جست‌وجوی استاد و پژوهشگر

Marcus Gerholdمشاهده پروفایل

استادیار

• Model-Based Testing
• Software Reliability
• Critical Infrastructures
• +۷ مورد دیگر

Marcus Gerhold is an Assistant Professor in the Formal Methods and Tools group at the University of Twente's Faculty of Electrical Engineering, Mathematics and Computer Science. His research focuses on model-based testing for software reliability in critical infrastructures, particularly railway systems, alongside significant contributions to game design and programming language analysis. His educational background includes: PhD in Computer Science from University of Twente (2018): Choice and Chance: Model-based Testing of Stochastic Behaviour MSc in Mathematics from Friedrich Schiller Universität Jena (2013): Embeddings of Weighted Morrey Spaces BSc in Mathematics from Friedrich Schiller Universität Jena (2011): Entropy-, Approximation- and Kolmogorov Numbers on Quasi-Banach Spaces Gerhold's research integrates theoretical model-based testing with practical critical infrastructure applications . His work on railway conformance testing addresses EULYNX controller validation, while his game design research explores affective mirroring in NPCs and procedural dungeon generation. The code modernity analysis stream leverages static analysis to quantify legacy code evolution across languages like Python and PHP, revealing version identification challenges through deep learning. Publication trends show consistent focus on model-based testing methodologies (40%), railway safety applications (25%), and innovative game design/code analysis (35%). Recent work increasingly incorporates AI/ML techniques for UML assessment and Python version identification, while maintaining rigorous formal methods foundations. He actively mentors 63 students across all academic levels and contributes to major research initiatives: STORM_SAFE (ERDF, 2024): Daily Supervisor for WP1/WP2 on software reliability for critical infrastructures ZORRO (KIC grant, 2023): Daily Supervisor for WP4 on zero downtime in cyber-physical systems MISSION (MSCA RISE, 2021-2025): Interim coordinator (early 2024) for space systems modeling As part of the Formal Methods and Tools research group, Gerhold participates in European collaborations while serving on SAC-SVT 2024 and FormaliSE 2023 program committees.

Jop Briëtمشاهده پروفایل

پژوهشگر

• Theoretical Computer Science
• Quantum Information Theory
• Combinatorics
• +۳ مورد دیگر

Jop Briët is a Researcher at the Department of Algorithms and Complexity at Centrum Wiskunde & Informatica (CWI) in the Netherlands. His work focuses on theoretical computer science, quantum information theory, combinatorics, and tensor analysis. He has held grants including the Veni Innovational Research Grant from NWO and a Rubicon fellowship. He has authored over 50 publications in leading venues, exploring topics such as Grothendieck inequalities, quantum computing, and additive combinatorics. His research interests span the interplay between combinatorics and computational complexity, with particular emphasis on tensor analysis, probabilistic methods, and algorithm design. Recent work includes studies on Szemerédi’s theorem with random differences and the application of quantum query algorithms to entanglement-based problems. Awards: Outstanding paper award TQC (2020), Andreas Bonn medal (2013), Stieltjesprijs (2011). Professional Activities: Editor for ERCIM News, Board Member of Koninklijk Wiskundig Genootschap, and frequent invited speaker at workshops on quantum computing and combinatorics. Grants: Veni Grant (2014), Rubicon Fellowship (2012). Current teaching includes courses on Additive Combinatorics and Quantum Information Processing, reflecting his commitment to bridging foundational theory with advanced applications in computing and mathematics.

Aurelien Baillonمشاهده پروفایل

استاد

• Behavioral Economics
• Decision Making Under Risk and Ambiguity
• Subjective Probability Elicitation
• +۱۲ مورد دیگر

Dr. Aurelien Baillon is a Professor of Economics of Uncertainty at the Erasmus School of Economics , Erasmus University Rotterdam, specializing in the Department of Applied Economics . His research focuses on individual decision-making under risk and ambiguity, combining empirical and theoretical approaches to understand probability elicitation and expert opinion aggregation. Key research areas: Behavioral Economics, Risk Attitudes, Bayesian Modeling Major projects: Bayesian Markets , Personal Model of Trumpery , Malakoff Humanis Chair His recent publications explore ambiguity theories , cybersecurity decision-making , and linguistic deception detection . Notable grants include the ERC Starting Grant (2016) and NWO Vidi Grant (2014). Collaborations span institutions like BRiO , HITS Institute , and GATE . The Datavisualization project with Alice Havrileck demonstrates his interdisciplinary approach to uncertainty analysis.

• Machine Learning
• Neural Networks
• Uncertainty Quantification
• +۴ مورد دیگر

Dr. Matias Valdenegro Toro is an Assistant Professor of Machine Learning at the University of Groningen within the Faculty of Science and Engineering and the Artificial Intelligence department of the Bernoulli Institute. He holds a PhD from Heriot-Watt University (2019) and a Master's in Autonomous Systems from Bonn-Rhein-Sieg University of Applied Sciences (2014). His research focuses on trustworthy machine learning models , particularly in uncertainty quantification , medical AI , and robotics , with applications in computer vision and explainable AI. He teaches courses like Introduction to Machine Learning and Deep Learning at the Bachelor and Master levels. His work emphasizes robustness in AI systems, including uncertainty estimation for medical applications, super-resolution techniques, and neuromorphic robotics. He has published widely on topics like Bayesian neural networks, prompt tuning, and sanity checks for explanations. Notable awards include Best Reviewer at ICML (2024) and Highlighted Reviewer at ICLR (2022). He collaborates with institutions like the German Research Center for Artificial Intelligence and actively contributes to open-source datasets (e.g., the Japanese Uncertain Scenes Dataset ). Key grants and activities include organizing the ENLIGHT BIP Course on Deep Learning for Forestry and teaching at the European Summer School on AI . His research also addresses regulatory challenges like the EU AI Act's implications for uncertainty quantification in general-purpose AI.

Mitra Nasriمشاهده پروفایل

استادیار

• Real-Time Systems
• Embedded Systems
• Scheduling Algorithms
• +۴ مورد دیگر

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.

Giovanni Silenoمشاهده پروفایل

مدرس

• Artificial Intelligence
• Logic Programming
• Knowledge Representation
• +۵ مورد دیگر

Giovanni Sileno is an academic specializing in Artificial Intelligence, Logic Programming, and Knowledge Representation, with teaching appointments at the University of Amsterdam, EPITA Paris, and Université Pierre et Marie Curie. His primary affiliation is with the Informatics Institute at the University of Amsterdam where he serves as a Lecturer. His research interests span multiple domains within computer science, focusing particularly on formal methods for normative systems, agent-based programming, and logic-based knowledge representation. His work bridges theoretical computer science with practical applications in policy modeling, forensic science, and business information systems. Dr. Sileno has developed several notable software projects including AgentScriptCC for single-threaded intentional agents, DCPLschema for normative policy specifications, and libraries for normative primitives in Answer Set Programming. His GitHub activity shows consistent contributions from 2012 through 2025, indicating active engagement in both research and development. His publications reflect a strong focus on formal methods applied to practical problems, with particular emphasis on normative systems, agent architectures, and logic programming applications. The research trajectory shows evolution from foundational topics in logic and numeral systems toward increasingly sophisticated applications in policy modeling and agent-based systems. As an educator, he has taught across multiple institutions and disciplines, covering topics from basic programming paradigms to advanced knowledge representation and formal modeling techniques. His teaching spans undergraduate to master's level courses in information studies, cognitive science, data science, and forensic science.

Johannes Hölzlمشاهده پروفایل

پژوهشگر

• Formal Verification
• Probabilistic Programming
• Markov Chains
• +۷ مورد دیگر

Johannes Hölzl is a Post-doctoral Researcher in the Faculty of Science , specifically within the Department of Computer Science at Vrije Universiteit Amsterdam . He works in the Section of Theoretical Computer Science , focusing on formal verification and probabilistic systems. His research integrates higher-order logic with programming languages to model and verify complex computational processes. Position: Post-doctoral Researcher Institution: Vrije Universiteit Amsterdam Department: Computer Science Section: Theoretical Computer Science Hölzl's research spans formal verification, probabilistic programming, and concurrency. He has contributed extensively to the Isabelle/HOL proof assistant, formalizing mathematical structures like measure theory, Markov chains, and timed automata. His work bridges theoretical analysis with practical verification tools, ensuring rigorous proofs in automated reasoning. His publications highlight advancements in probabilistic systems, including formalizing Markov decision processes (2017), verifying compilers for probability density functions (2015), and analyzing expected running times of probabilistic programs (2016). The 2025 article on probabilistic timed automata indicates ongoing exploration of concurrent probabilistic models. Hölzl has no explicitly listed scientific awards in the provided texts. His collaborations with researchers like Tobias Nipkow and Andrei Popescu underscore interdisciplinary efforts in formal methods and security verification. He contributes to the Theoretical Computer Science Section at VU Amsterdam, advancing foundational research in logic-based programming and probabilistic modeling.

Marielle Stoelingaمشاهده پروفایل

استاد

• Predictive Maintenance
• Formal Methods
• Fault Tree Analysis
• +۷ مورد دیگر

Prof. Marielle Stoelinga is a Professor at the University of Twente, Netherlands, working within the Electrical Engineering, Mathematics and Computer Science faculty in the Formal Methods and Tools department. She leads significant research initiatives in formal methods with applications to safety, security, and reliability engineering. Her research spans predictive maintenance , fault tree analysis , attack tree modeling , and the integration of safety and security through formal methods. She focuses on applying big data analytics to predict system failures, with particular emphasis on critical infrastructure including railway systems, satellite missions, and nuclear reactors. Her work bridges theoretical formal methods with practical applications in asset management. Analysis of her recent publications reveals a strong trend toward integrating safety and security analysis through attack-fault-defense trees, developing formal frameworks for risk assessment, and applying model checking techniques to real-world maintenance problems. Her research increasingly addresses the human and organizational aspects of predictive maintenance systems while maintaining rigorous formal foundations. 5 million euros research grant from Dutch National Organization for Scientific Research (NWO) for PrimaVera project Prof. Stoelinga leads the PrimaVera research project ( Predictive maintenance for Very effective asset management ), which takes a holistic approach to predictive maintenance spanning sensor systems, data science, maintenance optimization, and human factors. Her research group actively contributes to formal methods applications in critical infrastructure sectors including energy, transportation, and aerospace.

• Process Mining
• Process Modelling and Simulation
• Distributed Computing
• +۵ مورد دیگر

Claudio di Ciccio is an Associate Professor at the Department of Information and Computing Science within the Faculty of Science at Utrecht University, Netherlands. Previously, he worked with the Department of Computer Science of Sapienza University of Rome (Italy) and the Institute for Information Business of the Vienna University of Economics and Business (WU Vienna), Austria. He received his PhD in Computer Science and Engineering in 2013 from Sapienza University. His research interests span across Process Mining, Formal Methods, Automated Reasoning, and Blockchain & Distributed Ledger Technologies. He has developed expertise in Process Modelling and Simulation, Distributed Computing, Logic, and Artificial Intelligence. His work bridges theoretical formal methods with practical applications in business process management and decentralized systems. His recent publications focus on advancing Process Mining techniques while addressing critical challenges in data privacy and security, particularly in decentralized environments. His research explores the intersection of visual analytics and process mining, developing innovative approaches for multi-faceted process information analysis through time and space. He has made significant contributions to formal methods for process specification verification and constraint satisfaction. Member of the Steering Committee of the IEEE Task Force on Process Mining General Chair of the Conference on Process Mining (ICPM) in 2023 PC chair of ICPM in 2021 PC chair of the Conference on Business Process Management (BPM) in 2022 PC chair of the Blockchain Forum at BPM in 2019 and 2024 Di Ciccio has been actively involved in numerous significant research projects related to process mining, blockchain applications, and formal methods. His work demonstrates a consistent focus on developing practical tools and frameworks that address real-world challenges in business process management while maintaining strong theoretical foundations. His research group appears to focus on the intersection of process science with emerging technologies, particularly in secure and decentralized environments.

• Stochastic Modeling
• Model Checking
• Hybrid Systems
• +۴ مورد دیگر

Dr. Anne K.I. Remke is a Full Professor in the Department of Mathematics of Operations Research at the University of Twente's College of Engineering. Her research focuses on stochastic modeling, hybrid systems, and formal verification techniques, with applications in energy systems, cybersecurity, and healthcare. She contributes to UN Sustainable Development Goals related to affordable and clean energy (SDG7) and industry innovation (SDG9). Her recent work includes developing stochastic hybrid system specifications, intrusion detection systems for smart grids, and parameter estimation methods for battery models. She has collaborated internationally on projects involving energy distribution networks and cybersecurity infrastructure. Remke has supervised 3 PhD students and maintains an active publication record with over 76 research outputs since 2004. Her technical expertise spans model checking algorithms, probabilistic verification, and algorithm design for infinite-state systems. She frequently publishes in peer-reviewed journals like Energy Informatics and conferences such as E-Energy and IEEE CSR, focusing on real-world applications like smart grid communication and energy management optimization.

Anton J. Wijsمشاهده پروفایل

دانشیار

• Parallel Software Development
• Formal Verification
• Model Checking
• +۴ مورد دیگر

Anton J. Wijs is an Associate Professor at the Eindhoven University of Technology (TU/e) , affiliated with the Model-Driven Software Engineering group within the Department of Software Engineering and Technology . His research focuses on parallel software development and leveraging parallelism to enhance formal verification techniques. He holds leadership roles as a Board Member of the European Association for Programming Languages and Systems (EAPLS) and a member of the Steering Committee of ETAPS. Academic Background: Wijs earned his PhD in Computer Science from VU Amsterdam (2007), followed by postdoc positions at INRIA (France), TU/e, and RWTH Aachen University (Germany). He transitioned to an Assistant Professor role at TU/e in 2015 and became an Associate Professor in 2023. Research Interests: His work emphasizes scalable verification methodologies using GPUs, formal analysis of concurrent systems, and tools like mCRL2 . He collaborates with industry partners such as ASML and Codeplay Software to bridge academic research with practical applications. Awards & Grants: Notable achievements include the Best Student Paper Award (FACS 2017) , the Amazon Research Award (2022) , and an NWO grant for GPU-accelerated state space analysis. He co-led the GEARS project (2017–2022) , focusing on efficient parallel model checking. Teaching: Wijs teaches courses on Programming , Program Verification Techniques , and Digital Twins of Medical Devices . He actively supervises students and contributes to international conferences as a program chair and reviewer.

Matthias Volkمشاهده پروفایل

استادیار

• Formal Methods
• Probabilistic Model Checking
• Safety-Critical Systems
• +۳ مورد دیگر

Matthias Volk is an Assistant Professor in the Formal System Analysis group at Eindhoven University of Technology (TU/e). His research focuses on improving the safety and reliability of complex systems through formal methods, particularly probabilistic model checking. He develops automated techniques for system modeling and analysis, with a focus on industrial applications. He is a core developer of the Storm model checker. Academic Background: B.Sc. and M.Sc. in Computer Science from RWTH Aachen University Ph.D. from RWTH Aachen University, supervised by Joost-Pieter Katoen Postdoctoral researcher at the University of Twente Joined TU/e as an Assistant Professor in 2023 Research Interests: Probabilistic model checking Safety-critical systems Automated verification tools Industrial collaborations for formal methods Grants and Funding: NWO grant NWA.1160.18.238 (PrimaVera) ERC Consolidator Grant 864075 (CAESAR) EU Horizon 2020 project MISSION (101008233) Labs/Teams: Part of the Formal System Analysis group and Algorithms and Logics for Verification group at TU/e.

Burcu Kulahcioglu Ozkanمشاهده پروفایل

استادیار

• Formal Methods
• Software Testing
• Concurrent Systems
• +۷ مورد دیگر

Burcu Kulahcioglu Ozkan is an Assistant Professor and Delft Technology Fellow at the Delft University of Technology (TU Delft) Software Engineering Research Group (SERG). Her research bridges formal methods with software engineering to enhance the reliability of concurrent and distributed systems , with applications in blockchain systems and graph databases . Recipient of Amazon Research Award (2022) and Stellar Academic Research Grant (2023) Founder of the FORSE Lab , focusing on lightweight formal methods for software engineering Co-PI of Ripple’s UBRI program at TU Delft, targeting blockchain testing Co-leader of the TU Delft-JetBrains AI4SE collaboration track Her research spans model checking , debugging , and fuzz testing , addressing challenges in event interleavings and network faults in distributed systems. She has received multiple best paper awards , including OOPSLA’23 Distinguished Paper and ICGT’25 Best Software Science Paper . She serves on program committees for major conferences like ICSE’26 , CAV’25 , and ECOOP’25 , and has delivered invited talks at VLDB Summer School (2025), Sabanci University (2024), and Dagstuhl Seminars (2023).

Valentin Robuمشاهده پروفایل

استاد

• Artificial Intelligence
• Decentralized Energy Systems
• Multi-Agent Systems
• +۴ مورد دیگر

Valentin Robu is a Full Professor of Artificial Intelligence for Decentralized Energy Systems at Eindhoven University of Technology (TU/e). He is a Senior Researcher at CWI (National Research Institute for Mathematics and Computer Science, Amsterdam) and holds a visiting appointment at Princeton University's ECE department. His core expertise lies in multi-agent systems and distributed AI, with a focus on applying AI to energy challenges like smart grids, electric vehicle coordination, and renewable integration. He has authored over 150 peer-reviewed publications and won awards such as the 2019 UK Innovation of the Year Award and the 2018 Low Carbon Transport Award. Education and Career: Robu earned his PhD from TU Eindhoven and CWI (2009). Before his current roles, he was an Associate Professor at Heriot-Watt University (UK), a Senior Research Fellow at the University of Southampton, and held visiting roles at Harvard and MIT. He collaborates globally with institutions like MIT, Harvard, and TU Delft. Research Interests: His work addresses challenges in decentralized energy systems, including AI-driven grid optimization, game-theoretic models for renewable integration, and blockchain applications in energy trading. He focuses on ensuring grid stability, fair resource sharing, and sustainable energy access. Awards: In addition to his Innovation and Low Carbon Transport awards, he has been recognized as a 'Best Reviewer' in 2018. His research impacts UN Sustainable Development Goals related to affordable energy and climate action. Grants and Projects: He leads projects like CESI (UK Energy Systems Integration), CEDRI (India Demand Reduction), and ORCA (Offshore Robotics Hub). His work is featured in media outlets like the BBC, Economist, and World Economic Forum. Labs and Teams: He contributes to TU/e's EAISI (Eindhoven AI Systems Institute) and CWI's Intelligent and Autonomous Systems Group. Collaborations span academia and industry, including Scottish Power Energy Networks and Microsoft Research.

• Formal Methods
• Model Checking
• Probabilistic Systems
• +۳ مورد دیگر

David N. Jansen is a Researcher at the University of Twente's Department of Formal Methods and Tools. His work focuses on formal methods, probabilistic model checking, and algorithmic tools for software verification. He has contributed to the development of the probabilistic model checker MRMC and conducted extensive research on binary decision diagrams (BDDs) for symbolic model checking. His research interests include formal verification techniques, probabilistic systems analysis, and the optimization of computational methods in software engineering. He has published on topics such as BDD package comparisons, scheduling algorithms under uncertainty, and the performance evaluation of model checking tools. Jansen's work aligns with advancements in formal methods and their applications in ensuring software reliability and efficiency. His publications span conference proceedings, journals, and technical reports, reflecting a strong emphasis on both theoretical foundations and practical tool development.