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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

Miguel Angel Olivares Mendez is an Associate Professor and Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) of the University of Luxembourg , where he leads mobile robotics research within the Automation & Robotics Research Group. He joined SnT in May 2013 as an Associate Researcher and was promoted to Research Scientist in December 2016. Education : Diploma in Computer Science Engineering (2006), University of Malaga M.Sc. in Robotics and Automation (2009), Technical University of Madrid Ph.D. in Robotics and Automation (2013), Technical University of Madrid His research focuses on unmanned aerial systems , computer vision , and robotics automation , with expertise in sensor fusion, vision-based control, and soft-computing techniques. He has supervised 7 research projects and published over 60 journal/book chapters and conference papers. Honors & Service : Best PhD Thesis Award (2013), European Society for Fuzzy Logic and Technology (EUSFLAT) Associate Editor, Journal of Intelligent & Robotic Systems (JINT) Reviewer Editor, Frontiers in Robotics and AI Organizing committee roles: BICS 2010 (Local Arrangement Chair), IEEE ETFA 2015 (Financial Chair) His work bridges theoretical and applied robotics, with active involvement in international academic conferencing and editorial leadership.

• Unmanned Aerial Systems
• Computer Vision
• Sensor Fusion
• +3 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

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
• +3 more

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.

• Computer Vision
• Deep Learning
• Media Forensics
• +1 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

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

Gabriel Irribarem Soares Ruas is a Researcher affiliated with the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the Services and Data Management research group (SEDAN). He holds a Master’s degree from the University of Brasília (UnB, Brazil) awarded in 2009. His research focuses on computer vision and artificial intelligence, with over 15 years of development experience. He collaborates under the leadership of Prof. Radu State’s SEDAN group. No specific grants, awards, or supervised students are listed in the provided information. Contact details include his office at Bureaux modulaires bloc G, 6, rue Coudenhove-Kalergi, L-1359 Luxembourg, and his email: gabriel.ruas@uni.lu .

• Computer Vision
• Artificial Intelligence

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

Abd El Rahman Shabayek is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg, leading research in AI-driven Computer Vision for space and energy sectors. His interdisciplinary background includes contributions across prestigious universities in France, the UK, Spain, and Egypt. He holds an Erasmus Mundus MSc and a PhD in Computer Vision and Robotics from France. Current Affiliations: CVI² Research Group (SnT), University of Luxembourg. Former Roles: Assistant Professor at Suez Canal University, adjunct positions at Sinai University and the Information Technology Institute. Research focuses on optimizing deep neural networks for spatial/terrestrial applications, with over 50 publications and an h-index of 16. Notable contributions include work on 3D deformation transfer, anomaly detection in battery thermal imaging, and hybrid attention models for pedestrian detection. His work bridges academia and industry through collaborations in healthcare, 3D scanning, and space tech. He has received two best paper awards and actively reviews for IEEE/Springer journals and top conferences like IROS, AAAI, ICCV, and CVPR. Teaching includes the Computer Vision module in the International Space Master’s program and AI summer camps for adolescents. Awards: Two best paper awards (3D deformation and skeletal feedback). Grants: Successfully led proposals for Luxembourg National Research Fund (FNR) projects under PPP and CORE programs. Key projects include the Zero-G Lab for space operations emulation and development of the STARR system for stroke rehabilitation. His labs focus on AI-driven solutions for energy systems, robotics, and biomedical applications.

• Artificial Intelligence
• Computer Vision
• Deep Learning
• +5 more

Heiko SCHÜTT is an Associate Professor of Computational Science and Modelling at the University of Luxembourg's Faculty of Humanities, Education and Social Sciences. He is affiliated with the Department of Behavioural and Cognitive Sciences, where his research focuses on integrating computational models with cognitive and neural processes. His work spans machine learning, perceptual decision making, and visual perception, leveraging tools like deep neural networks and Bayesian analysis. Key research interests include analyzing neural representations through methods like representational similarity analysis, developing probabilistic models for feature segmentation, and investigating reward processing mechanisms in the brain. His publications highlight contributions to understanding how computational models can explain human cognition, particularly in areas like face recognition and color constancy. Recent work emphasizes the application of Bayesian experimental design to controversial stimuli and the optimization of loss functions in machine learning contexts. SCHÜTT collaborates across disciplines, bridging artificial intelligence with neuroscientific insights while maintaining a focus on experimental validation of computational hypotheses. He holds a strong academic profile with over 35 publications since 2016, addressing topics ranging from early visual processing to high-level cognitive functions. Despite his prolific output, no formal awards or grants are listed in the provided materials.

• Computational Neuroscience
• Machine Learning
• Perceptual Decision Making
• +3 more

Dr. Michael Spratling is a Postdoctoral Researcher in the Department of Behavioural and Cognitive Sciences at the University of Luxembourg. His work bridges computational neuroscience and artificial intelligence, with specialization in neural networks, computer vision, and biologically-inspired learning systems. Spratling develops robust AI models through adversarial training techniques and neural architecture innovations. His core research investigates predictive coding mechanisms in machine learning, adversarial defenses for computer vision systems, and biologically-plausible neural network architectures. Recent projects focus on improving model resilience against data perturbations using adaptive smoothing techniques. Spratling maintains active GitHub repositories featuring benchmark tools for evaluating deep learning robustness. His work has applications in medical imaging and autonomous systems requiring reliable visual recognition. He received the Vebleo Scientist Award in 2020 for contributions to molecular biology-inspired AI research. He collaborates internationally on projects involving few-shot anomaly detection and multimodal neural networks. Current grants support research in length extrapolation for large language models and margin-based loss functions.

• Neural Networks
• Computer Vision
• Predictive Coding
• +3 more

Romain TOEBOSCH is a Doctoral Researcher at the University of Luxembourg's Department of Behavioural and Cognitive Sciences within the Faculty of Humanities, Education and Social Sciences. His work focuses on innovative intersections between technology and human behavior, particularly in personal informatics, affective computing, and educational tools. He conducts research at Maison Sciences Humaines (MSH) in Esch-sur-Alzette. TOEBOSCH's research interests include designing ethical technology interfaces, co-creation methodologies with vulnerable populations, and future-oriented design fiction. His work often explores how technology can enhance self-tracking, collaboration, and learning through gamification and AI-driven systems. His publications highlight trends in developing non-judgmental user interfaces, addressing online manipulation risks for older adults, and creating negotiation-based tools for healthy behaviors. He has pioneered frameworks like the Chef's Hat simulation environment for reinforcement learning agents and explored affective-aware human-robot interaction through card games. His recent work extends to professional informatics tools and temporal self-negotiation strategies. TOEBOSCH's research integrates disciplines like human-computer interaction, behavioral science, and computer science to address real-world challenges in education, health, and aging populations.

• Human-Computer Interaction
• Personal Informatics
• Design Fiction
• +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

Faisal HAWLADER is a Postdoctoral Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), within the Ubiquitous and Intelligent Systems (UBIX) research group. Advised by Dr. Raphaël Frank, his work focuses on Connected and Automated Vehicle (CAV) technologies, particularly cooperative driving strategies leveraging V2X communication and 5G networks. His research emphasizes real-time object detection, distributed perception systems, and teleoperated driving solutions. Education : Master's degree in Information and Computer Sciences, University of Luxembourg (2020) Research Interests : Faisal's research addresses challenges in cooperative perception for autonomous vehicles, including occlusion-free 4D perception, edge-cloud hybrid computing for 360-degree sensing, and infrastructure-assisted distributed perception strategies. He also investigates cybersecurity aspects of vehicular networks, such as detecting false position attacks. Publications Trends : His recent work emphasizes V2X-enhanced perception systems (e.g., V2X-BEVDet4D), 5G-enabled teleoperation, and experimental evaluations of cooperative perception in realistic scenarios. Key themes include real-time object detection algorithms, latency optimization in edge-cloud architectures, and closing simulation-reality gaps in vehicular perception systems. Awards : No scientific awards explicitly mentioned. Advising & Grants : No advisees or grants listed in the provided data. Labs/Teams : Member of the UBIX research group, collaborating on cutting-edge projects related to intelligent transportation systems and vehicular communication technologies.

• Connected and Automated Vehicles
• Cooperative Driving Strategies
• V2X Communication
• +3 more