جستجوی استاد راهنمای دانشگاهی

Grégoire DANOY is a Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability, and Trust (SnT) and Head of the Parallel Computing and Optimization Group (PCOG). He specializes in artificial intelligence, with a focus on optimization algorithms, machine learning, and swarm intelligence. His work addresses challenges in cloud computing, high-performance computing, smart mobility, and unmanned autonomous systems like drone swarms. He has authored over 150 publications, including articles in IEEE Transactions and conferences like NeurIPS and GECCO. He currently leads major projects such as UltraBO (€1.019M), ADHOC (€1.291M), and SERENITY (€1.228M), collaborating with institutions in France and Poland. Education: PhD in Computer Science (2008) from École Nationale Supérieure des Mines de Saint-Étienne, Master’s in Computer Science (2004), and Industrial Engineering Degree (2003) from Luxembourg University of Applied Sciences. Research Interests: Developing novel AI techniques for solving large-scale optimization problems, with applications in distributed systems, autonomous robotics, and federated learning. He emphasizes scalable solutions for combinatorial challenges using parallel computing and swarm intelligence. Grants & Projects: Principal Investigator for EU-funded initiatives like ADARS (2021–2024) and FNR PoC/SIMMS (2019–2021). His work bridges academia and industry, with technology transfer projects in autonomous robot swarms. Awards: Recognitions include the Best Student Paper Nomination (2022), IEEE CybConf Best Paper Award (2017), and ACM GECCO nominations (2016, 2009). He serves on the editorial board of Engineering Applications of Artificial Intelligence (EAAI). Labs & Teams: Leads the Parallel Computing and Optimization Group (PCOG), focusing on interdisciplinary research in AI and distributed systems. He also contributes to outreach programs like FNR's Researchers at School.

• Artificial Intelligence
• Optimization Algorithms
• Machine Learning
• +۵ مورد دیگر

Pascal BOUVRY is a full Professor of parallel computing and optimization techniques at the University of Luxembourg's Department of Computer Science , within the Faculty of Science, Technology and Medicine (FSTM) . He currently serves as the Dean of the FSTM and leads the Parallel Computing and Optimisation group . Additionally, he oversees the University's High Performance Computing (HPC) infrastructure. His research focuses on parallel computing, optimization algorithms, distributed systems, and their applications in bioinformatics and distributed environments. Prof. BOUVRY holds a Ph.D. in Computer Science from the University of Grenoble (France) and has extensive industry experience, including roles as CEO/CTO of tech firms and leadership in telecom and financial services sectors. He has pioneered initiatives like the Master in High-Performance Computing and Technopreneurship programs at the University of Luxembourg. His research interests span GPU programming paradigms , federated learning , distributed optimization , and trustworthy AI . Recent work includes advancements in HPC education frameworks, federated learning frameworks (e.g., FedPref), and quantum circuit optimization. He contributes to editorial boards of journals like IEEE Transactions on Sustainable Computing and IEEE Cloud Computing Magazine. Prof. BOUVRY has held international leadership roles, including as Honorary Chair of conferences and active participation in technical committees. His educational efforts emphasize bridging academic research with industrial applications, particularly in HPC and AI.

• Parallel Computing
• Optimization Techniques
• High-Performance Computing (HPC)
• +۵ مورد دیگر

Pierre KELSEN is a Full Professor in the Department of Computer Science at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM). His research focuses on Software Engineering, Formal Methods, Model-Driven Engineering, and Algorithmic Graph Theory. He leads the LASSY Laboratory for Advanced Software Systems, emphasizing model decomposition, regulatory compliance, and formal verification techniques. Education: PhD in Computer Science (1993, University of Illinois at Urbana-Champaign), M.Sc. (1989, UIUC), and Diploma (1986, University of Karlsruhe). Postdoctoral work at the University of British Columbia and Max-Planck-Institut für Informatik. Research Interests: - Development of formal modeling languages (e.g., VCL, F-Alloy) - Model transformation and validation frameworks - Algorithms for compliance and complexity challenges - Visual and modular design methodologies Funding: - ASINE (FNR Pearl, 2013–present): Architecture-based service innovation - MaRCo (FNR Core, 2010–2013): Business-centric regulatory compliance Publications span model-driven engineering, formal methods, and algorithmic foundations, with recent work exploring AI integration in domain modeling and compliance analysis. Labs/Teams: LASSY Laboratory, collaborating on tools like Lightning and Democles for executable modeling frameworks.

• Software Engineering
• Formal Methods
• Model-Driven Engineering
• +۴ مورد دیگر

Alfredo Capozucca is a full permanent Researcher at the Department of Computer Science (DCS) within the Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg. He holds a PhD in Computer Science from the University of Luxembourg (2010) and an M.S. from the National University of Rosario, Argentina (2003). His research focuses on modern software engineering methods, dependable systems, and computing education, with an emphasis on formal verification and sustainable computing practices. Capozucca has contributed to the design of courses at undergraduate and master's levels, including serving as Deputy Programme Director for the BSc in Computer Science from 2021-2024. His work bridges theoretical foundations with practical applications in education and industry. Research interests prominently include AI in education (e.g., ChatGPT's role in formal specification writing), formal verification techniques, and the integration of DevOps philosophies into academic curricula. He has authored numerous papers on topics ranging from security policy analysis to energy-efficient transactional models. Capozucca's contributions extend to open-source projects and tool development, such as the Messir UML requirements engineering tool. His teaching spans software engineering fundamentals, dependability, and modern DevOps practices, reflecting a commitment to aligning education with industry needs. Key professional roles include R&D engineer positions (2004-2006) and leadership in educational program design. His research infrastructure is based at the Maison du Nombre facility in Luxembourg. While no specific grants or awards are listed, his extensive publication record and teaching contributions highlight sustained academic engagement.

• Software Engineering
• Dependable Systems
• Computing Education
• +۳ مورد دیگر

Dr. Jose Luis SANCHEZ LOPEZ is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) of the University of Luxembourg, leading the Aerial Robotics Lab (AeRoLab) within the Automation & Robotics Research Group (ARG). He joined SnT in 2017 as a Postdoc Research Associate, promoted to Research Scientist in 2021. His research focuses on autonomous robotics, particularly aerial systems, emphasizing situational awareness, SLAM, and trajectory planning. Education: Ph.D. in Robotics (2017), M.Sc. in Automation & Robotics (2012), and Engineering degree in Industrial Engineering (2010), all from the Technical University of Madrid. Visiting Research: Arizona State University (2012), LAAS-CNRS (2014–2016). Research Interests: Multi-agent robotic systems, sensor fusion, localization/mapping, computer vision, machine learning, and trajectory control. He has authored over 56 peer-reviewed publications, with an h-index of 18. Projects: Leads projects like DEUS (PI), NEDA, ÄerdFly (PI), and RoboSAUR. Contributions span European, Luxembourg, and Spain-funded initiatives, focusing on autonomous systems, 5G integration, and construction-site robotics. Teaching: Lectured in MICS, BiCS, BING (Uni.lu) and GITI (UPM). Actively involved in academic service as a reviewer, editor, and competition participant (e.g., IMAV, IARC). Outreach: National Coordinator for Luxembourg’s Robotics European Week, promotes robotics education in schools and public events.

• Robotics
• Autonomous Systems
• Computer Vision
• +۵ مورد دیگر

Prof. Michael HALLING is a Full Professor in Sustainable Finance at the University of Luxembourg's Faculty of Law, Economics and Finance, Department of Finance. His work focuses on sustainable finance, corporate finance dynamics, climate risk assessment, and financial regulation. He holds the prestigious Chair in Sustainable Finance and has published extensively on topics like MiFID II compliance, mutual fund fee structures, and post-pandemic market recovery. Contact: michael.halling@uni.lu Research Interests : Prof. HALLING’s research bridges theoretical finance with practical applications, emphasizing sustainable investment practices, corporate debt management, and regulatory frameworks. Key themes include: Climate risk modeling using public news sentiment analysis Impact of behavioral preferences on corporate investment decisions Automated compliance systems for financial institutions Market dynamics during crises (e.g., pandemic effects on capital access) Recent Publications Trends : Recent works analyze MiFID II regulatory impacts (2024), stochastic modeling of corporate investment (2023), and firm-specific climate risk quantification. His 2020 studies explored pandemic-driven shifts in corporate financing strategies. Awards : No awards explicitly mentioned in the provided texts. Grants & Advising : No student advisees or grant details provided in available data. Labs/Teams : No specific research group affiliations listed.

• Sustainable Finance
• Corporate Finance
• Climate Risk Assessment
• +۵ مورد دیگر

Mike Papadakis is an Associate Professor at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), where he leads the SerVal research group. His research focuses on software engineering, software security, and artificial intelligence. He holds a PhD in Software Testing and Verification from Athens University of Economics and Business, with an MSc and BSc from the same institution. His research explores mutation testing, machine learning applications in software development, and test optimization. Recent publications demonstrate a strong emphasis on AI robustness, flaky test analysis, and automated debugging techniques. Notable achievements include the IEEE TCSE Rising Star Award (2020) and 12 additional research awards. He has published over 100 peer-reviewed articles and delivered more than 30 invited talks globally.

• Software Engineering
• Software Security
• Artificial Intelligence

Maxime CORDY is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) , University of Luxembourg, within the Security, Design and Validation group (SerVal) . He holds a PhD from the University of Namur (Belgium, 2014) and specializes in software engineering, applied artificial intelligence, and cybersecurity. His work focuses on adversarial machine learning, deep learning robustness, and model checking for critical systems. Research interests include adversarial attacks on tabular data , energy system optimization , code understanding models , and software quality assurance . Recent projects address challenges in secure AI deployment, automated test generation, and fault detection in large language models. Publications emphasize empirical studies on adversarial defenses, data augmentation for code models, and energy consumption forecasting. He contributes to tools like Daedalux (variability-aware model checking) and benchmarks like Tabularbench for adversarial robustness evaluation. Current affiliations include leadership within the SerVal group and collaborations on interdisciplinary projects such as MALETSQUE (Machine Learning Techniques for Software Quality Evaluation). His work bridges theoretical computer science with practical applications in energy systems, medical imaging, and space program design.

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Konstantinos KANAVOURAS is a Doctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg, specifically in the Space Systems Engineering research group (SpaSys). He is advised by Prof. Andreas Hein and focuses on model-based systems engineering, software development, and aerospace engineering applications in satellite systems. His research integrates agile methodologies and machine learning for spacecraft design and anomaly detection. Kanavouras holds a Master’s degree from Aristotle University of Thessaloniki (2021) and contributed as an avionics engineer to ESA’s AcubeSAT nanosatellite project under the Fly Your Satellite! program. His work emphasizes lightweight data management tools, PocketQube missions like POQUITO, and fractionated satellite systems for planetary observation. His publications highlight trends in small satellite development, including agile systems engineering practices, thermal anomaly detection via machine learning, and adapting space projects to remote collaboration (e.g., during the pandemic). Key projects include the University of Luxembourg’s first PocketQube mission (POQUITO) and lean approaches to spacecraft subsystems. Current affiliations include the SpaSys group at SnT, with a focus on interdisciplinary collaboration between systems engineering and software development. No scientific awards are listed, but his work aligns with cutting-edge space technologies and mission design.

• Model-Based Systems Engineering
• Software Development
• Aerospace Engineering
• +۴ مورد دیگر

Prof. Leon van der Torre is a full professor of computer science at the University of Luxembourg, affiliated with the Lab for Intelligent and Adaptive Systems (ILIAS). He specializes in formal models of reasoning and interaction in intelligent systems, with research spanning deontic logic, argumentation theory, cognitive robotics, and compliance technologies. He was granted the Bao Yugang Chair Professorship at Zhejiang University (2023) and has held visiting positions, including at Stanford University's CSLI (2013). His research focuses on integrating logical formalisms with computational systems to address normative reasoning, multiagent coordination, and ethical AI. Key contributions include work on argumentation frameworks, deontic logic applications, and formal models of normative systems. He teaches courses such as 'Introduction to Intelligent Systems' and 'Game Theory', reflecting his expertise in AI and computational reasoning. Prof. van der Torre actively participates in international conferences (e.g., DEON, PRIMA) and has authored over 400 publications. His work bridges theoretical foundations with practical applications, addressing challenges in AI ethics, legal reasoning, and multiagent systems coordination.

• Deontic Logic
• Artificial Intelligence
• Cognitive Robotics
• +۴ مورد دیگر

Nicolas GUELFI is a Full Professor at the University of Luxembourg's Faculty of Science, Technology and Medicine (Department of Computer Science). He has been a faculty member since 1999, leading the Lassy laboratory for over a decade and co-founding the academic Bachelor in Computer Science program. His research focuses on software engineering, dependability, resiliency, formal methods, and AI-driven systems. He has coordinated over 60 staff members on international projects and contributed to standards like ERCIM's RISE and SERENE working groups. Education: PhD in Formal Methods (Paris XI, 1999) Teaching: Software Engineering across universities (Paris XI, EPFL, EPITA) since 1994 Roles: ERCIM Executive Committee member, Expert for Judicial Conformance Trials Research interests emphasize requirements engineering (MESSIR framework), resilient systems, and AI integration. He has pioneered tools like SEMKIS-DSL and MESAS for system specification. His work bridges academia and industry through DevOps education programs and standards analysis. Publications span formal verification, Petri nets, and model-driven engineering. He has advised on high-stakes litigation involving €0.1M–€100M projects, leveraging his expertise in system conformance.

• Software Engineering
• Dependable Systems
• Formal Methods
• +۴ مورد دیگر

Lars BEEX is a Senior Research Scientist at the University of Luxembourg's Faculty of Science, Technology and Medicine, Department of Engineering. He holds the right to supervise PhD students and has directed five to completion. His research focuses on computational mechanics of solids, including Bayesian inference, multiscale methods, and quasicontinuum approaches, with applications to materials like textiles, foams, and medical devices. His academic journey includes a PhD from Eindhoven University of Technology (2008-2012), supervised by Marc Geers and Ron Peerlings, as well as MSc and BSc degrees from the same institution. **Research Interests:** - Computational mechanics of solids - Bayesian inference and uncertainty quantification - Multiscale modeling (quasicontinuum method) - Mechanical modeling of fibrous and discrete materials - Phase-field damage models - Contact mechanics and elastoplasticity **Awards:** - Biezeno Solid Mechanics Award 2013 (Best PhD thesis in solid mechanics, Netherlands) - Cum laude distinction for both MSc and BSc degrees **Industrial Collaborations:** - SISTO Armaturen - IEE - Kiswire International **Teaching:** - Numerical methods for continuous optimization - Courses for Computer Science, Mathematical Modelling, and Engineering students **Lab/Affiliations:** - Legato Team (part of the University of Luxembourg's engineering research cluster)

• Computational Mechanics of Solids
• Bayesian Inference
• Multiscale Methods
• +۵ مورد دیگر

Amal AKLI is a Researcher affiliated with the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), specifically within the Department of Computer Science. She is part of the Security Design and Validation research group (SERVAL), led by Prof. Yves Le Traon. Amal holds a Master’s degree in computer science from the National School of Computer Science in Algeria (2022). Her research focuses on Machine Learning operations (MLops), data science, and software engineering, with a particular emphasis on applying AutoML and few-shot learning techniques to improve software development and testing processes. Her recent publications explore parameter-efficient fine-tuning of pre-trained code models and predicting flaky tests using few-shot learning. While no scientific awards are explicitly mentioned, her work contributes to advancing automated testing and machine learning integration in software engineering. Amal's research aligns with the broader goals of the SERVAL team in enhancing software design and validation methodologies.

• Machine Learning operations (MLops)
• Data Science
• Software Engineering

Stéphane BORDAS is a Full Professor in Computational Mechanics at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), leading the Computational Mechanics (Legato) research group. His work focuses on free boundary problems, method development for complex geometries, and applications in fracture mechanics, biomechanics, and computational engineering. He previously held roles at Cardiff University and the Swiss Federal Institute of Technology in Lausanne (EPFL). His research integrates computational methods like XFEM, isogeometric analysis, and meshfree techniques to address challenges in engineering and medicine. Education: Ph.D. in Theoretical and Applied Mechanics, Northwestern University (2003) M.Sc. in Civil Engineering, École Spéciale des Travaux Publics and Northwestern University (1999) Research Interests: Computational Mechanics, Biomechanics, Finite Element Methods, Fracture Mechanics, High-Performance Computing, Isogeometric Analysis. Grants & Projects: ERC Starting Grant (RealTCut) for surgical simulation and material cutting FP7 ITN INSIST for meshless methods Labs/Teams: Computational Mechanics (Legato) Group at the University of Luxembourg. His work bridges academia and industry, with applications in aerospace, biomedical engineering, and materials science. He is active in open-source software development, including codes for XFEM, isogeometric analysis, and meshfree methods.

• Computational Mechanics
• Biomechanics
• Finite Element Methods
• +۶ مورد دیگر

Benoît ALCARAZ is a Researcher affiliated with the Department of Computer Science at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM). His work focuses on advancing artificial intelligence and machine learning, particularly in ethical AI frameworks, argumentation systems, and natural language processing. He is based at the Maison du Nombre research facility in Esch-sur-Alzette. Research Interests include developing algorithms for ethical decision-making in AI, optimizing machine learning models through evolutionary techniques, and creating user-centric NLP tools for real-time applications. His work bridges theoretical computer science with practical ethical considerations, as seen in his exploration of bias mitigation in visual learning and argumentation-based reinforcement learning agents. Notable contributions include frameworks like Ajar for ethical reinforcement learning and IRRMA for image-based meeting assistants. While no explicit awards or grants are listed, his publications indicate active involvement in interdisciplinary AI research with a focus on societal impact.

• Artificial Intelligence
• Machine Learning
• Argumentation Theory
• +۳ مورد دیگر