جست‌وجوی استاد و پژوهشگر

• modeling and verification of concurrent systems
• resource-aware embedded systems
• compositional performance and dependability evaluation
• +۵ مورد دیگر

Holger Hermanns is a Professor of Computer Science at Saarland University in Germany, where he heads the Dependable Systems and Software group. He also serves as Scientific Director of Schloss Dagstuhl - Leibniz Zentrum für Informatik. His academic journey includes previous positions at Universität Erlangen-Nürnberg, Universiteit Twente in the Netherlands, and INRIA Grenoble Rhône-Alpes in France. He has served as Dean of the Faculty of Mathematics and Computer Science at Saarland University from 2010-2012 and as Dean of Studies from 2004-2006. Holger Hermanns' research focuses on modeling and verification of concurrent systems, resource-aware embedded systems, compositional performance and dependability evaluation, and their applications to energy and space informatics. He is an outspoken proponent of proactive algorithmic accountability. His work bridges formal methods with practical applications in critical systems, particularly in the domains of cyber-physical systems and satellite networks. His recent publications reveal a strong emphasis on human oversight of AI systems, software doping detection, satellite network protocols, and explainable AI. There's a clear trend toward addressing practical challenges in dependable computing, with increasing focus on the societal implications of algorithmic decision-making and the environmental impact of computing systems. Holger Hermanns has received numerous prestigious awards and recognitions: ERC Advanced Grant POWVER ERC Proof-of-Concept Grant LEOpowver Member of Academia Europaea (elected 2013) German "Preis des Fakultätentages Informatik" award (2013) Dutch "Vernieuwingsimpuls" award (2001) ERC Advanced Grantee Co-spokesperson of the Center for Perspicuous Computing, SFB TRR 248 As Scientific Director of Schloss Dagstuhl - Leibniz Zentrum für Informatik, Hermanns plays a crucial role in fostering international collaboration in computer science research. His leadership extends to various program committees and steering committees of major conferences in formal methods and theoretical computer science, including TACAS (steering committee since 2015), LICS (steering committee 2020-2023), and ICALP (steering committee 2020-2022). He has served as conference chair for LICS and ICALP in 2020. His research group at Saarland University focuses on dependable systems and software, with strong connections to both theoretical foundations and practical applications.

Lennart Rubbertمشاهده پروفایل

مدرس

• Mechatronics
• Robotics
• Biomedical Engineering
• +۶ مورد دیگر

Lennart Rubbert is a Lecturer in the Department of Mechanical Engineering at INSA Strasbourg. He serves as Head Teacher for 5th-year mechatronics (MIQ) students and acts as Contact Person for SST, PSSM, and VSSH programs. His office is located in T1.23 on the ground floor of the mechanical platform mezzanine. His research focuses on advanced mechatronics, robotics, and biomedical engineering applications. Key areas include compliant mechanism design, soft robotics, and surgical device innovation. He leads the Robotics, Data Science and Healthcare Technologies (RDH) research unit at ICube, overseeing projects like the ARC steerable needle system (SATT Conectus) and the Origabot ANR project exploring origami-inspired robotics. Current research initiatives include: EndoFlex : Labex-CAMI funded work on flexible endoscopic configurations 3D-printed soft robots : Normalien scholarship-supported projects He has advised students including John BERRE (OrigaBot thesis), Benjamin CALMÉ (EndoFlex), and Loïc MOSSER (3D-printed soft robots). His 2017 book The Art of Flexure Mechanism Design remains a foundational text in compliant mechanism studies. Technical contributions span laser profilometry for silicone deposition, genetic algorithm-driven soft actuator design, and ROS2 integration in additive manufacturing systems. He actively collaborates through partnerships like SATT Conectus and ANR grants.

Eric BONJOURمشاهده پروفایل

استاد

• Systems Engineering
• Model-Based Systems Engineering
• Digital Transformation
• +۳ مورد دیگر

Eric BONJOUR is a University Professor and Director of Studies at the École Nationale Supérieure de Géologie et des Sciences de l'Ingénieur (ENSGSI), part of Groupe INP in Nancy, France. His research focuses on model-based systems engineering, digital transformation, and improving the acceptability of innovative solutions through projects like the BRAFITEC initiative with Brazilian universities. He holds a PhD in Automation and Computer Science from Université de Franche-Comté (2008) and a Mechanical and Microengineering degree from ENSMM (1996). His teaching includes courses on system engineering, linear control systems, Agile project management, and requirements engineering. Research interests span project management maturity models, autonomous vehicle safety, and knowledge management. He coordinates international collaborations and leads educational programs such as the IDEAS Master’s degree in Innovation and Design and the Engineering Degree in Systems and Innovation Engineering. Recent publications emphasize advancements in requirements validation, autonomous vehicle safety scenarios, and Bayesian network applications in risk mitigation. His work bridges theoretical systems engineering with practical industrial challenges, particularly in automotive and healthcare sectors.

Natalia Kushikمشاهده پروفایل

مدرس

• Model-Based Testing
• Finite State Machines
• Software-Defined Networks (SDN)
• +۷ مورد دیگر

Natalia Kushik is a Lecturer at Telecom SudParis, part of the Institut Polytechnique de Paris. Her primary affiliation is with the ACMES (Algorithmics and Computer Models for Engineering and Systems) research group. Her research focuses on model-based testing methodologies, formal verification of systems, and applications in software-defined networking (SDN), cloud computing, and distributed systems. Her work extensively employs finite state machines (FSMs) and automata theory to design test strategies for complex systems. Notable areas include deriving homing/synchronizing sequences for automata, race condition detection in distributed systems, and optimizing network configurations using timed models. She has contributed to improving the reliability and security of SDN controllers and cloud infrastructures through formal methods. Recent trends in her publications emphasize probabilistic approaches for test suite minimization, emulation-based validation of dynamic networks, and formal analysis of reactive systems. She has collaborated on projects involving QoE (Quality of Experience) evaluation for multimedia services and fault models for digital circuits. Her work often bridges theoretical computer science with practical system implementation challenges. Her articles frequently explore intersections between formal methods and real-world applications, such as applying cellular automata for network parameter modeling and using SMT solvers for configuration validation. She has also published on optimizing interpreted programming languages using state models and proactive trust assessment mechanisms for service systems. Kushik’s research is characterized by interdisciplinary collaborations, with contributions to both academic conferences (e.g., ICTSS, ENASE) and industry-oriented venues (e.g., IEEE NCA). Her work addresses challenges in system reliability, security, and scalability across diverse domains like telecommunications, cloud computing, and embedded systems.

Valerio Incertiمشاهده پروفایل

استادیار

• Management & Organization
• Organizational Behavior
• Virtual Teams
• +۵ مورد دیگر

Valerio Incerti is an Assistant Professor at SKEMA Business School in France, specializing in Management & Organization research. His work focuses on virtual teams , knowledge management , and organizational behavior , with a particular emphasis on the effects of Multiple Team Membership (MTM) and communication rules on teamwork dynamics. 2017 PhD in Industrial Innovation Engineering from University of Modena and Reggio Emilia 2013 Master in Engineering Management (summa cum laude) from University of Modena and Reggio Emilia Research interests span organizational polychronicity , social identity , and team performance , with publications in journals like M@n@gement and Journal of Enterprising Communities , as well as conferences such as the Academy of Management Annual Meeting and INGRoup Conference . His methodological approach includes mixed-method studies, simulation modeling, and experimental research. Key article trends show interdisciplinary work bridging management theory with operations research and social identity perspectives , particularly in areas like LGBT entrepreneurship and environmental sustainability .

Marie-Eléonore Kessaciمشاهده پروفایل

استاد

• Combinatorial Optimization
• Metaheuristics
• Local Search Algorithms
• +۴ مورد دیگر

Marie-Eléonore Kessaci is a Professor at the University of Lille , affiliated with the Polytech Lille Engineering School and the Computer Science and Statistics Department . She is associated with the ORKAD team at the Lille Computer, Signal and Automatic Research Center (UMR 9189) . Her research focuses on: Combinatorial Optimization Metaheuristics and Local Search Automatic Algorithm Configuration/Selection Landscape Analysis Adaptive Algorithms Multi-objective Optimization Professor Kessaci defended her Habilitation à Diriger des Recherches (HDR) in November 2019 and obtained her PhD in Computer Science in December 2011 from the University of Lille 1. She has held post-doctoral positions at Université Libre de Bruxelles (September 2012 - August 2013).

Nadarajen Veerapenمشاهده پروفایل

مدرس

• optimization
• metaheuristics
• local search
• +۳ مورد دیگر

Nadarajen Veerapen is a Lecturer at University of Lille within the Faculty of Economic, Social and Territorial Sciences . He has been affiliated with the CRIStAL laboratory since 2018, working in the ORKAD team . His teaching responsibilities include leading the Business Intelligence and BIMST courses, and co-leading the Data Sciences course for the Information Systems and Decision Support (SIAD) Master's program. His research focuses on optimization, metaheuristics, local search algorithms, automatic algorithm configuration, search landscape analysis, and networks of local optima . He previously served as a Research Fellow at the University of Stirling , Scotland, and earned his Ph.D. in computer science from the University of Angers . His expertise spans data visualization, machine learning, and data quality, contributing to both academic and practical advancements in computational methods and decision support systems.

• Software Engineering
• Model-Based Systems Engineering
• Automotive Software
• +۴ مورد دیگر

Sebastien SAUDRAIS serves as an Enseignant-chercheur (Teacher-Researcher) at ESTACA, a prominent French engineering school specializing in aeronautics and automotive systems. He is affiliated with the Pôle S2ET research division and the ESTACA'Lab department, where he bridges academic research with industrial applications in automotive software development. His research spans Software Engineering , Model-Based Systems Engineering , and Automotive Software , with deep expertise in Embedded Systems , Real-Time Systems , and Energy Management for electric vehicles. He focuses on AUTOSAR (Automotive Open System Architecture) frameworks, safety-critical system design, and model-driven approaches for automotive innovation, particularly in steering-by-wire systems and energy optimization. Analysis of his 15 most recent publications (2011-2016) reveals consistent contributions to automotive software engineering, emphasizing model transformations, quality-of-service modeling, and energy-aware system design. His work frequently addresses AUTOSAR integration challenges, physical model incorporation for electric vehicles, and safety analysis in transportation systems, demonstrating strong industry relevance through collaborations with automotive research consortia. SAUDRAIS actively contributes to ESTACA'Lab's mission through educational initiatives like the PIRATE projects, which introduce engineering students to research methodologies, and teaches courses spanning algorithmic foundations to advanced model-based automotive system design.

• Semantic Web
• Web Services Composition
• Formal Concept Analysis
• +۶ مورد دیگر

Nizar Messai is a Researcher at the University of Tours , affiliated with the Faculty of Science and Technology and Polytechnic School of the University of Tours (EPU) . He works within the Laboratory of Fundamental and Applied Computer Science (LIFAT, UR 6300) , focusing on semantic technologies and distributed systems. Research Interests : Semantic Web Services Composition Formal Concept Analysis (FCA) for Data Mining Blockchain Applications in Trustworthy Systems Context-Aware IoT Mashups Linked Open Data Integration Scientific Contributions : Developed semantic similarity measures for service discovery Created the LDS Java library for LOD-based similarity Explored blockchain for decentralized choreography execution Integrated attention mechanisms in travel mashup systems Applied FCA to clinical decision support systems Collaborations & Labs : Active member of the LIFAT (UR 6300) laboratory, contributing to projects at the intersection of computer science, semantic technologies, and biomedical informatics.

Nicolas Durandمشاهده پروفایل

استاد

• Metaheuristics
• Combinatorial Optimization
• Interval Methods
• +۵ مورد دیگر

Nicolas Durand is a Professor at the National School of Civil Aviation (ENAC), specializing in Air Traffic Management through the integration of Metaheuristics , Combinatorial Optimization , and Interval Methods . His work focuses on hybridizing Evolutionary Algorithms with Machine Learning to enhance Conflict Resolution and Trajectory Prediction in aviation systems. His research spans Unmanned Aerial Systems (UAS) , ADS-B Data Analysis , and 3D Collision Avoidance . Recent projects include Behavior Cloning for conformal automation and Median Regression for lateral deconfliction. Collaborations with institutions like ONERA and ISAE-SUPAERO highlight his interdisciplinary approach. Publications reveal a trend toward Explainable AI in ATM, with applications in Dynamic Conflict Resolution , Mass Estimation , and UAS Integration . His work bridges theoretical optimization (e.g., Global Optimization , Interval CP ) with operational needs, emphasizing Controller Expertise and Uncertainty Quantification .

David Gianazzaمشاهده پروفایل

پژوهشگر

• Air Traffic Management
• Machine Learning
• Aircraft Trajectory Prediction
• +۳ مورد دیگر

David Gianazza is a Researcher at the National School of Civil Aviation (ENAC) , focusing on air traffic management and trajectory prediction. His work combines machine learning and operational research to address challenges in aircraft conflict resolution, airspace configuration, and performance modeling. Specializes in neural networks and metaheuristic optimization Key research areas: air traffic complexity , 3D trajectory planning , and workload modeling His 15 most recent articles (2024-2012) demonstrate expertise in ADS-B data analysis, mass/thrust estimation, and hybrid deterministic-stochastic search algorithms. Collaborations include researchers like Nicolas Durand , Richard Alligier , and Jean-Marc Alliot across institutions in France, Netherlands, and USA. Publications highlight applications of ant colony optimization , A* algorithms , and gradient boosting machines to air traffic problems. His work bridges theoretical computer science and practical ATM solutions , with emphasis on safety and efficiency.

Andrija Vidosavljevicمشاهده پروفایل

مدرس

• Combinatorial optimization
• Optimization under uncertainty
• Mathematical modeling
• +۵ مورد دیگر

Andrija Vidosavljevic serves as a Lecturer-researcher at Ecole Nationale de l'Aviation Civile (ENAC) in the OPTIM team within the MORO axis. He is affiliated with the Department of Mathematics and Computer Science at ENAC's School of Aeronautics, where he conducts research at the intersection of optimization theory and air traffic management systems. Dr. Vidosavljevic's research spans combinatorial optimization, optimization under uncertainty, and mathematical modeling with specific applications to traffic management and air transport systems. His work addresses critical challenges in urban air mobility, airspace design for high-density environments, and trajectory planning for both manned and unmanned aircraft. He has made significant contributions to understanding how traffic structure affects airspace capacity and safety, particularly in constrained urban environments where traditional air traffic management approaches face limitations. His publication record reveals a clear trajectory toward increasingly complex urban air mobility challenges, with recent work focusing on conflict detection and resolution for constrained urban airspace, centralized separation management for unmanned aircraft systems, and the integration of strategic and tactical approaches to air traffic management. The research demonstrates sophisticated modeling techniques including genetic algorithms, multi-agent systems, and hybrid machine learning approaches to address uncertainty in air traffic systems. Scientific Recognition: Best paper award for the Network Management track at ICRAT 2016 for 'The Influence of Traffic Structure on Airspace Capacity' Dr. Vidosavljevic has been actively involved in major European research initiatives including the Metropolis project (and its successor Metropolis II), Capacity Optimisation in TrajecTory-based OperatioNs, and the REDUCED SEPARATION MINIMA (RESET) project. His collaborative work spans multiple international institutions, reflecting the global nature of air traffic management research. He works within ENAC's Applied Mathematics, Computer Science and Automation for Aeronautics Laboratory (MAIAA), specifically in the OPTIM team that focuses on optimization methods for aeronautical applications. His current research within the MORO axis addresses the mathematical foundations of air traffic flow management and airspace design, with particular emphasis on next-generation urban air mobility systems.

Jocelyn FIORINAمشاهده پروفایل

استاد

• Wireless Communication
• Ultra-Wideband Systems
• Signal Processing
• +۳ مورد دیگر

Jocelyn FIORINA is a Full Professor and ViceDean of International Affairs at CentraleSupélec. She is affiliated with the Laboratoire des signaux et systèmes (L2S), where she leads research in telecommunications and signal processing. Her academic titles include HDR (Habilitation to Direct Research) and Engineer qualifications. Her research focuses on wireless communication systems, ultra-wideband (UWB) technologies, and advanced signal processing techniques. Key areas include indoor localization, federated learning for communication constraints, time reversal methods in UWB networks, and multi-armed bandits for network optimization. She has authored over 20 peer-reviewed articles and two books, including Cognitive Radio and Networking for Heterogeneous Wireless Networks (Springer, 2015). Recent work emphasizes federated learning strategies under communication limits (2024), adaptive K-nearest neighbor positioning (2022), and UWB beamforming (2013). Her contributions span theoretical analysis, algorithm design, and practical implementations in ad-hoc networks and sensor systems. As ViceDean, she oversees international collaborations and academic partnerships. Her lab, L2S, is part of Paris-Saclay University’s research ecosystem, focusing on energy, industry 4.0, and healthcare applications. She actively participates in workshops and conferences, including IEEE Vehicular Technology Conferences and the International Conference on Ultra-Wideband (ICUWB).

Pierre-Antoine ADRAGNAمشاهده پروفایل

دانشیار

• Additive Manufacturing
• 3D Printing Optimization
• Reverse Engineering
• +۴ مورد دیگر

Pierre-Antoine ADRAGNA serves as a Research Teacher at the University of Technology of Troyes (UTT), affiliated with the Laboratory of Mechanical & Material Engineering (LASMIS). His academic work bridges theoretical research and industrial applications in advanced manufacturing technologies. His research interests focus on Additive Manufacturing optimization , particularly FDM 3D printing processes, where he develops techniques for infill reinforcement and continuous extrusion. Additional expertise includes Reverse Engineering for medical prosthetics and building reconstruction, Mechanical Tolerancing methodologies, and Finite Element Analysis for predicting manufacturing outcomes. His work demonstrates strong industry collaboration, notably with Levels3D in the Automodel3D project for 3D building reconstruction. Dr. ADRAGNA's publication record reveals consistent contributions to mechanical engineering literature, with recent work emphasizing practical solutions for 3D printing challenges and manufacturing process optimization. His research integrates computational methods with experimental validation to address real-world manufacturing constraints. Automodel3D (2016-2019): Automated 3D building reconstruction from point clouds, co-financed by EU and Champagne-Ardenne region OptiFabAdd (2018-2021): Digital tool development for FDM additive manufacturing optimization, supported by EU and CD10 His laboratory work at LASMIS focuses on advancing mechanical engineering methodologies through computational approaches and experimental validation, contributing to UTT's research profile in advanced manufacturing systems.

• Data Analysis
• Statistical Learning Methods
• Structural Equation Modeling
• +۶ مورد دیگر

Laura Trinchera is a Professor of Statistics at NEOMA Business School, specializing in data analysis, statistical learning methods, and structural equation modeling. She holds a Master’s in Economics and Management from the University of Naples Federico II, Italy, and a PhD in Statistics (2008) from the same institution. Her research focuses on advanced statistical methodologies such as Partial Least Squares (PLS), clustering algorithms, and applications in supply chain management and marketing. She has held visiting researcher positions at institutions including University of California Santa Barbara, University of Michigan, Hamburg University, and HEC Paris. Her work spans interdisciplinary fields, including: Development of PLS-based methodologies for complex data structures Analysis of unobserved heterogeneity in longitudinal growth models Applications of AI in environmental performance and retail analytics Exploration of consumer behavior in sustainable diets and eating disorders Recent publications highlight her contributions to: AI-driven dynamic capabilities for environmental management Statistical methods for detecting hidden patterns in longitudinal data Impact of mobile commerce on retail performance Role of marketing capabilities in SMEs Her collaborative network includes partnerships with leading universities worldwide, emphasizing methodological advancements in data science and their practical applications. She actively participates in academic conferences, contributing to the advancement of PLS techniques and composite indicator systems.