جست‌وجوی استاد و پژوهشگر

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

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.

Jose Luis SANCHEZ LOPEZمشاهده پروفایل

پژوهشگر

• Robotics
• Autonomous Systems
• Computer Vision
• +۵ 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.

• Software Engineering
• Software Security
• Artificial Intelligence

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
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

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.

• Model-Based Systems Engineering
• Software Development
• Aerospace Engineering
• +۴ 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.

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

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.

• Non-Terrestrial Networks (NTN)
• 6G Communication Systems
• Satellite Communications
• +۵ مورد دیگر

Eva LAGUNAS is an Assistant Professor and Deputy-Head of the SIGCOM research group at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) , University of Luxembourg. Her expertise lies in Non-Terrestrial Communication Systems , focusing on radio resource management and wireless networks optimization. She holds a Ph.D. and M.Sc. in Telecommunications Engineering from the Polytechnic University of Catalonia (UPC), Barcelona. Key Affiliations & Roles: Principal Investigator (PI) of the FNR CORE project VARRAY-5G (Vehicular Phase Array Antennas for 5G) PI of the CHIST-ERA project SHIELD (Secure Distributed Learning & Smart Contract Ecosystems) Co-PI in the ESA ARTES-funded NeuroSat project (Neuromorphic Processors for SatCom) Deputy-Head of SIGCOM group and active contributor to the TelecomAI-Lab (AI-driven satellite communication) Event organizer: Special Session on ML for NTN at IEEE ICMLCN 2025, Track Chair at EUCNC 2025 Research Interests: Non-Terrestrial Networks (NTN), 6G integration, satellite-ground network convergence, AI-driven optimization, reconfigurable intelligent surfaces (RIS), and neuromorphic computing for onboard processing. She also leads efforts in vehicular communications and energy-efficient satellite payloads. Recent Achievements: 2025: Elected to the EURASIP Board of Directors 2024: Listed in the 100 Brilliant and Inspiring Women in 6G list 2023: Co-authored NeuroSat project's IEEE publication on neuromorphic computing for SatCom Labs & Projects: TelecomAI-Lab : Developing neuromorphic hardware (e.g., Intel Loihi2, BrainChip AKIDA) for satellite applications ESA NeuroSat : Pioneering neuromorphic processors for onboard SatCom resource management Grants & Funding: Secured Luxembourg National Research Fund (FNR) and CHIST-ERA grants for projects like VARRAY-5G and SHIELD, totaling over €2M in research investment.

• Computer Vision
• Deep Learning
• Media Forensics
• +۱ مورد دیگر

Nesryne Mejri serves as a Postdoctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, within the Computer Vision, Imaging & Machine Intelligence (CVI2) research group led by Prof. Djamila Aouada. Her office is located at BLE, E02 011. She earned her Master's degree in Information and Computer Science from the University of Luxembourg in 2021. Her academic trajectory demonstrates a focused progression into advanced visual intelligence research. Dr. Mejri's primary research centers on Computer Vision and Deep Learning , with specialized expertise in media forensics and detection of forged visual content . Her work directly addresses critical security challenges in the digital age, particularly the proliferation of deepfakes and synthetic media manipulation. This research combines theoretical machine learning advances with practical applications for media authentication. As part of the CVI2 group, she contributes to cutting-edge projects developing robust forensic methodologies under Prof. Aouada's supervision. No information is available regarding students she has advised or specific research grants secured. Her current efforts focus on enhancing detection capabilities for increasingly sophisticated visual forgeries.

• Machine Learning
• Deep Learning
• Multi-Agent Systems
• +۳ مورد دیگر

Hedieh HADDAD is a Doctoral researcher at the University of Luxembourg, affiliated with the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the Parallel Computing & Optimization Group (PCOG), headed by Prof. Pascal Bouvry. Her research focuses on Machine Learning (particularly Deep Learning), Multi-Agent Systems, Optimization Algorithms, and Intelligent Transportation Systems. Education : She holds a Master’s degree from Shahid-Beheshti University of Tehran (Iran) , completed in 2019. Previously, she served as a research assistant at the Artificial Intelligence Research Lab. Research Interests : Hedieh’s work emphasizes advanced Machine Learning applications, Multi-Agent Systems for complex problem-solving, and Optimization Algorithms for Intelligent Transportation Systems. Her interdisciplinary approach bridges theoretical advancements with real-world deployment challenges in transportation and computational efficiency. Affiliations : She is part of the Parallel Computing & Optimization Group (PCOG) at SnT, focusing on high-performance computing and optimization strategies.

• Operating Systems
• Fault Tolerance
• Cyber-Physical Systems
• +۵ مورد دیگر

Marcus Völp is an Associate Professor and head of the CritiX research group at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT). His research focuses on ultra-reliable operating systems, fault and intrusion tolerant systems for cyber-physical environments, and hierarchical hybridization techniques to construct resilient computing platforms. His work bridges theoretical foundations with practical implementations, particularly in developing dependable systems-on-chip that can withstand faults and intrusions. Research spans formal verification methods, radiation-hardened hardware, blockchain security, and autonomous vehicle safety systems. Recent publications demonstrate advancement in parameterized system verification, radiation effects on routers, and N-version machine learning for autonomous systems. His group maintains strong focus on practical resilience mechanisms for real-time and critical systems across computing layers.

• IoT
• Decision Support Systems
• Industry 4.0
• +۴ مورد دیگر

Sylvain Kubler is a Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg's SerVal group. He holds a PhD from Université de Lorraine (2013) and previously served as an Associate Professor at the Research Center for Automatic Control of Nancy. His work focuses on IoT applications, decision support systems, and their integration into Industry 4.0, renewable energy, and smart cities. He has contributed to projects involving blockchain consensus mechanisms, maintenance scheduling, and energy system optimization. His research emphasizes sustainable technologies and distributed systems security. Research Interests: IoT and Blockchain Integration Decision Support Systems for Smart Cities and Industry Renewable Energy and Multi-Energy Networks AI-Driven Maintenance and Prognostics Privacy-Preserving Distributed Systems Recent Contributions: Sylvain’s recent work explores adaptive blockchain frameworks (e.g., DRAFTEE), reinforcement learning for maintenance scheduling, and explainable AI (XAI) in prognostics. His articles analyze trade-offs in federated learning architectures and multi-level energy system coordination. Affiliations and Labs: A core member of the SerVal group, he collaborates on initiatives like the IoT-based BIoTope ecosystem and the Sabine blockchain project. His work aligns with Luxembourg’s focus on secure, reliable, and sustainable technological solutions.

• Software Engineering
• Cyber-Physical Systems
• Real-Time Systems
• +۴ مورد دیگر

Seung Yeob SHIN is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. He holds a PhD from the University of Massachusetts Amherst (2016), specializing in software engineering with a focus on system modeling and analysis through simulation and model checking frameworks. His work is centered at the Software Verification and Validation (V&V) Lab , led by Prof. Lionel Briand. Research Interests: Software Engineering Methodologies Cyber-Physical Systems Testing Real-Time Systems Analysis AI-Driven Testing Techniques Model Checking & Simulation Key Contributions: Pioneering work on fuzzing techniques for SDN controllers Development of probabilistic WCET estimation methods Advancements in metamorphic testing for CPS Control theory-based stress testing frameworks Publications: Over 30 peer-reviewed articles focusing on testing methodologies for real-time systems, cyber-physical systems, and quantum programming analysis. Recent trends emphasize AI integration in software validation and uncertainty-aware system design. Labs & Teams: Active member of the V&V Lab, collaborating on hardware-in-the-loop testing and embedded system validation projects.

Luis A. Leivaمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Machine Learning
• Computational Interaction
• +۱۲ مورد دیگر

Luis A. Leiva is an Assistant Professor in the Department of Computer Science at the University of Luxembourg’s Faculty of Science, Technology and Medicine. He leads the Computational Interaction research group and serves as director of the Interdisciplinary Lab for Intelligent and Adaptive Systems (ILIAS). His academic background includes a PhD in Computer Science (with honors), an MAS in Pattern Recognition and Artificial Intelligence, an MSc in Electrical Engineering, and dual BSc degrees in Industrial Design and Industrial Engineering, all from the Universitat Politècnica de València (UPV). His research lies at the intersection of Human-Computer Interaction (HCI) and Machine Learning , with a focus on computational interaction . He investigates methods to enable, explain, and support user interaction through computational models and data-driven techniques. His key areas include implicit interaction —leveraging behavioral signals such as mouse movements and gaze—and synthetic data generation , particularly using kinematic models to simulate human-like gestures. His work has contributed to usability evaluation, user engagement prediction, adaptive interfaces, and stroke gesture modeling. His recent publications span top-tier journals and conferences such as ACM Transactions on Computer-Human Interaction (TOCHI) , IEEE Transactions , CHI , IUI , and SIGIR . The research trends reflect a strong emphasis on multimodal interaction, affective computing, brain-computer interfaces, and deep learning applications in user interface modeling and personalization. Best paper award at IUI'25 Marie Skłodowska-Curie Actions (MSCA) Seal of Excellence (2019) Extraordinary PhD thesis award (2014) Outstanding Reviewer Recognition at CHI, ICMI, MobileHCI, and UIST Quality Teaching Awards finalist at Aalto University (2020) Luis A. Leiva has advised numerous MSc and BSc students at the University of Luxembourg and Aalto University and has secured significant research funding as PI or co-PI for projects such as SYMBIOTIK (EIC), SCRIPTOR (FNR), BANANA (CHIST-ERA), and SAMUSE (Audacity). He is an Associate Editor for the International Journal of Human-Computer Studies and Machine Learning with Applications , and actively serves on the program committees of major HCI and AI conferences. He is also a co-founder and former CTO of Sciling, an SME specializing in machine learning solutions, and has held postdoctoral positions at Aalto University and the PRHLT Research Center (UPV). He leads the Computational Interaction research group and the ILIAS lab, both dedicated to advancing intelligent, adaptive, and user-centered computing systems through interdisciplinary research combining machine learning, cognitive science, and interactive technologies.

• Software Engineering
• Regulatory Compliance
• Legal Requirements Engineering
• +۵ مورد دیگر

Nicolas SANNIER is a Postdoctoral Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the Software Verification and Validation (SVV) research group led by Prof. Lionel Briand. He holds a PhD in Computer Science from the University of Rennes (France, 2013). His research focuses on regulatory compliance, legal requirements engineering, and the application of model-driven engineering, natural language processing, and machine learning to analyze legal and regulatory texts. Key areas include GDPR compliance for software systems, automated regulatory change analysis, and formalization of legal policies. Previously, he worked at EDF, Inria, and other institutions. His work bridges academic research with practical applications in industries such as finance and nuclear energy. He develops frameworks for extracting semantic legal metadata, simulating legal policies, and automating compliance checks using runtime verification techniques. His expertise includes natural language processing for legal texts, automated cross-reference resolution, and technology transfer projects. His research has produced tools like MatrixMiner and frameworks for regulatory requirements modeling (e.g., INCREMENT). He emphasizes long-term sustainability of safety requirements repositories and addresses challenges in variability and traceability in complex systems. Current trends in his publications focus on AI-driven compliance solutions, GDPR privacy concerns in mobile apps, and automated analysis of financial regulations.

• Computer Vision
• Deep Learning
• Cybersecurity
• +۳ مورد دیگر

Marcella ASTRID is a Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the CVI2 department. Her research focuses on advanced machine learning techniques applied to cybersecurity and computer vision challenges, particularly in the detection of synthetic media (deepfakes) and anomaly detection systems. She specializes in developing robust models that address vulnerabilities in adversarial scenarios and improve generalizability across diverse datasets. Key research areas include deepfake detection through spatio-temporal analysis, anomaly detection via novel training paradigms, and efficient neural network compression for resource-constrained environments. Her work bridges theoretical advancements in machine learning with practical applications in surveillance systems, autonomous robotics, and cybersecurity infrastructure. Recent contributions emphasize leveraging autoencoder weaknesses, pseudo anomaly generation, and localized attention mechanisms to enhance detection accuracy and model robustness. Marcella’s research also explores cross-modal learning (audio-visual synchronization) and semi-supervised methodologies to tackle data scarcity issues in critical domains like battery thermal imaging and multi-camera traffic classification. She actively publishes in top-tier venues and collaborates on interdisciplinary projects addressing real-world security and reliability challenges.