جست‌وجوی استاد و پژوهشگر

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.

Mahdi Moeiniمشاهده پروفایل

دانشیار

• Operations Research
• Combinatorial Optimization
• Mathematical Programming
• +۵ مورد دیگر

Mahdi Moeini is an Associate Professor in Operations Research and Machine Learning at ENSIIE (École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise), affiliated with the SAMOVAR laboratory at Télécom SudParis, Institut Polytechnique de Paris. His research focuses on optimization techniques, including DC programming, combinatorial optimization, and their applications in logistics, healthcare, and finance. Academic Roles: Associate Professor (2022–present), Adjunct Lecturer (2014–2022) at TU Kaiserslautern, Germany. Research Expertise: Portfolio optimization, vehicle routing with drones, emergency medical systems, and metaheuristics. Key Contributions: Published 14 journal papers, 24 conference chapters, and 8 technical reports, with a Habilitation in 2018. Research Interests: Combinatorial optimization, mathematical programming, sustainability in digitization, and machine learning applications. Teaching: Courses include Operations Research, Data Science, Computational Intelligence, and Financial Data Analysis.

Étienne Andréمشاهده پروفایل

استاد

• Model Checking
• Formal Verification
• Timed Systems
• +۶ مورد دیگر

Étienne André is a full professor at Université Sorbonne Paris Nord, affiliated with the SAFER team at LIPN. His research focuses on formal verification of timed and real-time systems, parameter synthesis, and cyber-physical systems security. He leads multiple projects including MoCcA (multi-agent systems), ProMiS (side-channel mitigation), and SECReTS (energy-efficient real-time systems). His work emphasizes reducing carbon footprint through sustainable research practices. Education and roles include heading the P2S Master's program in safety and security programming. He has supervised numerous PhD students and post-docs, contributing to tools like IMITATOR for parametric model checking. He actively participates in conferences like Petri Nets, ATVA, and ICFEM, serving in program committees and as conference chair. His awards include a PhD award from Académie Lorraine and an ha-index of 78.

• Artificial Intelligence
• Constraint Programming
• Max-SAT
• +۲ مورد دیگر

Sami Cherif is a Lecturer at the University of Picardie Jules Verne, specializing in Optimization and Cryptography, AI - OCIA . His research focuses on advanced applications of Constraint Programming and Max-SAT in solving complex industrial and cryptographic problems. PhD in Computer Science (2022, Aix-Marseille University) Key collaboration networks: Chu-Min Li, Sorina Ionica, Corinne Lucet Research Interests Dr. Cherif’s work bridges Artificial Intelligence with Cryptography , emphasizing: Max-SAT resolution techniques Energy-efficient manufacturing systems Conference scheduling optimization Cryptographic attack modeling Publication Trends His recent publications (2025–2024) highlight Max-SAT as a central method for: Self-stabilization analysis Assembly line energy optimization Cryptographic problem solving Conference scheduling Academic Collaborations Active collaborations in constraint programming include co-authors such as Chu-Min Li , Sorina Ionica , and Corinne Lucet , with applications spanning from industrial engineering to cryptanalysis.

Pascal Quachمشاهده پروفایل

پژوهشگر

• Robust Optimization
• Resilience Engineering
• Energy Systems
• +۳ مورد دیگر

Pascal Quach is a researcher specializing in robust optimization and resilience engineering, with a focus on energy systems and critical infrastructure. His work intersects operations research, stochastic optimization, and climate adaptation. Research Focus : Distributionally robust optimization, microgrid design, infrastructure resilience Methodologies : Benders decomposition, column-and-constraint decomposition, reinforcement learning Recent trends in his publications highlight applications of advanced optimization techniques to enhance climate resilience in infrastructure networks and improve energy system reliability under uncertainty. He actively explores causal representation learning in human motion modeling, demonstrating interdisciplinary interests. He is affiliated with the Industrial Engineering Laboratory, where he collaborates with Yiping Fang and Anne Barros on projects addressing supply-demand uncertainty, distributed energy resources, and network scalability challenges.

Richard Alligierمشاهده پروفایل

مدرس

• Machine Learning
• Air Traffic Management
• Optimization Algorithms
• +۵ مورد دیگر

Richard Alligier is a lecturer and researcher at Ecole Nationale de l'Aviation Civile (ENAC) specializing in artificial intelligence applications for air traffic management. His work bridges machine learning, optimization algorithms, and trajectory prediction to address critical challenges in conflict detection and resolution for both manned and unmanned aerial systems. Research Focus : Trajectory prediction, conflict resolution, UAV collision avoidance, mass/thrust estimation, and uncertainty modeling Key Collaborations : Nicolas Durand, David Gianazza, Xavier Olive, Kim Gaume, Sarah Degaugue His publications (2011–2024) analyze trajectory uncertainty quantification, 3D maneuver visualization, and human-aligned deconfliction strategies using ADS-B data. Notable contributions include: Dual-horizon collision avoidance algorithms integrating human factors High-confidence interval prediction frameworks Wind parameter extraction from flight paths Machine learning models for climb/descent phase optimization Awarded the 2019 best paper in trajectory prediction , his work emphasizes operational alignment between automated systems and air traffic controller decision-making. He employs GPU acceleration, metaheuristics, and deep learning architectures while maintaining a focus on practical implementation through partnerships with ONERA and ISAE-SUPAERO.

Alexandre Gondranمشاهده پروفایل

پژوهشگر

• Quantum Mechanics
• Optimization
• Graph Coloring
• +۴ مورد دیگر

Alexandre Gondran is a researcher at École Nationale de l'Aviation Civile (National School of Civil Aviation) with a career spanning quantum mechanics, combinatorial optimization, and air traffic management. His work bridges foundational physics and practical operations research, focusing on quantum interpretations (de Broglie-Bohm theory, double-scale models), graph coloring algorithms, and robust flight path allocation. Education : PhD in Computer Science (2008) from University of Technology of Belfort-Montbéliard and University of Franche-Comté. Research Interests : Alexandre's research explores quantum mechanics' foundational aspects through de Broglie-Bohm theory, semiclassical limits, and path integral methods. In optimization, he develops hybrid metaheuristics and exact algorithms for graph coloring, gate allocation, and air traffic conflict resolution. Publication Trends : His articles demonstrate dual expertise in quantum foundations (12/15 papers) and optimization (3/15), with recent works extending to stochastic processes and tropical mathematics applications in physics. Collaborations : Alexandre frequently collaborates with Michel Gondran (quantum theory), Laurent Moalic (graph algorithms), and Nicolas Barnier/Ruixin Wang (transportation systems), reflecting interdisciplinary research across physics, computer science, and aviation engineering.

Marcel Mongeauمشاهده پروفایل

استاد

• Operations Research
• Global Optimization
• Numerical Optimization
• +۵ مورد دیگر

Marcel Mongeau is a Professor in Operations Research at the École Nationale de l'Aviation Civile (ENAC) in Toulouse, France, affiliated with the OPTIM team under the MORO axis . His research focuses on operational research, global optimization, numerical optimization, and mixed-integer programming, with applications in aeronautics, chemical engineering, life sciences, and other industries. Education PhD in Combinatorics & Optimization (1991), University of Waterloo, Canada MSc in Mathematics (1987), University of Montreal, Canada BSc in Mathematics (1985), University of Montreal, Canada Habilitation to Direct Research (2003), Paul Sabatier University, France Research Interests : Mongeau's work addresses complex optimization problems through mathematical modeling and algorithm development. Key areas include aircraft trajectory planning, contrail avoidance, stochastic programming, and multi-modal transportation optimization. His methodologies integrate exact optimization, heuristic approaches, and computational modeling. Publications Trends : Recent publications emphasize air traffic flow management , contrail-safe trajectories , stochastic aircraft scheduling , and multi-modal transportation synchronization . Applications span environmental impact minimization, machining efficiency, and climate-aware aviation planning. Scientific Recognition : He is a Member of the Academy of Technologies , reflecting his contributions to applied mathematical sciences. Advising & Grants : Mongeau has supervised PhD students and postdoctoral fellows, particularly in optimization and operational research. His research has been supported through collaborations with institutions like IBM, INRIA, and CNRS. Labs & Teams : He is associated with the OPTIM team at ENAC and previously worked with the MOGISA group at LAAS-CNRS and the Optimisation & Interactions group at Paul Sabatier University.

Ionela Prodanمشاهده پروفایل

دانشیار

• Control Engineering
• Applied Mathematics
• Model Predictive Control
• +۹ مورد دیگر

Ionela Prodan is an Associate Professor at the Laboratory of System Design and Integration (LCIS) , affiliated with Grenoble Institute of Technology, Université Grenoble Alpes, France. She is part of the CO4SYS research team and serves as deputy director of LCIS-Grenoble INP since 2021. Ph.D. in Control Engineering (2012, Supélec, France) HDR (Habilitation to Conduct Research, 2020) B.S. in Automation and Applied Informatics (2009, Univ. Politehnica of Bucharest, Romania) Research Interests focus on multi-disciplinary domains with expertise in control systems and applied mathematics. Her work spans: Control Theory: Model Predictive Control (MPC), distributed/decentralized approaches Optimization: Mixed-integer programming, set-theoretic methods Applications: Motion planning for autonomous vehicles, energy management in DC microgrids Teaching Activities include: Doctoral courses on constrained optimization-based control (English, EEATS doctoral school) Formation for engineers (Eramet Ideas, France) Courses in English/French for 3rd to 5th year students at Esisar and Ho Chi Minh Institute of Technology Leadership Roles: Vice-chair of the 2022 IFAC CAO organizing committee Associate Editor for EUCA European Control Conference (2022–present) and IEEE Transactions on Control Systems Technology (2023–present) Member of IFAC Technical Committee 6.3 Power and Energy Systems (2020–present) Co-animator of the CT CPNL French research group on Nonlinear Model Predictive Control (2021–present)

• Graph Matching
• Combinatorial Optimization
• Document Analysis
• +۳ مورد دیگر

Romain Raveaux is an Assistant Professor at the University of Tours' Computer Science Laboratory (LIFAT). His research intersects machine learning, operations research, and graph theory for environmental monitoring and document analysis. Applications include insect counting for biodiversity assessment and document image quality evaluation. Raveaux holds a PhD from the University of La Rochelle and has authored over 40 publications. His methodologies combine combinatorial optimization with structural pattern recognition, addressing problems like graph matching and edit distance computation. Research Highlights Graph-based representations for pattern recognition Mixed-integer programming for graph matching Machine learning models for insect classification Document image analysis frameworks

• Scheduling
• Supply Chain Management
• Operational Research
• +۴ مورد دیگر

Ali Skaf is an Associate Professor at CESI LINEACT, affiliated with the Engineering and Numerical Tools Research team. His research focuses on scheduling problems, supply chain resilience, multi-objective optimization, and port logistics. He holds a PhD in Automatics from Belfort Montbéliard University of Technology (2020) and a Master's in Computer Science from the Lebanese-French University (2012). His educational activities span Computer Science, Operational Research, and Mathematics across engineering cycles and preparatory courses. Skaf's work emphasizes port terminal operations, including quay crane scheduling, yard truck coordination, and mixed-integer programming models for container handling. His recent publications (2018–2022) highlight contributions to NP-completeness analysis of scheduling problems and optimization algorithms for maritime logistics. His research integrates exact methods, heuristics, and computational complexity analysis to enhance supply chain efficiency. No scientific awards are explicitly mentioned, though his active publication record reflects ongoing scholarly engagement. His advising and grants details are not documented here, but his team's focus on numerical tools and engineering applications suggests collaborative projects in industrial automation and logistics systems. Labs/Teams: Member of the Engineering and Numerical Tools Research team at CESI LINEACT, focusing on applied operational research and port logistics solutions.

Mohammed Hichame BENBITOURمشاهده پروفایل

استادیار

• Supply Chain Management
• Operations Management
• Business Analytics
• +۳ مورد دیگر

Mohammed Hichame BENBITOUR is an Assistant Professor in Logistics at EM Normandie Business School since 2021, serving as DA M2 IA for Marketing Strategy. He holds a PhD in Industrial Engineering from CentraleSupélec (2018), focusing on supplier operations in the automotive industry. His research explores supply chain management, operations optimization, and sustainability. He teaches courses like Supply Chain 4.0 Issues , Purchasing and Logistics Fundamentals , and Strategic Logistics Management . Professional experience includes a visiting researcher role at London Business School (2020). His work spans academic publications in top-tier journals like International Journal of Production Research and Journal of Environmental Management , addressing topics such as production planning, inventory control, and sustainable practices. He actively participates in international conferences, presenting at INFORMS, MSOM, and IEEE events. Research interests emphasize cross-disciplinary approaches to logistics challenges, combining data analytics with real-world industry applications. His recent studies include fair scheduling in delivery companies, renewable energy policy impacts, and personalized retail strategies. He maintains strong ties with automotive and manufacturing sectors through applied research.

Amaya Nogales Gómezمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Machine Learning
• Telecommunications
• +۳ مورد دیگر

Amaya Nogales Gómez is an Associate Professor at the Interdisciplinary Institute for Artificial Intelligence (3IA) at Université Côte d’Azur and a member of the Wimmics Research Team. Her research focuses on combinatorial optimization, machine learning, and their applications in telecommunications and operations research. She holds a Ph.D. in Mathematics from the University of Seville (2015) and has held roles including Postdoctoral researcher at I3S and researcher at Huawei France (2014–2019). Education: PhD in Mathematics, University of Seville (2015); Postdoctoral studies at I3S, Sophia Antipolis. Her research interests include: Optimization algorithms for resource allocation and network design Machine learning techniques for pattern recognition and classification Applications in mobile video streaming and radio resource management Key research areas span telecommunications optimization, data-driven decision making, and mathematical modeling. She has contributed to patents and publications in top-tier conferences/journals. Current openings: See internship on Fairness-aware NLP here .

Sonia Cafieriمشاهده پروفایل

استاد

• Nonlinear Optimization
• Global Optimization
• Combinatorial Optimization
• +۳ مورد دیگر

Sonia Cafieri is a Professor at the École Nationale de l'Aviation Civile (ENAC) in Toulouse, part of the Université de Toulouse. She leads the Mathematics of Optimization and Operations Research (MORO) group within the OPTIM research team. Her roles include membership in the Managing Board of EUROPT and the Nonlinear Mathematical Programming group of GdR-ROD. She chairs the Program Committee of EUROPT 2021 and serves on ENAC's Research and Doctoral Councils. Education: HDR in Applied Mathematics (2012, Université Paul Sabatier), PhD (2006, University of Naples), and Laurea in Mathematics (2001, Second University of Naples). Research focuses on Nonlinear Optimization, Global Optimization, Combinatorial Optimization (network clustering), and Operations Research applications in air transportation and engineering. Recent work addresses air traffic management, trajectory optimization, and stochastic programming for robust scheduling. Publications span optimization methodologies and applications, with a focus on aircraft conflict resolution, drone trajectory planning, and robust cyclic scheduling. Software contributions include ROSE (reformulation engine) and COUENNE (MINLP solver). Teaching includes courses on Numerical Analysis, Combinatorial Optimization, and Operations Research for Air Transportation at ENAC and other institutions.

• Mechanical Engineering
• Additive Manufacturing
• Smart Materials
• +۴ مورد دیگر

Pascal LAFON is a Full Professor at the University of Technology of Troyes (UTT), affiliated with the Laboratory of Mechanical & Material Engineering (LASMIS) and the Department of Physics, Mechanics, Materials and Nanotechnology . He serves as the Director of Corporate Relations at UTT since 2023 and previously led LASMIS lab from 2012-2016. His academic duties include coordinating the 'Mechanics, Material and Advanced Manufacturing' master’s program (2018-2023) and the UTT doctoral program's 'Material, Mechanics, Optics and Nanotechnology' training (2012-2023). Director of Corporate Relations, UTT (2023-present) Head, LASMIS Lab (2012-2016) Master’s Program Coordinator (2018-2023) Doctoral Training Supervisor (2012-2023) His research focuses on Mechanical Optimization (mixed/random variables, nonlinear objectives), Additive Manufacturing (design, material behavior), and Smart Material Applications . Current projects integrate metamodeling (RBF, Kriging) with multi-objective optimization for manufacturing processes and structural systems. Publications and projects demonstrate expertise in: metal forming , composite materials , springback analysis , and breakwater design . He has supervised 13 PhD students since 1996, including international collaborations with Lebanese University and Northwestern Polytechnical University .