جستجوی استاد راهنمای دانشگاهی

Gerrit Van Onsem is a postdoctoral researcher in High Energy Physics at the Department of Physics within the Faculty of Science and Bio-engineering Sciences at Vrije Universiteit Brussel (VUB). With a substantial research output of 549 publications and an impressive h-index of 100 based on over 44,197 citations, he is an active contributor to the CMS Collaboration at CERN. His research interests span High Energy Physics, Particle Physics, Collider Physics, and the CMS Experiment, with specialized focus on Higgs Boson Physics, Quark Physics, Lepton Physics, Quantum Chromodynamics, and Beyond Standard Model Physics. The fingerprint analysis of his work shows dominant activity in collisions (100%), protons (43%), luminosity (37%), quarks (37%), leptons (34%), bosons (31%), cross sections (29%), and transverse momentum (27%). His recent publications (2024-2025) demonstrate significant contributions to Higgs boson measurements, heavy ion physics, searches for new physics beyond the Standard Model, and precision measurements of fundamental particles. His work primarily involves analyzing data from the Large Hadron Collider, with particular emphasis on proton-proton and heavy ion collisions at various energy levels. Dr. Van Onsem has participated in numerous CMS-related activities including the CMS Physics Week (2015), CMS detector Control and Safety shifts, and specialized workshops on top quark physics and vector-like quarks. His research collaborations span international institutions as evidenced by the global nature of the CMS Collaboration.

• High Energy Physics
• Particle Physics
• Collider Physics
• +۶ مورد دیگر

Xavier Devroey is an Assistant Professor of Software Engineering at the Faculty of Computer Science , University of Namur , where he co-leads the SNAIL Team . His research focuses on test automation for search-based and model-based software testing , test suite augmentation , DevOps , and variability-intensive systems . PhD in Computer Science (University of Namur, 2017) Master in Computer Science (University of Namur, 2010) Recent research highlights include: Automated Android safety/security audits (A3S3, 2025) REST API benchmarking infrastructure (2025) Energy consumption analysis through test execution (2025) Fuzzing approaches for Odoo integration testing (FuzzE, 2025) Scientific recognitions: 1st place Java Test Case Generation Tool Competition (2025) VAMOS 2024 Ten-Year Most Influential Paper SSBSE 2020 Best Paper Award ICST 2024 Distinguished Reviewer AST 2023 PC Reviewer Star He actively supervises PhD and master's students while organizing international conferences like ISSTA (2025) and Belgium-Netherlands Software Evolution Workshops (2024).

• Software Engineering
• Test Automation
• Search-Based Testing
• +۵ مورد دیگر

Gilles Perrouin is a Research Professor in the Faculty of Computer Science at the University of Namur, affiliated with the Research Center on Information Systems Engineering and the Namur Digital Institute. His expertise spans Software Engineering, Testing, Artificial Intelligence, and Machine Learning, with a focus on software product lines, configuration management, and automated testing techniques. He leads projects such as SQUAL.AI (Software Quality through Artificial Intelligence) and SmartTune (Hyper-parameter Optimization for Deep Learning). Perrouin has received awards including the Distinguished Reviewer Award (2023 and 2019) and the VAMOS 2024 ten-year Most Influential Paper Award. He actively participates in organizing conferences like the Belgium-Netherlands Software Evolution Workshop and contributes to initiatives promoting diversity in science, such as Women and Girls in Science events. His research involves advancing testing methodologies for complex systems, exploring energy-efficient neural architectures, and addressing fairness in machine learning. Collaborations span international institutions, reflecting his global impact in software engineering and AI.

• Software Engineering
• Testing
• Artificial Intelligence
• +۳ مورد دیگر

Pierre Yves Schobbens is a Professor of Computer Science at the Université Catholique de Louvain, specializing in software product lines verification, formal methods, and agent-oriented programming. He holds leadership roles including President of the Precise research center and the international affairs commission of the Faculty of Computer Science. His research focuses on software reliability, energy-aware systems, and real-time systems. Education: Bachelor in Philosophy (1982) Master in Applied Mathematics and Economics (1983) Master in Computer Engineering (1984) Doctorate in Computer Science (1993) Research Interests: Software Product Line Verification Model Checking Formal Methods for Real-Time Systems Energy Efficiency in Neural Architectures Agent-Oriented Programming Key Contributions: Development of featured transition systems for variability analysis Advances in mutation testing for timed systems Tools like ProVeLines for software product line verification Awards: Most influential paper award (IEEE RE 2016) Best paper (SAFECOMP 2012) 2024 VAMOS Ten-Year Most Influential Paper Award Grants & Projects: Lead on SQUAL.AI (AI-driven software quality) ERNEST (energy-efficient IoT scheduling) CFV (Center for Software Verification) He collaborates extensively with institutions like the Ecole Normale Supérieure and the University of Birmingham, and has supervised over 90 research works.

• Software Product Lines
• Software Verification
• Formal Methods
• +۵ مورد دیگر

Tom Van Cutsem is an Associate Professor of computer science at KU Leuven in Belgium, where he is affiliated with the Distributed and Secure Software (DistriNet) research group within the Faculty of Engineering Science and Department of Computer Science. He also maintains an affiliation with Nokia Bell Labs, where he previously served as a Research Department Head with research interests in decentralized systems, IoT, stream processing and machine learning for software engineering. His academic career includes a previous position as Assistant Professor at Vrije Universiteit Brussel from 2010 to 2014. Dr. Van Cutsem holds a PhD in Computer Science from Vrije Universiteit Brussel. His educational background has provided the foundation for his expertise in distributed systems, programming languages, and software security. His primary research interests span Distributed Systems , Software Security , Blockchain , and Programming Language Design . With the DistriNet research group, he pursues work on decentralized systems, IoT, stream processing, and machine learning for software engineering. His research focuses on making distributed systems more secure, reliable, and accessible, with particular attention to blockchain technology and Web3 infrastructure. He is a founding member of IFIP WG 2.16 on Programming Language Design. His recent publications demonstrate a strong focus on blockchain security and infrastructure, with numerous papers on Web3, smart contracts, and decentralized systems from 2023-2025. His work addresses critical challenges in blockchain validation, smart contract security, and Web3 infrastructure, reflecting his commitment to making decentralized systems more secure and accessible to low-resource participants. Several of his current projects focus on secure middleware for smart contracts and scalable infrastructure for self-sovereign applications. Dr. Van Cutsem supervises PhD students including Weihong Wang, with whom he has co-authored multiple recent publications. He is currently leading several research projects including SODISA (Scalable Software Development and Infrastructure for Self-sovereign Applications), Secure Sandboxing for WebAssembly-based Smart Contracts, and Programming languages for privacy-preserving and verifiable computing, with funding extending through 2028-2029. He leads research within the Distributed and Secure Software (DistriNet) group at KU Leuven, which focuses on creating secure and dependable distributed systems. His team works on cutting-edge challenges in blockchain infrastructure, smart contract security, and decentralized application development, with connections to both academic and industrial partners including Nokia Bell Labs.

• Distributed Systems
• Software Security
• Blockchain
• +۵ مورد دیگر

Boris Cherry is a Research Fellow at the Faculty of Computer Science, University of Liège, specializing in software engineering with focus on static program analysis and database systems. His educational background includes: PhD in Sciences (2024) with thesis on "Empirical Investigation and Static Detection of Code Smells in Applications using Document-Oriented Datastores" Master in Computer Science (2020) with thesis on "JCrashPack2.0: Search-based crash reproduction hardness analysis" Cherry's research centers on static analysis techniques for database applications, particularly MongoDB. He investigates code smells, crash reproduction mechanisms, and software quality metrics through empirical studies and tool development. His work bridges theoretical program analysis with practical database application challenges, emphasizing empirical validation and reproducibility in software engineering research. Publication trends (2020-2024) reveal consistent specialization in MongoDB-related static analysis, evolving from crash reproduction studies to comprehensive code smell detection frameworks. His research combines database theory, software quality metrics, and empirical validation methods, with strong emphasis on tool development for practical industry application. Cherry actively contributes to academic community building through event organization, including co-organizing the 2024 PhD Student Day for the Faculty of Computer Science. His collaborative work with the Software Evolution and Analysis Group demonstrates strong institutional integration and interdisciplinary research approaches.

• Static Program Analysis
• Software Engineering
• Database Systems
• +۲ مورد دیگر

Freya Blekman is a Professor at the Free University of Brussels , specializing in High Energy Physics and Particle Physics . As a key member of the CMS collaboration , her work focuses on Physics Beyond the Standard Model , Higgs Boson Research , and Collider Experiments . She contributes to Dark Matter searches, Jet Physics , and Machine Learning applications in particle identification. Education : Not explicitly stated Research Trends Her recent publications (2023–2025) emphasize transformer-based neural networks for quark jet tagging, azimuthal correlations in photon-lead collisions, and double-parton scattering studies. Keywords include proton collisions , Higgs bosons , and quantum chromodynamics , reflecting her dual focus on fundamental research and advanced detector technologies. Scientific Awards CMS LPC Distinguished Researcher (2013, 2020) Jaarprijs Wetenschapscommunicatie (2016) Science Magazine Breakthrough of the Year (2012) for Higgs boson discovery High Energy and Particle Physics Prize (2019) Advising & Grants She supervised doctoral research on Dark Matter+Higgs decays and secured grants for CERN programs , HL-LHC upgrades , and international collaborations with Switzerland . Labs & Teams Active in the CMS experiment at CERN and Future Circular Collider studies, she collaborates with teams on detector R&D , data analysis , and theoretical extensions of the Standard Model.

• High Energy Physics
• Particle Physics
• Physics Beyond the Standard Model
• +۴ مورد دیگر

Pieter Leyman serves as an Assistant Professor in Sustainable Production Processes within the Industrial Systems Engineering (ISyE) research group at Ghent University's Faculty of Engineering and Architecture. He maintains an affiliate membership with Flanders Make, the strategic research center for the Flemish manufacturing industry. Education: PhD in Applied Economic Sciences from Ghent University (2016) Postdoctoral research at KU Leuven and University of Antwerp Research stay at Leiden University, Netherlands Research Focus: Dr. Leyman specializes in developing metaheuristic algorithms for NP-hard combinatorial optimization problems, integrating them with machine learning techniques to enhance performance. His work centers on energy-aware production scheduling to drive sustainability, with core expertise in optimization, explainable AI, and instance hardness analysis. Current projects address carbon-aware scheduling for GHG reduction and counterfactual explanations in AI systems. Publication Trends: Recent work (2022-2025) demonstrates a clear trajectory toward sustainable manufacturing solutions, with 60% of publications focusing on carbon-aware scheduling and energy optimization. His research bridges combinatorial optimization (particularly knapsack problem variants) with machine learning, yielding novel approaches like the NICE algorithm for counterfactual explanations. The work consistently targets industrial applications in manufacturing and transportation systems. Collaborations and Infrastructure: As part of ISyE and Flanders Make, Leyman engages in industry-academia partnerships focused on manufacturing innovation. His research leverages computational infrastructure for large-scale optimization and AI integration, with ongoing projects in net-zero manufacturing and competence-aware scheduling systems.

• Combinatorial Optimization
• Metaheuristics
• Scheduling
• +۵ مورد دیگر

Mattias Guns is an Associate Professor in the Department of Computer Science at the Faculty of Engineering Science, KU Leuven. He is a core member of the Declarative Languages and Artificial Intelligence (DTAI) research unit and holds affiliations with Leuven.AI and the KU Leuven Institute for Mobility (LIM). He serves on the Council of the Faculty of Engineering Science and the Programme Committees for Artificial Intelligence and Mobility and Supply Chain. His research centers on bridging Artificial Intelligence with constraint-based optimization, focusing on Explainable AI, Predict-and-Optimize frameworks, and machine learning integration for constraint solving. Key interests include human-centric explainability in decision systems, perceptual reasoning, and energy-efficient optimization models. His work addresses fundamental challenges in program synthesis, scheduling, and trustworthiness of AI planning systems. Recent publications reveal strong trends in fusing machine learning with declarative problem-solving paradigms. Notable themes include LLM-driven constraint modeling, mutational testing for solvers, step-wise explanation generation, and preference learning for unsatisfiable constraints. His research consistently targets real-world applications in supply chain optimization, inventory management, and perceptual reasoning systems. As principal investigator, he leads multiple major projects: TED-AI: Trustworthy Explanations for Decision Making in AI (2025) Towards Human-Centric Explainable Constraint Solving (2025-2028) SAELING: Energy Optimization via Learning (2024-2027) From Natural Language to Constrained Optimization (2023-2027) He has supervised PhD student Mulamba Ke Tchomba on machine learning-enhanced constraint solvers for perceptual reasoning. Within the DTAI research group, he contributes to KU Leuven's leadership in declarative AI through collaborative work on constraint programming foundations and applications. His team actively develops open-source tools like CMPpy for prediction-optimization integration and participates in European AI initiatives through Leuven.AI.

• Artificial Intelligence
• Constraint Programming
• Optimization
• +۳ مورد دیگر

Brecht Vermeulen is a Postdoctoral Researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology. He works within the Internet Technology and Data Science Lab, focusing on networking, video quality assessment, and energy-efficient systems. Research Areas: Quality of Experience (QoE), Dynamic Spectrum Sharing, Video Coding, Interoperability Testing, Federated Experimentation. Key Collaborations: IMEC, FIRE initiative, EU-US/South Korea partnerships. Research Focus: Vermeulen's work spans scalable video coding, distributed CORBA monitoring, and energy efficiency in telecommunications. He applies genetic programming to video quality metrics and explores AI-driven radio systems for spectrum sharing. Publication Trends: His recent articles address zero vulnerability computing hypotheses, healthcare robotics during pandemics, and federated testbed architectures. Earlier works focus on QoE for video, thin client power efficiency, and tunnel setup mechanisms.

• Computer Science
• Networking
• Quality of Experience (QoE)
• +۵ مورد دیگر