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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)
• +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

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
• +6 more

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.

• Machine Learning
• Deep Learning
• Multi-Agent Systems
• +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

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

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

Jorge GONCALVES is a Full Professor at the Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, and a Principal Research Associate at the University of Cambridge's Department of Plant Sciences. He holds expertise in computational biology, systems biomedicine, and machine learning applications in healthcare. His roles include leading research on gene regulatory networks, epidemic modeling, and deep brain stimulation technologies. Education: Licenciatura from University of Porto (1993), M.S. and Ph.D. from MIT (1995/2000). Postdoctoral work at MIT and Caltech, followed by academic positions at the University of Cambridge (Lecturer, Reader, Principal Research Associate). Visiting Professorships at the University of Luxembourg and Caltech. Research Interests : Dynamical systems modeling, network inference, biomedical applications of AI, and systems biology. His work spans drug repositioning, early warning signals for disease transitions, and multiomics analysis in immunology. Publications : Focused on interdisciplinary approaches combining machine learning with biological systems. Key themes include computational methods for gene network analysis, epidemic monitoring systems, and AI-driven medical diagnostics. Awards : Not explicitly listed in provided texts. Advising and grants: Extensive collaboration with institutions globally, including leadership in EU-funded projects and industry partnerships. Active in mentoring researchers across computational biology and engineering disciplines. Labs/Teams: Leads LCSB teams focused on systems biomedicine and AI-driven health solutions. Collaborates with the University of Cambridge on plant sciences and robotics initiatives.

• Computational Biology
• Systems Biomedicine
• Machine Learning
• +5 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

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.

• Human-Computer Interaction
• Machine Learning
• Computational Interaction
• +12 more