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Yannick BARAUD is a Full Professor in Mathematics at the University of Luxembourg, leading the group 'Developing Contemporary Mathematical Statistics' within the Department of Mathematics. He holds the ERA-Chair 'SanDAL' in Mathematical Statistics and Data Science, funded by the European Commission. His research focuses on robust estimation, model selection, hypothesis testing, and nonparametric methods. He serves as the Study Programme Director for the Master in Data Science and has held academic positions at the University of Nice Sophia Antipolis and CNRS. His career includes roles as a researcher at École Normale Supérieure (Paris) and a lecturer at the same institution. He earned his PhD from Université Paris-Sud and studied at École Normale Supérieure de Cachan. His work emphasizes rigorous statistical methodologies, including rho-estimation and robust Bayes-like approaches. Notable contributions include advancements in density estimation under shape constraints and robust regression techniques. He has published extensively on topics such as loss functions, empirical processes, and statistical inference, with applications in epidemiology and data science. His leadership in the SanDAL initiative underscores his commitment to bridging mathematical statistics and practical data science challenges. Collaborations and grants further highlight his role in advancing interdisciplinary research.

• Mathematical Statistics
• Model Selection
• Robust Estimation
• +3 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

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

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.

• Software Engineering
• Cyber-Physical Systems
• Real-Time Systems
• +4 more

Dr. Vittorio FRANZESE is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg's SPASYS department. His work focuses on CubeSat technology, autonomous space systems, and deep-space exploration. He leads projects like the POQUITO PocketQube mission and the LUMIO lunar CubeSat, aiming to advance miniaturized satellite capabilities for interplanetary navigation and meteoroid impact monitoring. Key research areas include spacecraft autonomy, optical navigation algorithms, and mission design for CubeSats. He has contributed to initiatives such as the ERC-funded EXTREMA project, developing self-driving interplanetary CubeSats. His technical expertise spans satellite systems engineering, trajectory optimization, and sensor development for space applications. Publications highlight advancements in laser communication terminals, asteroid mission analysis, and swarm satellite technologies. Collaborative efforts include the Hera Milani CubeSat mission for asteroid exploration. His work bridges theoretical research with practical implementation, emphasizing innovation in low-cost space technologies.

• Spacecraft Design
• Aerospace Engineering
• Astrodynamics
• +4 more

Dr. Carol Martinez Luna is a Research Scientist and Deputy Head of the Space Robotics group (SpaceR) at the SnT Interdisciplinary Centre, University of Luxembourg. She holds a PhD in Robotics and Automation from Universidad Politécnica de Madrid (2013) and previously served as an Assistant Professor at Pontificia Universidad Javeriana, Colombia. Her research spans Space Robotics , Computer Vision , and Machine Learning , with current focus areas including: Multi-purpose manipulation for planetary/orbital robots Perception systems for autonomous space operations Domain adaptation to bridge simulation-to-reality gaps On-ground testing of orbital technologies Recent publications (2022-2025) predominantly address space debris removal , autonomous grasping , and robotic perception , with heavy emphasis on machine learning techniques and high-fidelity simulation validation. Notable trends include generative models for manipulation and adaptive control under uncertainty. She actively advises 7 PhD students and 9 Master's candidates on topics ranging from space manipulation to vision-based safety systems. Her lab develops experimental platforms for orbital scenario emulation and collaborates on ESA-funded debris removal initiatives.

• Space Robotics
• Computer Vision
• Machine Learning
• +5 more

Baris Can YALCIN is a postdoctoral researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg , specializing in control theory and its applications in linear and non-linear control, adaptive control, estimator design, and filter design. He works within the Space Robotics (SpaceR) group under Prof. Miguel Angel Olivares Mendez. His research focuses on advancing control systems through adaptive methodologies and robust estimator/filter design, contributing to fields like space robotics and autonomous systems. His work bridges theoretical control frameworks with practical implementations.

• Control Theory
• Linear Control
• Non-Linear Control
• +3 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

Anis KACEM is a Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg, part of the Signal Processing and Satellite Communications (SIGCOM) research group. His work focuses on Computer Vision and Pattern Recognition, particularly in Human Behavior Understanding from visual data. He received his PhD in Computer Science from the University of Lille (France) in 2018. Research interests include advanced topics such as Earth Observation via multi-modal autoencoders, domain adaptation for image classification, vulnerability-aware deepfake detection, and CAD system reverse engineering. His contributions span neural network pruning, 3D shape analysis, and generative models for medical imaging. Publications highlight innovations in spatio-temporal learning for deepfake detection, hybrid attention mechanisms for pedestrian detection, and tool-augmented CAD task solvers. His work bridges theoretical advances with practical applications in autonomous systems and space technology. Notably, he has contributed to challenges like the SHARP 2023 Challenge on CAD history recovery and developed frameworks like Picasso for CAD sketch inference using self-supervised learning.

• Computer Vision
• Pattern Recognition
• Human Behavior Understanding
• +5 more

Dr. Mohammed Oualid ATTAOUI is a Postdoctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg, affiliated with the SVV department. His work focuses on advancing artificial intelligence and machine learning methodologies, particularly in the context of deep neural network (DNN) safety analysis, clustering algorithms for data streams, and medical image processing applications. He holds a strong research interest in generative adversarial networks (GANs), black-box model analysis, and transfer learning techniques. His current position involves developing robust frameworks to ensure safety and reliability in AI systems, with notable contributions to the SAFE methodology for DNN retraining and validation. Research interests span across multiple domains including: Deep Learning and Safety-Critical AI Systems Data Stream Mining and Real-Time Clustering Medical Imaging Analysis (Histopathology, Computer Vision) Feature Selection and Optimization in Bioinformatics Subspace and Topological Clustering Approaches His recent research trends emphasize the intersection of adversarial machine learning and safety engineering, with publications demonstrating advancements in GAN-enhanced simulation-driven testing and clustering-based safety analysis for DNNs. His work bridges theoretical algorithm development with practical applications in healthcare imaging and autonomous systems. Dr. ATTAOUI's research outputs reflect a strong focus on methodological innovation with over 15 peer-reviewed articles since 2018. He actively contributes to open-source tools for data stream clustering and maintains an active presence in AI safety communities. His current projects explore adaptive clustering techniques for evolving data streams and robustness certification of medical image processing systems.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +5 more

Holger Voos is Full Professor in Engineering Science at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), where he leads the Automatic Control Laboratory. His research focuses on distributed networked control, autonomous robotic systems, safety-critical applications, and mechatronic system design. His recent publications demonstrate strong research emphasis on: Advanced SLAM algorithms integrating visual, inertial and wireless technologies Optimal control strategies for spacecraft formations and aerial robots Neuromorphic vision systems and sensor fusion techniques Reinforcement learning approaches for robotic manipulation Constraint-based optimization methods for robotic perception and control

• Autonomous Robots
• Networked Control Systems
• Mechatronic Systems
• +1 more

Arunkumar RATHINAM is a Postdoctoral researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the CVI2 department. His research focuses on autonomous systems, spacecraft navigation, and machine learning applications in space exploration. He has contributed to the development of datasets like SPARK and Zero-G Lab, which advance space operations emulation and computer vision techniques. Affiliations: SnT-CVI2, University of Luxembourg Key Research Areas: spacecraft pose estimation, thermal anomaly detection, autonomous navigation, and robotics for space missions His work bridges machine learning with practical space systems, addressing challenges in thermal monitoring (e.g., Li-ion battery cells) and vision-based navigation for spacecraft proximity operations. He has pioneered experimental facilities like the Zero-G Lab to simulate microgravity environments and test space robotics systems. Notable contributions include datasets such as SPARK and AKM, which provide critical data for training models in spacecraft trajectory estimation and textureless target detection. His publications emphasize real-world applications of AI in space systems, including RGB-T pedestrian detection and hybrid attention mechanisms for robust vision systems.

• Spacecraft Navigation
• Autonomous Systems
• Computer Vision
• +5 more