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نمایش ۱-۱۵ از ۵۵ استاد راهنما

اطلاعات پروفایل‌ها از صفحات عمومی دانشگاه‌ها گرفته شده و ممکن است به‌روز نباشد.

Wanja Hoferمشاهده پروفایل

پژوهشگر

University of Erlangen–NurembergGermany

Dr. Wanja Hofer is a former research staff member at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). She specialized in embedded systems, real-time operating systems, and aspect-oriented programming. Her research focused on optimizing hardware-centric systems like Sloth and CiAO, addressing challenges in interrupt handling, scheduling, and software product line variability. Her academic journey includes a PhD in 2014 titled Sloth: The Virtue and Vice of Latency Hiding in Hardware-Centric Operating Systems . She contributed to key projects such as Sloth (time-triggered RTOS) and CiAO (aspect-oriented OS family), emphasizing scalability and configurability for automotive and embedded domains. Hofer also held roles like Web chair for EuroSys 2009 and co-maintained the EuroSys Research Directory. Her teaching involved Basics of Systems Programming in C and OS-related seminars. She advised over 15 graduate students on topics ranging from MPU-based task isolation to filesystem-level variability management. Notable contributions include hardware-accelerated interrupt handling, aspect-oriented OS design, and embedded system energy optimization. Hofer currently works at Brose Fahrzeugteile, applying her expertise in embedded systems and real-time computing to automotive technologies. Her work bridges academic innovation with industrial applications, particularly in safety-critical and resource-constrained environments.

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Sven Apelمشاهده پروفایل

استاد

Saarland UniversityGermany

Sven Apel is Professor of Computer Science at Saarland University, where he holds the Chair of Software Engineering and directs the Saarbrücken Graduate School of Computer Science within the Saarland Informatics Campus. His research aims to advance software engineering into an era of intensive automation by developing methods, tools, and theories for building efficient, reliable, and maintainable software systems, with a strong emphasis on the human factor and interdisciplinary inquiry. His primary research interests include software variability and configuration, AI-based program generation and optimization, socio-technical software analysis, and the application of empirical and neurophysiological methods to study program comprehension. He actively collaborates with industry partners such as Siemens AG, Bosch Engineering, and Airbus Helicopters to apply his research in real-world contexts. His recent publications demonstrate a strong trend towards integrating artificial intelligence and neurocognitive methods into software engineering, focusing on configurable systems, performance modeling, debugging processes, and the scientific validity of empirical studies. His work spans top venues like ICSE, FSE, ASE, and IEEE TSE. ERC Advanced Grant “Brains On Code” ASE Fellow ACM Distinguished Member Hugo Junkers Award for Research and Innovation Heisenberg Professorship (DFG) Emmy-Noether Fellowship (DFG) Best Doctoral Dissertation Awards (University of Magdeburg, Ernst-Denert Foundation, 2007) Most Influential Paper Awards (SPLC'19, ICPC'22, GPCE'23) ACM SIGSOFT Distinguished Paper Awards (ICSE'15, ICSE'21) Best Paper Awards (SPLC'11, Modularity'15, Academy of Management'18) Distinguished Reviewer Awards (ASE'18, ICSE'24, FSE'24) Sven Apel has secured significant research funding, including an ERC Advanced Grant (€2.5M) and multiple DFG grants as Principal Investigator and Project Leader. He has advised numerous PhD and Master’s students and is actively involved in the academic community through program committees for major conferences like ICSE, FSE, and ASE. His work is conducted within a collaborative environment that includes close partnerships with researchers at the Max Planck Institute for Informatics and other institutions within the Saarland Informatics Campus.

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Ondrej Vaculinمشاهده پروفایل

استاد

Ingolstadt University of TechnologyGermany

Prof. Ondrej Vaculin, Ph.D., is a Professor at Technische Hochschule Ingolstadt (THI), specializing in passive vehicle safety, mechatronic systems, and automated driving. He joined THI in 2018 and previously held roles at TÜV SÜD Prague (2008–2018) as Vice President for Safety and Security in Automotive, and as a researcher at Czech Technical University (2005–2008) and DLR Oberpfaffenhofen (2000–2005). His research focuses on enhancing vehicle safety through advanced simulation, sensor integration, and machine learning applications. Education: Ph.D. in Mechanics of Solids, Deformable Bodies and Continua from Czech Technical University in Prague (2001), and a degree in Technical Cybernetics from the Faculty of Electrical Engineering at the same university (1991). His work bridges theoretical research and practical implementation, addressing challenges in automated driving systems, crash simulation, and human body diversity in safety design. Research interests include passive safety systems, autonomous vehicle dynamics, and infrastructure integration for safety enhancements. Recent publications emphasize collaborative smart infrastructure, sensor fusion for free space detection, and machine learning in crash detection. He actively contributes to FISITA, serving as a Council Delegate and member of technical committees. Awards/memberships: Active in FISITA, holding leadership roles in technical committees. No explicit awards listed, though his contributions to automotive safety standards are notable. Grants and advising: While no specific grants or students are detailed, his extensive industry and academic collaborations (e.g., IN2Lab testing field projects) highlight his role in applied research and development.

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Ben Hermannمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Ben Hermann is a Professor for Secure Software Engineering at Technische Universität Dortmund, Germany, with research focusing on the intersection of programming languages and security. His work primarily centers on vulnerability detection using static analysis, risk assessment of software libraries, security guarantees in type systems, and language-based security. His academic journey includes a doctoral degree from Technische Universität Darmstadt in 2016, followed by postdoctoral work in Eric Bodden's Secure Software Engineering Group at the Heinz Nixdorf Institute. Since 2020, he has held a tenure-track professorship at TU Dortmund, after serving as an interim Professor for IT Security at Paderborn University from October 2019 to September 2020. Hermann's research portfolio demonstrates consistent output in static program analysis frameworks, particularly with contributions to Soot and PhASAR. His work spans vulnerability detection, analysis reusability, and research quality in computer science, with emphasis on artifact evaluation. His recent publications show progression from framework development toward security applications and research methodology. Hermann has been actively involved in numerous conferences including ASE, ICSE, ECOOP, and SPLASH, often serving in program committees and as session chair. His research group at TU Dortmund includes students like Maximilian Krebs who presented work on energy consumption prediction of programs. He maintains an active presence in the academic community, advocating for research quality and reproducibility, and serves in various organizational roles including Doctoral Symposium Chair and Diversity & Inclusion Chair for conferences.

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Darko Marinovمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Darko Marinov is a Professor in the Siebel School of Computing and Data Science at the University of Illinois Urbana-Champaign, where he conducts research focused on improving software quality through advanced testing techniques. His work addresses fundamental challenges in software testing including flaky tests, regression test prioritization, and configuration testing. Dr. Marinov's research interests span multiple areas of Software Engineering , with particular emphasis on: Software Testing and Quality Assurance Regression Test Prioritization and Selection Flaky and Non-Deterministic Tests Configuration and Variability Testing Test Suite Optimization Software Reliability and Defect Detection His extensive publication record demonstrates consistent contributions to the field, with research trends showing evolution from foundational testing techniques to addressing modern challenges in software testing, particularly focusing on reliability issues in continuous integration environments and the growing complexity of test suites in large software systems. Dr. Marinov has received numerous prestigious awards recognizing the impact of his work: Two ACM SIGSOFT Impact Paper awards (2012, 2019) ASE Most Influential Paper Award (2015) FSE Test-of-Time Honorable Mention (2024) Seven ACM SIGSOFT Distinguished Paper awards CHI Best Paper Award (2017) Elected Fellow of Automated Software Engineering (2023) His research has been generously supported by major technology companies and government agencies including NSF, Boeing, Facebook, Google, Huawei, IBM, Intel, Microsoft, Qualcomm, Samsung, and SRC. Dr. Marinov actively contributes to the academic community through conference organization, serving as Area Chair for ASE 2025 and Program Committee member for multiple conferences including FSE 2026. His mentoring excellence has been recognized through various awards, highlighting his commitment to guiding the next generation of software engineering researchers.

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Constanza Rodriguez Picedaمشاهده پروفایل

پژوهشگر

Helmholtz Centre Potsdam - German Research Centre for GeosciencesGermany

Constanza Rodriguez Piceda is a researcher at the Deutsches GeoForschungsZentrum (GFZ) in Potsdam, Germany, affiliated with the Department of Basin Modelling. She holds a PhD in Geophysics from Universität Potsdam (2022) and is associated with University of Plymouth (email: constanza.rodriguez@plymouth.ac.uk ). Her research focuses on geodynamics, lithospheric modeling, subduction zone processes, and paleomagnetism. Education: PhD in Geophysics (Universität Potsdam, 2022) Research Areas: Southern Central Andes geodynamics, 3D gravity/rheological modeling, lithospheric strength analysis, mantle hydration, Cambrian paleogeography, and tectonic evolution. Publications: 15+ peer-reviewed articles on lithospheric-scale modeling, seismicity distribution, paleomagnetic constraints, and geodynamic simulations of subduction zones. Key collaborations include institutions like Universidad de Buenos Aires, Technical University of Munich, and GFZ.

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Daniel Strüberمشاهده پروفایل

دانشیار

University of KoblenzGermany

Daniel Strüber is an Associate Professor in Software Engineering at Chalmers University of Technology and the University of Gothenburg, Sweden, and an affiliate of the Department of Software Science at Radboud University Nijmegen, Netherlands. His research focuses on model-driven engineering, AI engineering, and empirical software engineering, addressing challenges in software quality, variability management, and security. He holds a PhD (summa cum laude) from Philipps University Marburg and has held academic positions including Assistant Professor at Chalmers and postdoctoral roles at King's College London and Philipps University Marburg. Education: PhD in Computer Science, Philipps University Marburg (2011–2016) Diplom (M.Sc. equivalent) in Computer Science, Philipps University Marburg (2005–2011) Research Interests: Strüber's work spans model-driven engineering, AI integration in software systems, and empirical studies. Key areas include: Model-based languages and tools for software quality assurance Machine learning-enabled systems and their engineering principles Robotics software engineering and variability management Formal methods for consistency and security Search-based optimization in model-driven development Recent Contributions: Recent work includes studies on LLM-assisted reverse engineering, empirical analysis of manual abstraction in software systems, and model-driven approaches for edge deployment of ML models. His research bridges theory with practical implementations in domains like robotics and web-based systems. Awards: Best Reviewer Award (SoSyM 2025) Distinguished Reviewer Awards (GPCE 2024, SPLC 2023) Transformation Tool Contest Awards (2020, 2016) EASST Best Paper Awards (ICGT 2020, ICGT 2017) Grants & Leadership: Co-editor of a JSS special issue on Product Line Engineering (2024) and program co-chair of SPLC 2024. Active in conferences like ICSE, ICGT, and MODELS. Leads grants such as the VR SEMLA project (2022–2024) and the DFG EUphORia fellowship (2019). Teaching: Courses include 'Software Engineering for AI Systems' at Chalmers and 'Software Product Lines' at Radboud University. Involves students in real-world projects via GiPHouse, a student-run company.

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Joanne M. Atleeمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Joanne M. Atlee is a Professor in the Department of Computer Science at the University of Waterloo, Faculty of Mathematics. She has been an active member of the software engineering research community since at least 2015, with continuous involvement in major conferences through 2025. Her research focuses on software product lines, domain-specific languages, cyber-physical systems, and model-driven engineering. She has made significant contributions to variability management and formal methods in software engineering, with publications spanning industrial case studies, model analysis techniques, and language workbenches. Her recent publications demonstrate a strong emphasis on practical applications of software engineering theory, particularly in the areas of dynamic product lines, declarative analysis, and human-in-the-loop verification systems. Her work bridges theoretical foundations with industrial applicability. Dr. Atlee has held numerous leadership positions in the academic community, including serving as General Chair for ICSE 2019, one of the most prestigious conferences in software engineering. She has also been active as a committee member, session chair, and mentor across multiple conferences including ASE, ICSE, ESEC/FSE, and MODELS. In terms of academic service, she has contributed to doctoral symposia, new faculty development, and equity initiatives, demonstrating a commitment to mentoring the next generation of researchers and promoting diversity in computing.

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Christian Dietrichمشاهده پروفایل

استاد

University of Erlangen–NurembergGermany

Christian Dietrich is a Professor at Technische Universität Braunschweig, specializing in operating systems, real-time systems, and software dependability. Previously affiliated with Friedrich-Alexander-Universität Erlangen-Nürnberg and Leibniz Universität Hannover, he leads the Systems Research and Architecture (SRA) group. His research focuses on dependable embedded operating systems, fault tolerance, static analysis, and compiler optimization. He has contributed to projects like dOSEK, cHash, and MELF, addressing challenges in real-time scheduling, redundancy reduction, and variability management in system software. Education: PhD in Computer Science from Leibniz Universität Hannover (2019). Research Interests: Embedded systems dependability, real-time OS design, static/dynamic analysis, fault injection, and compiler-driven optimization. His work bridges theory and practice, with applications in automotive and safety-critical systems. Recent Work: Recent articles explore compiler caching efficiency (IRHash), memory management (HyperAlloc), and fault-space pruning for hardware fault injection. His work on cHash reduced redundant compilations by 80%, earning a USENIX ATC Best Paper Award. Awards: ECRTS 2018 Outstanding Paper, RTAS 2015 Best Paper, and multiple teaching accolades. Supervised over 30 theses, including topics like live patching, fault injection frameworks, and stack-sharing mechanisms. Lab/Team: Heads the SRA group, collaborating on projects like AHA (Hardware Abstraction), CLASSY-FI (fault injection), and CADOS (RTOS variability management). Active in conferences like OSDI, EuroSys, and RTSS.

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Uwe Breitenbücherمشاهده پروفایل

استاد

Reutlingen UniversityGermany

Prof. Dr. Uwe Breitenbücher is a Professor of System Architecture at Reutlingen University's Faculty of Informatics. He holds a Diplom in Computer Science (2011) and a PhD (2016) from the University of Stuttgart. His research focuses on cloud computing, IT systems management, IoT, blockchain, and pattern languages for software architecture. He also leads educational initiatives in software engineering pedagogy, including gamified e-learning platforms like IT-REX and Gamify-IT. Education: Diplom-Informatiker (2011), University of Stuttgart Dr. rer. nat. (2016), University of Stuttgart His research interests emphasize practical deployment solutions for distributed systems, including cross-component issue management, blockchain interoperability, and cloud orchestration using TOSCA standards. He actively develops tools like Variability4TOSCA and Dromi to address challenges in deployment variability and microservice architecture. His recent articles highlight trends in cross-chain smart contract invocations, gamified education systems, and orchestration of heterogeneous deployment technologies. He has contributed to over 50 peer-reviewed publications since 2018, focusing on cloud automation, blockchain integration, and software engineering education. He chairs the Bachelor's Examination Board for Digital Business and collaborates with industry on projects like the 5G-PreCiSe initiative. His work bridges academic research with practical deployment challenges in modern distributed systems.

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Sandro Schulzeمشاهده پروفایل

استاد

Anhalt University of Applied SciencesGermany

Prof. Dr. Sandro Schulze is a Professor in the Department of Computer Science and Languages at Anhalt University of Applied Sciences. His research focuses on software engineering, particularly in areas such as software architecture analysis, software product line engineering, and variability management. He leads efforts in developing tools for visualizing fork ecosystems and tracking architecture smells. His work bridges theoretical research with practical applications in open-source systems and industrial software. Responsibilities include overseeing the Software Engineering research group within the department. He is actively involved in academic activities, including organizing workshops like WSRE and contributing to initiatives like the Software Reengineering Body of Knowledge (SREBOK). Publications highlight advancements in fork ecosystem visualization (e.g., VisFork toolsuite), empirical studies on architecture smells, and techniques for feature extraction from requirements. His work often emphasizes tool development and empirical validation of software engineering practices.

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Daniel Lohmannمشاهده پروفایل

استاد

Leibniz University HannoverGermany

Daniel Lohmann is a Full Professor and Fachgebietsleiter (Head of Department) at the Department of Operating Systems and Middleware within the College of Engineering and Computer Science at Leibniz Universität Hannover . His research focuses on operating system construction , embedded systems , and dependable real-time systems , with a strong emphasis on generative approaches , software product lines , and hardware-RTOS co-design .

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Xinyu Qinمشاهده پروفایل

استاد

University of TrierGermany

Xinyu Qin is a Professor at the Department of Electrical and Computer Engineering within the School of Information Engineering at Guangdong University of Technology. His research focuses on advanced robotics, signal processing, and integrated circuit design, contributing to fields like multi-manipulator systems and Delta-Sigma modulators. Education: Affiliated with prestigious institutions through collaborative research Research Interests: Robotics, Machine Learning, Electrical Engineering His recent publications (2023-2025) demonstrate expertise in robotic task allocation, high-speed circuit design, and explainable AI for healthcare. Award-winning work includes Interactive Explainable Deep Survival Analysis (2024) and SVP: Safe and Efficient Speculative Execution Mechanism through Value Prediction (2023). Key collaborations involve Guoxing Wang and Liang Qi across 16 records. Current projects involve optimizing convolutional neural network accelerators, analyzing atmospheric river impacts on Greenland's crustal deformation, and advancing MASH Delta-Sigma modulator architectures. His work bridges theoretical innovation with practical applications in smart energy systems and autonomous robotics.

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Kai Ludwigمشاهده پروفایل

پژوهشگر

Hochschule HarzGermany

Kai Ludwig is a Researcher affiliated with Otto von Guericke University Magdeburg , where he is pursuing a doctorate in the "Databases and Software Engineering" research group under the supervision of Prof. Gunter Saake and Prof. Thomas Leich. His work bridges academic research and practical software development, with a focus on variability analysis and software product line engineering.

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Juliana Alves Pereiraمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Juliana Alves Pereira is a Professor at the Computer Science Department of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil, where she leads the Artificial Intelligence for Software Engineering lab (AISE) as part of the Software Engineering lab (LES). Her academic journey includes a Ph.D. in Software Engineering with distinction (summa cum laude) from Otto-von-Guericke-Universität Magdeburg (OvGU) in Germany (2018), a Master's degree in Computer Science from the Federal University of Minas Gerais (Brazil), and postdoctoral research at the University of Rennes, Inria/IRISA (France). Her research focuses at the intersection of software engineering and artificial intelligence, particularly in automating software engineering through software analysis, machine learning, recommender systems, and meta-heuristic optimization. Dr. Pereira's work explores applications of Machine Learning, Explainability, Transfer Learning, Generative AI, Deep Learning, Natural Language Processing, and Recommender Systems in software quality and human aspects contexts. Her publications demonstrate a consistent focus on empirical software engineering, with significant contributions in code quality analysis, pull request characteristics, exception handling, and performance prediction in configurable systems. Her research shows increasing integration of advanced AI techniques with traditional software engineering practices. Best Dissertation Prize from the School of Computer Science in 2018 (Germany) Dissertationspreis award from OvGU (2018) ACM Best Paper Award from SPLC 2021 ACM Best Paper Award from ICPE 2020 CBSoft Most Influential Paper Award from Brazilian Computer Society (SBC) Dr. Pereira actively supervises master's and doctoral research in the Software Engineering concentration area at PUC-Rio. She has served on Program and Organizing Committees for major international conferences including ICSE, ASE, SANER, MSR, and ICSME. Her laboratory collaborations span national and international research groups, reflecting her significant impact in the software engineering community.

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