Find Academic Supervisors

Dimitris MitropoulosView profile

Assistant Professor

• Software Engineering
• Cybersecurity
• Secure Software Development
• +3 more

Dimitris Mitropoulos is an Assistant Professor at the National and Kapodistrian University of Athens (NKUA) in the Department of Business Administration, where he teaches courses on Distributed Ledger Technologies, Data Security and Privacy, Algorithms and Business Analytics, and Introduction to Programming. He also serves as Head of the Reliability Engineering Directorate at the National Infrastructures for Research and Technology (GRNET), Greece's national research and education network organization. Previously, he was a Postdoctoral Researcher in the Computer Science Department at Columbia University. Dr. Mitropoulos received his Ph.D. degree in Secure Software Development Technologies from the Athens University of Economics and Business (AUEB) in 2014. His doctoral research was supported by the Heracleitus II Scholarship, co-financed by the European Union and Greek national funds. He is a member of prestigious professional organizations including ACM, IEEE, and USENIX. Dr. Mitropoulos conducts pioneering research at the intersection of software engineering and cybersecurity, with particular expertise in secure software development, vulnerability analysis, and blockchain security. His work spans multiple dimensions of software security including code injection attacks, infrastructure as code security, smart contract analysis, and dependency management in software ecosystems. His research methodology combines static and dynamic analysis techniques with empirical studies of real-world software systems, particularly focusing on Java, Python, and Solidity ecosystems. His recent work has made significant contributions to understanding security vulnerabilities in modern software development practices and infrastructure management. Dr. Mitropoulos has received numerous prestigious awards for his research contributions, including the Research Excellence Award from NKUA (2025), Distinguished Paper and Artifact Awards at PLDI '22, Best Data Showcase Award at MSR 2018, and multiple postdoctoral research funding scholarships. His work on "Finding typing compiler bugs" was recognized with both Distinguished Paper and Artifact Awards at PLDI '22, highlighting the significance and reproducibility of his research. He has also received recognition for his service to the academic community, including a Certificate of Appreciation from ESEC/FSE '21 for his contributions to conference organization. Dr. Mitropoulos has been actively involved in securing research funding and leading significant research projects. He currently serves as Principal Investigator for the SecOPERA project (2023-Today), funded by the European Commission under Horizon Europe. Previously, he contributed to several major EU and US-funded projects including eSSIF-Lab (2019-2022), FASTEN (2019-2022), PRIViLEDGE (2018-2021), CERTCOOP (2017-2020), PANORAMIX (2016-2019), and TREDISEC (2016-2018). His research has been supported by diverse funding sources including the European Commission's Horizon 2020 program, the National Science Foundation, and the Defense Advanced Research Projects Agency (DARPA). Dr. Mitropoulos plays an active role in the international research community through various leadership positions. He serves on program committees for top-tier conferences including OOPSLA (2026), ICSE (2026), ESEC/FSE (2025), and ISSTA (2025). He has previously served as Workshop Co-Chair for ISSTA 2025 and Student Volunteer Chair for ESEC/FSE 2021. His contributions to mentoring the next generation of researchers include serving as a mentor for the ICSE Student Mentoring Workshop (2022) and supervising Google Summer of Code projects (2017).

• Algorithmic Graph Theory
• Parallel Algorithms
• Graph Theory
• +4 more

Stavros Nikolopoulos is a Professor in the Department of Computer Science & Engineering at the University of Ioannina, Greece. He serves as Director of the Algorithms Engineering Lab and holds a PhD in Computer Science (1991, University of Ioannina). His research focuses on Algorithmic Graph Theory, Parallel Algorithms, Malware Detection, and Software Watermarking. He has published extensively in top-tier journals and conferences, including Discrete Applied Mathematics and Theoretical Computer Science. Education: B.Sc. in Mathematics, University of Ioannina (1982) M.Sc. in Computer Science, University of Dundee (1985) Ph.D. in Computer Science, University of Ioannina (1991) Research Interests: Design and Analysis of Algorithms Graph Algorithms (e.g., permutation graphs, cographs) Malware Detection via System-call Group Analysis Graph-based Watermarking Systems Discrete Event Simulation Awards & Recognition: Best Student Paper Award (WEBIST'13) Best Paper Award (CompSysTech'13) Labs & Projects: Director, Algorithms Engineering Lab Principal Investigator in EU-funded projects (e.g., HRAKLITOS, PENED-05)

Michael EichbergView profile

Professor

• Software Engineering
• Static Analysis
• Software Development Tools
• +3 more

Michael Eichberg is a Professor at Technische Universität Darmstadt, Germany, where his work centers on software engineering, static analysis, programming languages, and secure software development tools. He is the principal architect of the OPAL framework for Java bytecode analysis and has an extensive publication record spanning PLDI, ICSE, ESEC/FSE, ISSTA, ASE, FSE, SOAP, and other premier venues. Research Interests: Static program analysis and its scalability to real-world code bases Software security, particularly cryptographic API misuse and Android app repackaging detection Concurrent and parallel programming models, including deterministic concurrency in Scala Software architecture conformance, drift and erosion detection, and rule reuse Development of open extensible tools and frameworks (OPAL, LectureDoc, QScope, Sextant, XIRC, IRC) Publication Trends: His recent work (2015-2022) demonstrates a strong focus on empirical evaluation of static analysis techniques, modular composition of analyses, and security-related program understanding. Key themes include unsoundness in call graph construction, purity and immutability analyses, parallelization of static analyses, and large-scale studies of cryptographic API misuse. Tools & Frameworks: OPAL – A flexible Java bytecode analysis and manipulation framework (core developer until 2019) LectureDoc 2 – Web-based lecture material authoring and presentation system QScope – Open extensible metrics framework for modern software projects Sextant – Eclipse-integrated software exploration tool XIRC/IRC – Frameworks for enforcing system-wide properties and architectural constraints

• Programming Languages
• Static Analysis
• Abstract Interpretation
• +6 more

Florian Kübler is a researcher at Technische Universitat Darmstadt, Germany, specializing in Programming Languages and Static Analysis . He has contributed to major conferences including PLDI, ISSTA, ESEC/FSE, and SOAP, focusing on topics like abstract interpretation, call graph construction, and modular program analysis. His work addresses challenges in code optimization, soundness evaluation, and runtime reusability in static analysis frameworks. Research Interests: Florian's research spans Abstract Interpretation for static analysis Modularization techniques in program analysis Call graph algorithms for Java Parallelization of static analyses Intermediate representation design Compiler and toolchain optimization Conference Contributions: His publications highlight expertise in static analysis frameworks (OPAL, SootKeeper), semi-implicit parallelization, and systematic evaluation of analysis soundness. Recent work (2022) explores collaborative program analysis, while earlier studies (2018-2020) focus on lattice-based modularization and call graph algorithms.

Dominik HelmView profile

Professor

• Program Analysis
• Static Analysis
• Call Graph Algorithms
• +5 more

Dominik Helm serves as an interim professor at the University of Duisburg-Essen and is a researcher at the Software Technology Group, Technical University of Darmstadt since 2018. He holds a Dr.-Ing. degree and serves as the lead maintainer of the OPAL static analysis framework. Helm is also affiliated with ATHENE (National Research Center for Applied Cybersecurity) and CRISP, where he contributes to cybersecurity research focusing on 'Security at Large' for comprehensive systems. Dr. Helm's research centers on modularization and automatic parallelization of collaborative static analyses to improve precision, soundness, and performance. His work specifically targets the OPAL framework for Java VM bytecode, with expertise spanning purity and immutability analyses, modular call graphs, and bug/security vulnerability detection. His research bridges theoretical foundations with practical implementation, addressing real-world challenges in static analysis. His publication record shows consistent contributions to top-tier conferences (PLDI, ISSTA, ESEC/FSE, ASE) with recent work focusing on cross-language analysis, modular call graph algorithms, and evaluation of static analysis precision. Helm has demonstrated particular interest in making static analysis more practical through modularity and parallelization. As an educator, Helm teaches courses including Software Engineering, Type Systems, Quality Assurance, and Program Analysis at the University of Duisburg-Essen. He has supervised multiple student teams through bachelor and master projects, guiding research on call graphs for dynamic languages, IDE solvers, alias analysis, and immutability analysis. Dr. Helm actively contributes to the academic community through program committee service for ICSE, ISSTA, ASE, and other major conferences. His work with the OPAL framework represents a significant contribution to the static analysis community, providing a platform for developing and composing modular analyses for Java bytecode processing and analysis.

• Design and Analysis of Algorithms
• Graph Algorithms
• Algorithmic Graph Theory
• +12 more

Stavros D. Nikolopoulos is a Professor in the Department of Computer Science & Engineering at the University of Ioannina, Greece, where he also directs the Algorithms Engineering Lab. His research spans theoretical and applied computer science, with a focus on algorithm design, graph theory, and cybersecurity. Research Interests: His primary research areas include the design and analysis of algorithms, especially in graph algorithms and algorithmic graph theory, with a focus on perfect graphs. He also investigates information hiding techniques such as software watermarking, codec systems, and data structures. More recently, his work has extended into malware detection and prevention in mobile systems through response-time modeling and hardware integrity protocols. Publication Trends: His recent publications (2016–2018) reflect a strong focus on graph-based models for software watermarking using self-inverting permutations and bitonic sequences, triadic closure in cographs, and security mechanisms for mobile and hardware systems. The interdisciplinary nature of his work combines theoretical foundations with practical applications in cybersecurity and trusted computing. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: While no explicit list of students or grants is provided, the existence of a dedicated lab and co-authored publications with multiple researchers (e.g., M. Chroni, A. Mpanti, I. Polenakis) suggests active supervision and collaboration. He has likely mentored students in algorithms, graph theory, and cybersecurity topics. No grant details are explicitly stated. Labs and Teams: He leads the Algorithms Engineering Lab at the University of Ioannina, which focuses on algorithmic research with applications in information hiding, malware detection, and graph-based modeling.

Mira MeziniView profile

Professor

• Software development paradigms and tools
• Programming systems for reliable distributed software
• Automated software analysis
• +3 more

Mira Mezini is a Professor of Computer Science at the Technical University of Darmstadt, Germany, leading the Software Technology Lab. She serves on steering committees, program committees, and editorial boards of top-tier conferences and journals. Her affiliations include the National Research Center for Applied Cybersecurity ATHENE and co-directorship of hessian.AI, the Hessian Center for Artificial Intelligence. Her research focuses on programming systems for reliable distributed software and AI, automated software analysis, and foundational code models. She has developed large-scale module concepts for adaptability, extensible programming languages, and intelligent software development environments that leverage web-based resources to generate programming rules and patterns. Specializes in software engineering Expert in programming language design Contribution to cybersecurity and AI Her recent work emphasizes static analysis, distributed systems, and programming language design, with trends in API misuse detection, decentralized applications, and secure local-first programming. The focus spans from foundational type systems to practical tools enhancing software quality and developer productivity. Scientific Awards Two-time IBM Eclipse Innovation Award recipient (2005, 2006) Google Research Award (2017) Horst Görtz IT Security Award (2014) ERC Advanced Grant (2012) ACM Fellow Dahl-Nygaard Prize (2025) She has held leadership roles including Dean of Computer Science at TU Darmstadt (2013-2014) and Vice President positions (2014-2019). Her service extends to international juries, funding panels, and editorial boards. Labs & Teams Leads the Software Technology Lab at TU Darmstadt, driving research in programming paradigms and tools. Co-directs hessian.AI and contributes to the Excellence Cluster 'Reasonable Artificial Intelligence.'

• Artificial Intelligence
• Automated Planning
• Machine Learning
• +7 more

Dimitris Vrakas is an Assistant Professor at the Department of Informatics, School of Informatics, Aristotle University of Thessaloniki (AUTh). He holds a PhD in Intelligent Planning Systems and has conducted post-doctoral research focusing on Planning for the Semantic Web. His professional experience includes roles as a Lecturer (per Greek law 407/80), Informatics Instructor in multiple educational institutions, and IT consultant for medium-sized enterprises through the Go-online Project. Education: Bachelor of Science (1995–1999): Informatics, Aristotle University of Thessaloniki PhD (2000–2004): Intelligent Planning Systems, Dept. of Informatics, AUTh Postdoctoral Research (2005–2007): Planning for the Semantic Web, AUTh Research Interests: Automated Planning, Heuristic Functions, Intelligent Autonomous Systems, Machine Learning Applications (Energy Management, NILM), Semantic Web Services, and Smart Environment Technologies. His work bridges theoretical AI advancements with practical implementations in energy systems and emergency response. Publications: Over 45 papers (including 15 journal articles) and 5 book chapters, with a focus on energy disaggregation, evacuation algorithms, and semantic web composition. His work demonstrates expertise in applying advanced techniques like GANs for data generation and reinforcement learning for adaptive planning. Awards: 2025 ACM SIGMOD Test-of-Time Award for contributions to time-series clustering Advising & Grants: Active in guiding PhD candidates (as per recent calls) and coordinating projects like the IRIS RISK PARADIGM for industrial safety. His work involves developing smart university platforms for energy monitoring and collaborating on EU-funded initiatives. Labs & Teams: Member of the Intelligent Systems Lab at AUTh, contributing to projects like the BOnSAI ontology for smart buildings and the IRISPortal for risk management. He also coordinates the Hellenic Artificial Intelligence Society and chairs conferences like SETN 2016.

Yufei DingView profile

Associate Professor

• Compiler Technology
• Machine Learning
• Quantum Computing
• +3 more

Yufei Ding is an Associate Professor in the Computer Science & Engineering Department at the University of California, San Diego (UCSD), where she leads the PICASSO Lab. Her research spans domain-specific language design, architecture and compiler optimization, and hardware acceleration, with current focus on developing high-performance, energy-efficient, and high-fidelity programming frameworks for quantum computing and machine learning. Dr. Ding received her Ph.D. in Computer Science from North Carolina State University and a B.S. in Physics from the University of Science and Technology of China. Her interdisciplinary background bridges physics and computer science, enabling her to tackle challenges in emerging computing paradigms. Her research interests focus on Compiler Technology, Machine Learning, and Quantum Computing , with specific expertise in domain-specific language design, architecture and compiler optimization, and hardware acceleration. Dr. Ding's work addresses critical challenges in programming frameworks for emerging technologies, particularly in making quantum computing more accessible and efficient through innovative compiler techniques and runtime systems. Dr. Ding's scientific contributions have been recognized with prestigious awards including the NSF CAREER Award (2020) and the IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High-Performance Computing (2019) . As an active researcher and educator, Dr. Ding serves on program committees for major conferences including PLDI, PPoPP, and SPLASH. She currently has Ph.D. openings in quantum computing and machine learning systems research, as well as a postdoc position in quantum computing for physics Ph.D. candidates with relevant background. Dr. Ding founded and leads the PICASSO Lab at UCSD, which focuses on developing innovative solutions for programming emerging computing technologies. The lab's work bridges theoretical foundations with practical implementations to address real-world challenges in high-performance computing.