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Mitra NasriView profile

Assistant Professor

• Real-Time Systems
• Embedded Systems
• Scheduling Algorithms
• +4 more

Mitra Nasri is an Assistant Professor at the Eindhoven University of Technology, affiliated with the College of Engineering's Department of Electrical Engineering. She contributes to the High Tech Systems Center and EAISI Foundational, focusing on interconnected resource-aware intelligent systems. Research Focus: Real-Time Systems, Scheduling Algorithms, Embedded Systems, Fault-Tolerant Computing, and Cyber-Physical Systems. Key Contributions: Development of scheduling frameworks for multi-rate task chains, response-time analysis techniques, and containerization strategies for real-time distributed applications. Her recent work includes advancements in weakly-hard timing constraints, parallel global scheduling, and cloud integration for embedded systems. She actively collaborates on projects like SAM-FMS and COMP4DRONES. Scientific Awards: Best Paper Award - RTAS 2022 Best Paper Award - RTNS 2016 Outstanding Paper Awards at RTAS 2017, 2022 and RTSS 2020 She teaches courses in Real-Time Systems, Operating Systems, and Automotive Software, and participates in organizing conferences like Embedded Systems Week and CompSys.

Kerstin BunteView profile

Professor

• Machine Learning
• Artificial Intelligence
• XAI (Explainable Artificial Intelligence)
• +7 more

Kerstin Bunte is a Professor of Machine Learning for interdisciplinary data analysis at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute's Intelligent Systems Group. She holds an Honorary Fellowship at the University of Birmingham and leads the Intelligent Systems Group. Her research focuses on interpretable machine learning, interdisciplinary applications (e.g., astrophysics and biomedical data), and visualization techniques. Research Interests: - Machine Learning - Artificial Intelligence - Explainable AI (XAI) - Interpretable Models - Dimensionality Reduction - Data Visualization - Astrophysical Data Analysis - Medical Imaging Awards & Grants: - DSSC XS funding (2023) - NWO VIDI grant (2020) - Rosalind Franklin Fellowship (2016–present) Advising & Students: Supervised PhD students include Elisa Oostwal, Janis Norden, Matteo Marcantoni, and Petra Awad. Research spans topics like tumor segmentation in medical imaging, astrophysical structure detection, and autonomous navigation systems. Labs & Collaborations: Leads the Intelligent Systems Group, collaborating with institutions like the University of Birmingham and the University of Warwick. Work involves interdisciplinary projects combining machine learning with astronomy, biomedical sciences, and robotics.

• Robotics
• Mechatronics
• Control Systems
• +5 more

Pieter van Goor is a Researcher in Robotics and Mechatronics at the Digital Society Institute. He holds a PhD from the Australian National University (2018–2022), awarded in July 2023, and served as a Postdoctoral Research Fellow there from May 2022 to June 2024. His research focuses on geometric methodologies in control systems, state estimation, and navigation, with applications to Lie groups, inertial systems, and multi-agent data fusion. Recent work emphasizes fusion of Gaussian distributions on Lie groups, observer design for navigation systems with delayed measurements, and equivariance in tracking controllers. Key research areas include robotics, mechatronics, and mathematical control theory, with publications addressing topics such as parallel transport in Kalman filtering, collaborative attitude estimation, and geometric approaches to data fusion. His work integrates theoretical mathematics (e.g., Lie group theory) with practical engineering challenges in navigation and robotics. Collaborations span institutions globally, with notable contributions to inertial navigation systems and multi-agent systems. Despite no explicitly listed awards, his h-index of 62 and 4 citations (as of 2023) reflect significant scholarly impact. Advising and grant details are not provided in the text.

Martin J. LandView profile

Associate Professor

• Production Management
• Make-to-order Industries
• Workload Control
• +4 more

Dr. Martin J. Land is an Associate Professor at the Faculty of Economics and Business , University of Groningen , specializing in Operations Management . He has held academic roles since 1992, including Programme Director for multiple Master’s programs and leadership in large-scale research projects like the €500k European-funded initiative. Doctoraal (MSc) in Econometrics and Operations Research (1992) PhD in Management Sciences (2004) His research spans Production Management , Workload Control , Smart Manufacturing , and Sustainable Energy Supply . Recent work includes optimizing hydrogen storage for offshore wind parks and developing control frameworks for high-variety manufacturing. Publications focus on improving throughput times, dispatching rules, and lean methodologies in production environments. He teaches key courses like Logistics & Supply Chain Operations and Sustainable Energy Supply , engaging over 600 students annually. Current projects involve the Prestatieverbetering Noordelijke Maakindustrie initiative, providing practical tools to small manufacturers in Northern Netherlands. Collaborations include Newcastle University Business School and Dutch consultancies like Langhout & Cazemier.

Tayfun KucukyilmazView profile

Lecturer

• Web Search Engines
• Machine Learning
• Parallel and Distributed Systems
• +3 more

Dr. Tayfun Kucukyilmaz is a Lecturer at the Rotterdam School of Management, Department of Technology and Operations Management. Previously, he served as an Assistant Professor at the University of Turkish Aeronautical Association and TED University (Computer Engineering Departments) from 2012 to 2021. His expertise spans Web Search Engines, Machine Learning, and High Performance Computing. Educational Background: B.S. in Computer Science and Engineering (Bilkent University, 1995–2000) M.S. in Computer Engineering (Bilkent University, 2000–2003) Ph.D. in Computer Engineering (Bilkent University, 2006–2012) Research Focus: His work emphasizes optimizing search engine performance, developing metaheuristic algorithms, and enhancing information retrieval systems. Current research integrates machine learning techniques with parallel/distributed computing for real-world applications like healthcare diagnostics. Collaborations: Active collaborations span global institutions, particularly in areas of optimization algorithms and search engine efficiency.

• Program verification
• Software Reliability
• Formal methods
• +4 more

Professor Marieke Huisman is a leading figure in software reliability at the University of Twente, where she chairs the Computer Science department within the Faculty EEMCS and leads the Formal Methods and Tools (FMT) Group. She serves as President and Steering Committee chair of the ETAPS association, Member of the board of IPN (ICT-Research Platform Netherlands), and Fellow of the Netherlands Academy of Engineering (NAE). Her research focuses on program verification, reliability of concurrent, parallel and distributed applications, software specification, and formal methods. She develops verification techniques through the VerCors verifier, with applications spanning concurrent data structures, GPGPU programming, and distributed systems. Her work bridges theoretical formal methods with industrial applications, particularly in safety-critical domains. Professor Huisman's recent publications demonstrate strong activity in deductive verification, with particular emphasis on verification of concurrent and parallel systems, memory models, and practical applications of formal methods. Her research shows consistent evolution from theoretical foundations toward practical industrial applications, with increasing focus on GPU programming verification and automated invariant generation. Netherlands Prize for ICT Research 2013 (50,000 euros) 2023 Athena Award for female researchers who stand out as role models She leads multiple significant research projects including NWO OC M Pallas, WWU Münster - UT collaboration Saves, NWO TTW OTP Cheops, NWO VICI Mercedes, and Interreg North Sea Storm_Safe. Her leadership extends to editorial roles including Associate Editor-in-Chief of the Software Track of Science in Computer Programming and executive board membership of VERSEN, the Dutch National Association for Software Engineering. Professor Huisman directs the FMT Group which develops the VerCors verification toolset for concurrent and parallel software. The group collaborates internationally with institutions including WWU Münster, TU Eindhoven, and NlNet Labs, focusing on making formal verification accessible and practical for real-world software development challenges.

Radia Joy PerlmanView profile

Lecturer

• Computer Networks & Communications
• Security & Privacy
• Cryptography
• +4 more

Radia Joy Perlman is a pioneering computer scientist, network engineer, and author renowned for her foundational contributions to network protocols and security. She is best known for inventing the Spanning Tree Protocol (STP) , which revolutionized network bridging, and the TRILL protocol , which improves Ethernet efficiency. Her work spans network design , security algorithms , and self-organizing systems . Perlman earned her Ph.D. in Computer Science from the Massachusetts Institute of Technology (MIT) in 1988. Her doctoral thesis on Byzantine-robust routing protocols laid the groundwork for resilient network design. She has taught courses at institutions including the University of Washington, Harvard University, MIT, and Texas A&M. Her research focuses on network scalability , security , and self-organizing systems . Recent publications include the third edition of her seminal book on network security (2022) and the RFC 6325 specifying TRILL. Her work addresses challenges in distributed algorithms , link-state routing , and PKI trust models . Perlman has received numerous accolades, including: National Inventors Hall of Fame (2016) Internet Hall of Fame (2014) SIGCOMM Award (2010) USENIX Lifetime Achievement Award (2006) ACM Fellow (2016) IEEE Fellow (2008)

Derek KarssenbergView profile

Professor

• Earth Surface Systems
• Spatio-Temporal Modelling
• Hydrology
• +7 more

Prof. Derek Karssenberg is a Professor of Computational Geography at Utrecht University's Department of Physical Geography within the Faculty of Geosciences. His research focuses on spatio-temporal modeling of Earth surface systems, including hydrology, geomorphology, ecology, and environmental health. He develops software frameworks like PCRaster, LUE, and Campo to enhance model scalability and usability. Current roles include coordinating the Computational Geography group and leading the AI & Sustainability Lab. His work integrates geocomputation with applied data science, addressing sustainability challenges and health-environment linkages. Research interests emphasize model development for complex systems, such as air pollution exposure assessment, land-use change impacts, and global hydrological modeling. Collaborations span environmental epidemiology, remote sensing, and machine learning. He co-initiated the Applied Data Science Master's program and innovates teaching methods using blended learning. Publications (2024–2020) highlight advancements in air pollution modeling, streamflow prediction via machine learning, and scalable hydrological frameworks. Activities include editorial roles for Environmental Modelling & Software and steering committees for Utrecht's Applied Data Science initiatives.

Vasilis TsouvalasView profile

Researcher

• Federated Learning
• Data Privacy
• Audio Recognition
• +6 more

Vasilis Tsouvalas is a Researcher in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), affiliated with the Interconnected Resource-aware Intelligent Systems research group. His work centers on advancing federated learning architectures with emphases on communication efficiency and privacy preservation. His core research domains include: Federated Learning Data Privacy and Security Audio and Speech Recognition Systems Communication Cost Optimization Model Compression Techniques Distributed Machine Learning Analysis of his recent publications reveals a strong trajectory in solving heterogeneity challenges in federated systems, with innovative approaches to functional encryption for unlearning compliance and vision model fine-tuning. His work consistently addresses real-world constraints like communication bottlenecks and edge device limitations while maintaining model accuracy. Contact: v.tsouvalas@tue.nl Dr. Tsouvalas has supervised 2 students according to institutional records, though specific names aren't publicly listed. His research is conducted within the Interconnected Resource-aware Intelligent Systems framework at TU/e, focusing on practical implementations for resource-constrained environments.

Francesc Verdugo RojanoView profile

Assistant Professor

• Scientific Computing
• Parallel Algorithms
• Partial Differential Equations
• +3 more

Francesc Verdugo Rojano is an Assistant Professor at the Faculty of Science (Computer Systems) at Vrije Universiteit Amsterdam, with additional affiliations at the Network Institute and Distributed Computer Systems. His research focuses on scientific computing, parallel algorithms, and numerical methods for partial differential equations, particularly leveraging finite element methods. He actively contributes to open-source software like Gridap, an extensible finite element toolbox in Julia. His work spans computational physics, structural engineering, and materials science, emphasizing scalable numerical techniques for complex systems. Notable research includes fusion technology simulations, hydroelastic analysis of floating structures, and optimization of surface-enhanced Raman spectroscopy substrates. Collaborations involve international teams and interdisciplinary applications. Teaching responsibilities include courses on parallel programming and large-scale parallel systems. His research outputs highlight contributions to unfitted finite element methods, geometric discretization, and computational mechanics, with a strong emphasis on practical software implementations.

• Computational Science
• Scientific Visualisation
• GPU Computing
• +5 more

Dr. Robert (Rob) G. Belleman is a Lecturer and researcher in the Computational Science Lab at the Informatics Institute, Faculty of Science, University of Amsterdam. He concurrently serves as Director of the university-wide College of Informatics (CoI), manager of the Visualisation Lab at Science Park, and head of the Education Group, consolidating teaching, research, and infrastructure leadership roles. Education details are not disclosed in the supplied text. His research integrates large-scale scientific computing with immersive visualisation. Core themes encompass GPU-accelerated simulations—from gravitational N-body dynamics to flood modelling—interactive visual analytics for criminal and biological networks, 3-D morphological analysis of marine organisms, sign-language lexicon technologies, and in-silico oncology platforms that fuse multiscale cancer models with clinical IT workflows. Recent articles (2022-2024) emphasise interdisciplinary visual analytics: uncovering cocaine-trafficking scenarios, discriminating coral species via 3-D quantification, and constructing 3-D sign-language lexicons. Earlier work advanced GPU computing for astrophysics and MD simulations, hybrid socio-genetic network modelling of HIV spread, and grid-enabled oncosimulation for nephroblastoma therapy planning. No scientific awards are listed in the provided source. Belleman leads educational innovation through the College of Informatics and the Education Group, while infrastructural oversight of the Visualisation Lab supports numerous UvA research teams. No explicit grant amounts or named PhD advisees appear in the text. He heads the Visualisation Lab facility at Science Park and coordinates the Education Group within the Computational Science Lab, fostering cross-disciplinary collaboration among computer scientists, life scientists, and physicists.

• Federated Learning
• Neural Networks
• Data Science
• +3 more

J.M. Galjaard is a researcher affiliated with the School of Electrical Engineering, Mathematics and Computer Science at an unnamed institution, specializing in the Data-Intensive Systems department. His primary research areas include Federated Learning, Edge Computing, Neural Networks, and Data Science. Research interests derived from his publications and collaborations focus on: Federated Learning and Continual Learning paradigms Edge Computing optimization techniques Multi-DNN/Multi-Model inference scheduling Robustness in meta-learning under label noise Watermarking in Large Language Models Data privacy in distributed systems Article trends highlight consistent contributions to: Federated Learning frameworks (2024-2025) Edge Computing innovations (2020-2021) Meta-Learning and label noise mitigation (2023) Model optimization under resource constraints Collaborative research with international teams Active collaborations include researchers like B. Cox, L.Y. Chen, and R. Birke, with cross-facility projects dominating recent output.

Kuan-Hsun ChenView profile

Assistant Professor

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +5 more

Kuan-Hsun Chen is an Assistant Professor specializing in Computer Architecture Design for Embedded Systems Real-Time Systems Non-Volatile Memory (NVM) Optimization Machine Learning and Edge AI His research focuses on bridging hardware-software gaps in real-time embedded applications through innovative architectural solutions. Research highlights include: Decision Tree Optimization for Real-Time Inference Wear-Leveling Techniques in NVM Probabilistic Timing Guarantees GPU-Accelerated Graph Algorithms Security-Enhanced NVM Designs He explores theoretical foundations while emphasizing practical implementations in autonomous systems and cyber-physical platforms. Scientific achievements: Best Paper Award (2023) Outstanding Paper Award (2023) Outstanding Reviewer Award (2024) His work spans algorithm design, hardware-software co-optimization, and rigorous system validation through fault injection and simulation frameworks.

• Software Model Checking
• Formal Methods
• Software Verification
• +6 more

Dirk Beyer is a Full Professor and Head of Research Chair at the Department of Computer Science, Ludwig-Maximilians-Universität München (LMU Munich), where he leads the Software and Computational Systems Lab. His research focuses on developing models, algorithms, and tools for constructing and analyzing reliable software systems, with emphasis on software verification, model checking, and static analysis. Professor Beyer's research spans multiple critical areas in software engineering and formal methods. He has made significant contributions to software model checking through tools like CPAchecker and BLAST, structure analysis of large systems using CrocoPat and CCVisu, and formal verification of real-time systems with Rabbit. His work on interfaces for component-based design (Chic) has advanced modular software development approaches. Beyer has pioneered methodologies in benchmarking and reliable experimental evaluation through BenchExec, which has become a standard in tool competitions. Analysis of his recent publications reveals a strong focus on advancing software verification techniques, particularly in transferring knowledge between hardware and software verification domains, decomposing verification tasks for parallel processing, and improving the effectiveness of verification witnesses. His work consistently bridges theoretical foundations with practical tool implementations, with a growing emphasis on comparative evaluation and competition frameworks that drive the field forward. ACM SIGSOFT Distinguished Paper Award (FSE 2024) ACM SIGSOFT Best Artifact Award (FSE 2024) As a principal investigator of the DFG Research Training Group ConVeY, Beyer has secured significant funding for advancing verification techniques. He has played leadership roles in numerous software verification competitions including SV-COMP and Test-Comp, serving as PC Chair for major conferences like TACAS 2018 and VMCAI 2020. His service contributions extend to chairing ETAPS 2022 and organizing multiple workshops on CPAchecker. Professor Beyer leads the Software and Computational Systems Lab at LMU Munich, which has developed numerous influential verification tools including CPAchecker (configurable software verification), BenchExec (reliable benchmarking), and CCVisu (software structure visualization). The lab maintains active collaborations with research groups worldwide and contributes significantly to the international verification community through competitions, benchmarks, and open-source tool development.

• Parallel Computing Systems
• Multi-core Embedded Systems
• System-level Design
• +5 more

Prof. A.D. Pimentel holds a full professorship at the Informatics Institute of the University of Amsterdam, leading the Parallel Computing Systems (PCS) group within the Systems and Networking Lab. His research focuses on multi-core and multi-processor systems, emphasizing performance, energy efficiency, dependability, and productivity in system design and runtime management. He earned his PhD and MSc in Computer Science from the University of Amsterdam in 1998 and 1993, respectively. Current roles: Chair of PCS group, Board member of Advanced School for Computing and Imaging (ASCI), and ICT Research Platform Nederland (IPN) Teaching: Courses on Multi-core Processor Systems, Embedded Software, and Architecture Research interests span edge AI, sustainable computing, and system-level modeling. Recent work includes innovations in energy-efficient scheduling, thermal management in 3D-stacked systems, and adaptive CNN inference at the edge. Over 25 years of contributions to embedded systems design space exploration and hardware/software co-design have been recognized through awards like the IEEE CEDA Outstanding Service Award (2025). Awards: IEEE DATE Fellow (2025), NWO Knowledge & Innovation Covenant grant lead Active in conference organization, serving as General Chair for Embedded Systems Week (2026) and Design Automation and Test in Europe (DATE 2024). Engages in cross-disciplinary projects like improved secure semiconductor evaluation (ISSE) and energy labeling for digital services.