations, with several tools developed from his research participating in international competitions. Dr. Chen's research excellence has been recognized through multiple prestigious awards: ACM SIGSOFT Distinguished Paper Award for FSE 2025 paper "QSF: Multi-Objective Optimization based Efficient Solving for Floating-Point Constraints" ACM SIGSOFT Distinguished Paper Award for ISSTA 2021 paper "Type and interval aware array constraint solving for symbolic execution" ACM SIGSOFT Distinguished Paper Award for ICSE 2018 paper "Towards optimal concolic testing" Bronze Medal (3rd place) in Cover-Branches category at Test-COMP 2025 for the FDSE tool Professor Chen is actively involved in mentoring the next generation of researchers, currently seeking Ph.D. and M.Sc. students to work with him on cutting-edge research in program analysis and formal methods. His research group has developed several tools that have gained recognition in international competitions, including AISE which ranked 1st in SV-COMP 2025's ReachSafety-Loops category and FDSE which won Bronze Medal in Test-COMP 2025. His research has been supported by grants that enable participation in major international conferences and competitions, fostering collaborations with researchers worldwide. Dr. Chen leads a research group focused on program analysis and formal methods at NUDT. His team has developed several notable tools including AISE for program verification and FDSE for software testing, which have achieved top rankings in international competitions like SV-COMP and Test-COMP. The research group maintains active collaborations with other institutions and participates regularly in major software engineering conferences, contributing to both theoretical advancements and practical tool development in the field.

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Sébastien Bardinمشاهده پروفایل

پژوهشگر

Max Planck Institute for Security and PrivacyGermany

Sébastien Bardin is a Senior Researcher and CEA Fellow at the Software Safety and Security Laboratory of Commissariat à l'Energie Atomique (CEA) in Paris-Saclay, France, with affiliation to University Paris-Saclay. He leads significant research initiatives including the BINSEC group on binary-level security analysis (since 2012) and the QBricks group on quantum program verification (since 2020), and served as Head of the Software Quantum Program at CEA LIST from 2021-2023. His research focuses on formal methods and automatic program analysis with applications in software security. Key areas include binary-level security analyses such as vulnerability detection & assessment, reverse engineering, and malware deobfuscation, as well as quantum programming and verification. His methodological expertise spans symbolic execution, abstract interpretation, software model checking, and SMT solving. Bardin's publications demonstrate consistent impact across top venues in security and formal methods, with notable papers at ESOP, CAV, ICSE, NDSS, and S&P. His work on robust symbolic execution, directed fuzzing, and binary-level analysis has established him as a leading researcher in security-oriented program analysis. Recent publications show growing emphasis on quantum program verification alongside continued contributions to binary security analysis. Scientific Awards: ICSE 2021 ACM SIGSOFT Distinguished Paper Award RTAS 2021 Best Paper Award CAV 2021 Selected Paper CEA Fellow (2021-present) ACM Senior Member (2021-present) Bardin actively mentors PhD students and has advised numerous researchers who have received recognition including GDR Sécurité and GDR GPL PhD awards. His service to the community is extensive, with leadership roles in GDR Sécurité, RESSI, and organizing major conferences including CAV 2023 (sponsor co-chair) and FIC 2023 (scientific program chair). He also contributes to multiple program committees across security and formal methods venues.

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