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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
• +5 more

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
• +5 more

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
• +7 more

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
• +4 more

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
• +5 more

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
• +6 more

Dr. Gamal ELGHAZALY is a Research scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), affiliated with the Ubiquitous and Intelligent Systems department. His work focuses on autonomous driving technologies, V2X communication systems, robotics, and control systems. Key research areas include 5G-enabled teleoperated driving, high-definition map construction, and 3D perception for autonomous vehicles. He has developed platforms like RoboCar and contributed to frameworks like FastCycle for modular automated systems. Research interests span robotics kinematics (planar parallel manipulators), adaptive control methodologies (sliding mode control, fuzzy logic), and hybrid systems (cable-driven robots). His publications emphasize real-time motion planning, sensor fusion, and safety-critical systems. Recent works (2023-2025) highlight advancements in 4D perception, cloud-assisted 3D reconstruction, and V2X-enabled collaborative systems. Publications from 2017-2018 reflect early contributions on parallel manipulator modeling and control, while recent efforts focus on integrating cutting-edge technologies like 5G and edge computing into autonomous systems. His work bridges theoretical robotics with practical implementations, addressing challenges in both dynamic environments and industrial applications.

• Autonomous Driving
• V2X Communication
• Robotics
• +3 more

Alexander SKUPIN is an Associate Professor and Chief Scientist in the Luxembourg Centre for Systems Biomedicine (LCSB) at the University of Luxembourg, specializing in Modelling of Biomedical Data. His research focuses on computational systems biology, neurodegenerative diseases, and integrative multi-omics analysis. Key research interests include modeling cellular energy metabolism, microglial dynamics in neurodegeneration, and calcium signaling dysfunction in Parkinson’s and Alzheimer’s diseases. His work combines experimental data with advanced computational methods to dissect disease mechanisms and predict therapeutic targets. Recent publications highlight innovations in: Sex-specific transcriptomic changes in tauopathy models Computational models of astrocytic morphology and mitochondrial efficiency Multi-omics integration for Parkinson’s disease intervention points Epidemiological modeling using Kalman-filtered SIRS networks No scientific awards explicitly mentioned. Advising and grants: No specific advisees or grant details listed, but his work implies leadership in collaborative projects involving organoid models and patient-derived xenografts. Labs/Teams: Part of LCSB’s Integrative Cell Signalling group, collaborating on systems biomedicine initiatives involving computational modeling and experimental validation.

• Systems Biomedicine
• Neurodegenerative Diseases
• Computational Modelling
• +6 more

Ivan Nourdin is a Full Professor of Stochastic Modelling in the Department of Mathematics at the University of Luxembourg. He holds a PhD in Mathematics from Université de Lorraine (2004) and has held academic positions at Université Pierre et Marie Curie (2005–2010) and Université de Lorraine (2010–2014). His research focuses on probability theory, stochastic analysis, and their applications to statistics, geometry, and data science. He co-founded GrewIA, a startup focused on AI and mathematics education. **Research Interests**: Malliavin calculus, Stein’s method, functional inequalities, free probability, rough paths theory, inference for high-dimensional problems. He has authored/co-authored over 80 journal articles and two monographs, including the award-winning Normal Approximations with Malliavin Calculus (2012). **Awards**: 2015 FNR Award for Outstanding Scientific Publication, 2013 France Scopus Researcher Award, 2011 Fondation des Sciences Mathématiques de Paris Prize. **Advising & Teams**: Leads a research group including postdocs and PhD students. Former advisees include Simon Campese, Federico Dalmao, and Guangqu Zheng. His team explores topics like stochastic processes, limit theorems, and applications in AI. **Contact**: Office MNO E05 0515090, Maison du Nombre, University of Luxembourg. Phone: (+352) 46 66 44 6380. Email: ivan.nourdin@uni.lu.

• Probability Theory
• Stochastic Analysis
• Malliavin Calculus
• +6 more

Giovanni PECCATI is a Full Professor in Mathematics and Head of the Department of Mathematics (DMATH) at the University of Luxembourg’s Faculty of Science, Technology and Medicine. He leads the research group 'Revealing order in randomness' and serves as President of the Luxembourg Mathematical Society. Previously, he held positions at Sorbonne Université (1999–2008) as Assistant Professor and at Université Paris-Nanterre (2008–2010) as Full Professor before joining Luxembourg in 2010. His research focuses on probability theory, stochastic analysis, and mathematical finance, with particular expertise in Malliavin calculus, limit theorems, and random fields. Key contributions include studies on nodal sets of random waves, Poisson functionals, and Stein’s method applications. Prof. Peccati’s awards include the 2018 IMS Fellowship and the 2015 FNR Award for Outstanding Scientific Publication. His work bridges pure mathematics with applications in statistical mechanics and mathematical physics, emphasizing probabilistic structures in geometric and physical systems. He has authored over 100 publications, including the influential book *Wiener Chaos: Moments, Cumulants and Diagrams* (2011), and co-founded the *Stochastic Analysis for Poisson Point Processes* research program. His current projects explore phase transitions in stochastic systems and geometric properties of random fields.

• Probability Theory
• Mathematical Finance
• Stochastic Analysis
• +4 more

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.

• Computer Vision
• Deep Learning
• Cybersecurity
• +3 more

Jean Botev is a Research Scientist and co-head of the Collaborative and Socio-Technical Systems (COaST) group at the University of Luxembourg's Faculty of Science, Technology and Medicine. He directs the VR/AR Lab, focusing on immersive technologies and human-centered design. His work bridges physical and digital realities through mediated reality approaches, emphasizing collaborative virtual environments and interaction techniques. Dr. Botev holds a PhD in Computer Science (2011, University of Luxembourg) and master's/bachelor's degrees from the University of Trier (Germany). He teaches courses in Virtual/Augmented Reality, Immersive Media, and programming disciplines across multiple university programs. His research spans 85+ peer-reviewed publications, with notable contributions to IEEE VR, ACM IVA, and TVCG. He leads €5M+ in grants, including the EU H2020 FET Open ChronoPilot project (€3M) exploring time perception modulation. Awards include the 2024 EuroXR Best Demonstration Award and multiple best paper recognitions. Botev actively engages in public outreach, organizing events like ACM SIGGRAPH Asia Demo Scene and promoting ethical design principles. His work integrates socio-technical systems, human factors, and interdisciplinary collaboration to advance immersive technology applications in education, cultural heritage, and healthcare.

• Mediated Reality
• Human-Computer Interaction
• Collaborative Socio-Technical Systems
• +3 more

Francesco Viti is an Associate Professor in Engineering Science (Traffic Planning and Management) at the University of Luxembourg, leading the MobiLab Transport Research Group within the Department of Engineering. His research focuses on mobility analysis, transport electrification, intelligent transport systems, and data science applications in transportation. He coordinates projects on public transport electrification, Mobility-as-a-Service (MaaS), and freight logistics optimization. Viti has authored over 250 publications and serves as an associate editor for journals like Transportation Research Part C. He advises the Luxembourgish government and the European Commission on transportation policy. Research Interests: Viti’s work spans traffic flow theory, transport electrification, MaaS modeling, and data-driven solutions for urban mobility challenges. Current projects include optimizing electric feeder bus services, analyzing ride-hailing fleet management under dynamic energy prices, and enhancing freight train operations through maintenance simulation. Key Contributions: His group develops models for synthetic population generation, demand estimation using crowdsourced data, and network equilibrium under interacting mobility providers. Recent studies explore the integration of digital twins for urban mobility and CCAM systems, as well as the impact of total cost of ownership on MaaS adoption.

• Transportation Planning
• Traffic Engineering
• Intelligent Transport Systems
• +5 more

Hamed RAHIMI NOHOOJI is a Postdoctoral researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the Automation department under Prof. Holger Voos's research group. He holds a Ph.D. from Curtin University (Australia, 2018) and has held research positions at the National University of Singapore, UC Louvain, University of Pisa, and the University of Birmingham. His research focuses on soft robotics , adaptive control systems , and human-robot interaction , with notable contributions to projects like the EU H2020 CYBERLEGs Plus Plus initiative and Singapore's A*STAR-funded soft gripper development. His work spans neuroadaptive control , reinforcement learning , and fault-tolerant systems , with applications in space robotics, wind turbine control, and collaborative robotics. With over 900 citations and an H-index of 18 (Google Scholar, 2023), his publications appear in top journals like Mechanical Systems and Signal Processing (IF 8.934) and Neurocomputing (IF 5.779). He has authored four Springer book chapters and served as a guest editor for journals including Frontiers in Robotics and AI and IEEE Transactions on Industrial Electronics . Research interests include: Soft Robotics : Design of compliant actuators, jamming grippers, and topology-optimized soft mechanisms Control Systems : Barrier Lyapunov functions, Nussbaum gain techniques, and neuroadaptive methods Human-Machine Collaboration : Adaptive trajectory optimization for safe human-robot interaction Space Applications : Soft robotics for extraterrestrial missions and compliant systems for space environments His recent articles emphasize constrained control systems , reinforcement learning for robotics , and lightweight gripper design for aerial platforms . His work often bridges theoretical control principles with practical robotic implementations in dynamic environments. Scientific achievements include a Student Travel Award at the 2016 Australasian Conf on Robotics and Automation. He has edited topical collections on Human-Robot Interaction and Soft Robotics , reflecting his leadership in shaping the field's research directions. Labs/Teams: Member of the Automation & Robotics Research Group at SnT, collaborating with Prof. Holger Voos and international partners on EU-funded projects.

• Soft Robotics
• Robotics Control Systems
• Adaptive Control
• +7 more