جستجوی استاد راهنمای دانشگاهی

Xavier Brussetمشاهده پروفایل

استاد

• Supply Chain Management
• Logistics
• Operations Management
• +۶ مورد دیگر

Xavier Brusset is a Professor in Supply Chain at SKEMA Business School since 2016, where he also serves as Director of the PRISM Research Center since 2017. Previously, he held professorial positions at Toulouse Business School (2015-2016) and ESSCA School of Management (2009-2015), where he was responsible for the Master 2 in Purchasing and Supply Chain Management program. His academic journey includes a PhD in Management Sciences from Université Catholique de Louvain (2010) and a Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense (2016). His research spans multiple critical areas in supply chain management, with particular focus on supply chain resilience, blockchain applications, weather risk management, and pandemic impacts on supply chains. Brusset has developed innovative approaches to understanding how supply chain partners interact, how information affects their behavior, and how external disruptions like weather anomalies and pandemics impact operational efficiency. His work bridges theoretical models with practical applications, often developing decision-support tools for managers facing complex supply chain challenges. Brusset's publication record shows a clear evolution of research interests, beginning with foundational work on supply chain contracts and information sharing, then expanding to weather risk management, and most recently focusing on pandemic disruptions and blockchain applications. His 15 most recent publications (2018-2025) demonstrate increasing sophistication in modeling complex supply chain phenomena, with particular emphasis on network effects, ripple effects, and multi-echelon optimization under disruption scenarios. Editorial board member of Logistics Research Editor of International Journal of Retail and Distribution Management (2022-2023) Recognized EU expert for CINEA research projects evaluation Organizer of the Colloquium on European Research in Retailing (CERR) Reviewer for multiple top journals including International Journal of Production Economics As an advisor, Brusset has supervised doctoral students including R. Alkhudary (co-director, Université Paris 2 Panthéon-Assas) and V. Capocasale (rapporteur). His professional experience extends beyond academia to include industry roles in financial markets and logistics technology, having co-founded WebLogistix, a platform for sharing logistics information in Argentina. His research has practical applications across multiple sectors, particularly in retail, food supply chains, and manufacturing, where he develops tools to help managers mitigate risks and optimize operations under uncertainty.

Christine Di Martinellyمشاهده پروفایل

دانشیار

• Operations Management
• Healthcare Systems
• Supply Chain Optimization
• +۱ مورد دیگر

Christine Di Martinelly is an Associate Professor in Operations Management at IÉSEG School of Management. She holds two PhDs in Economic and Management Sciences from Louvain School of Management and Applied Sciences from INSA Lyon. Her research focuses on operations management, healthcare systems, supply chain optimization, and resource allocation. Di Martinelly's extensive publication record addresses operational challenges in healthcare, including surgical scheduling, inventory management, and resource allocation. Her work employs mathematical modeling, optimization algorithms, and multicriteria decision analysis to improve efficiency in healthcare delivery systems. She has served as Academic Director at IÉSEG since 2014 and has professional experience as a consultant at Arthur Andersen earlier in her career.

Nadjib BRAHIMIمشاهده پروفایل

دانشیار

• Supply Chain Management
• Production Planning and Scheduling
• Operations Research
• +۴ مورد دیگر

Nadjib Brahimi is an Associate Professor at Rennes School of Business, specializing in Supply Chain Management and Operations Research. He holds a PhD in Production and Logistics Systems from Université de Nantes and has extensive academic experience, including roles as Academic Head of the Supply Chain Management & Information Systems department (2019–2020) and Programme Manager of the MSc in Data and Business Analytics. His expertise spans Production Planning, Supply Chain Optimization, and Reconfigurable Manufacturing Systems. Education: PhD in Production and Logistics Systems, Université de Nantes, 2004 M.Sc. in Automatic Control and Applied Computing, Ecole Centrale de Nantes, 2001 Engineering Degree in Electronics and Electrical Engineering, National Institute of Electronics and Electrical Engineering, Boumerdes, Algeria, 1999 Research Focus: His work emphasizes optimization of production systems, reconfigurable manufacturing, and sustainable supply chains. Key areas include task reassignment in assembly lines, biomass supply chain design, and disruption resilience strategies. Key Contributions: Over 40 peer-reviewed articles in journals like International Journal of Production Economics and European Journal of Operational Research . Developed robust optimization models for supplier selection and production routing. Advocated for circular economy principles in hybrid manufacturing systems. Labs/Teams: He collaborates with research groups on reconfigurable manufacturing systems and bioenergy supply chain design, contributing to projects in France, UAE, and Algeria.

• AI-enabled communications
• Green and energy-efficient communications
• Online optimization and machine learning
• +۶ مورد دیگر

E. Veronica Belmega is a Full Professor at ESIEE Paris (Université Gustave Eiffel) and a researcher at the LIGM laboratory in Marne-la-Vallée, France. Previously, she served as an Associate Professor at ENSEA graduate school and Deputy Director of the ETIS laboratory in Cergy. She holds an Engineer Degree from the University Politehnica of Bucharest, M.Sc. and Ph.D. from Université Paris-Sud 11, and an HDR habilitation from Université de Cergy-Pontoise. Her research focuses on AI-driven communication systems, energy efficiency, online optimization, and cyber-physical security, with a strong emphasis on applications in smart grids and IoT. Her work spans securing wireless communications against adversarial attacks, optimizing resource allocation in cognitive radio networks, and leveraging machine learning for GNSS localization and MIMO systems. Notable contributions include game-theoretic frameworks for PMU deployment and energy-efficient NOMA systems. Belmega has received prestigious awards such as the 2021 CY Alliance Award and the L’Oréal-UNESCO fellowship, and serves as an Area Editor for IEEE Trans. on Machine Learning in Communications and Networking. Current projects include a CEA LETI postdoc position on AI localization and a PEPR 5G project. She actively contributes to special issues like the EURASIP JASP on sustainable wireless communications. Belmega’s advising includes PhD student S. Maleki, co-author of her 2024 IEEE SmartGridComm Best Paper Award-winning work.

Romain Raveauxمشاهده پروفایل

دانشیار

• Image Analysis
• Machine Learning
• Structural Pattern Recognition
• +۵ مورد دیگر

Romain Raveaux is an Associate Professor at the LIFAT Computer Science Laboratory, University of Tours, affiliated with Polytech Tours. His research focuses on Image Analysis, Machine Learning, Structural Pattern Recognition, Graph Matching, Graph Neural Networks, Discrete Optimization, Reinforcement Learning, and Transfer Learning . Email: romain.raveaux@gmail.com , romain.raveaux@laposte.net Address: 64 av. Jean Portalis, Tours, France, 37200 Phone: +33 (0)2 47 36 14 27 Research Interests Graph Matching and Neural Networks Discrete Optimization for Pattern Recognition Transfer Learning in Graph-Based Models Historical Document Analysis Scientific Trends His recent work bridges Graph Neural Networks with Mixed-Integer Programming , focusing on Image Semantic Segmentation and Graph Cycle Detection . Earlier studies emphasize Genetic Algorithms for graph classification and Graph Edit Distance optimization in pattern recognition.

Sophie Huibertsمشاهده پروفایل

پژوهشگر

• Linear Programming
• Mixed Integer Programming
• Algorithm Analysis
• +۴ مورد دیگر

Sophie Huiberts is a CNRS researcher at LIMOS, Clermont Auvergne University in Clermont-Ferrand since fall 2023. Previously, she was a Simons Junior Fellow at Columbia University in New York City, hosted by Tim Roughgarden. She completed her PhD research at Centrum Wiskunde & Informatica in Amsterdam under Daniel Dadush and received her doctorate in 2022 from Utrecht University. Dr. Huiberts specializes in theoretical aspects of mathematical optimization, particularly focusing on the gap between practical performance and theoretical predictions of linear programming algorithms. Her research examines software implementations like Gurobi, CPLEX, SCIP, and HiGHS to understand why these algorithms perform better in practice than worst-case analysis would suggest. She has made significant contributions to smoothed analysis of the simplex method, establishing both upper and lower bounds on its complexity under perturbations of worst-case inputs. Analysis of her publication record shows consistent focus on bridging theoretical computer science with practical optimization methods. Her work spans linear programming theory, integer programming, combinatorial optimization, and computational geometry, with particular emphasis on understanding the geometric properties of optimization problems and the behavior of algorithms on real-world instances. Simons Junior Fellowship Dr. Huiberts maintains active engagement with the research community through social media platforms including Mastodon and Bluesky, and produces high-quality recordings of her research talks available on YouTube. She has made a conscious decision to stop air travel since 2023 due to climate concerns, demonstrating commitment to sustainable research practices while maintaining scientific connections through digital means. She is affiliated with LIMOS (Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes), a research laboratory at Clermont Auvergne University focused on computer science, modeling, and optimization systems, where she continues her investigations into the theoretical foundations of practical optimization algorithms.

• Operations Research
• Decision Analytics
• Supply Chain Management
• +۵ مورد دیگر

Laurent ALFANDARI is a Full Professor at ESSEC Business School, specializing in Operations Research and Decision Analytics within the Information Systems, Decision Sciences and Statistics (IDS) Department. He has held key academic roles including Academic Co-Director of the ESSEC-CentraleSupélec Master in Data Sciences & Business Analytics (2019–2023) and Coordinator of the Operations & Data Analytics PhD concentration (2018–2021). His research focuses on optimization techniques applied to supply chains, logistics, healthcare, and disaster preparedness. He has authored over 50 journal articles in top venues like European Journal of Operational Research and Transportation Science. Education : - Doctorate in Operations Research (Université Paris Dauphine-PSL, 1999) - Master of Research in Management Science (Université Paris Dauphine-PSL, 1995) - M.Sc in Management (ESSEC Business School, 1993) - Bachelor in Mathematics & Social Sciences (Université Paris Dauphine-PSL, 1990) Research Interests : His work addresses complex optimization challenges in urban logistics, healthcare networks, and disaster response. Notable contributions include freight-on-transit systems, autonomous robot delivery, and pandemic intervention sequencing. He emphasizes practical solutions for real-world problems through mixed-integer programming and robust optimization frameworks. Teaching & Mentoring : Teaches Decision Analytics and Operations Research across ESSEC programs (Grande École, Executive MBA, PhD). Supervised 14 PhD theses, including recent works on sustainable last-mile deliveries and healthcare analytics. Awards & Activities : 2020 ESSEC Top 4 Teaching Award, Vice-President of ROADEF (2012–2015), and leader in industrial collaborations with SNCF and Aid-Impact. Active in organizing academic conferences and serves as a journal reviewer for Annals of Operations Research and others. Labs & Collaborations : Member of LIPN (Sorbonne Université) and LAMSADE (Paris Dauphine). Consults for organizations like Babcock-Wanson and contributes to public-sector projects like EDF's ROADEF challenge.

Simon Theveninمشاهده پروفایل

استادیار

• Production Management
• Optimization Methods
• Production Scheduling
• +۴ مورد دیگر

Simon Thevenin is an Assistant Professor in the Automation, Production, and Computer Sciences Department at IMT Atlantique in France since 2018. He holds a Ph.D. from the University of Geneva (2015) and previously worked as a Postdoctoral researcher at HEC Montreal and an Algorithm Expert at Quintiq. His research focuses on optimization methods for production management, including scheduling, planning, and manufacturing line design. He leads projects such as the EU-funded ASSISTANT (2020-2023), ALICIA (2023-2025), and ACCURATE (2023-2026), advancing AI-driven solutions for sustainable manufacturing and supply chain resilience. His work integrates machine learning, robust optimization, and digital twin technologies to enhance production systems' adaptability and efficiency. Education: Ph.D. in Production Systems Scheduling, University of Geneva (2015) Teaching/Research Assistant, University of Geneva (2010-2015) Research Interests: His research emphasizes optimization under uncertainty, reconfigurable manufacturing systems, and AI applications in production. He explores topics like lot-sizing models, equipment lifecycle management, and circular manufacturing ecosystems. Grants/Projects: ASSISTANT (EU-funded, 2020-2023): AI for production digital twins ALICIA (EU-funded, 2023-2025): Circular production resource ecosystems ACCURATE (EU-funded, 2023-2026): Supply chain resilience against disruptions Labs/Teams: Part of the LS2N research lab (Modelis team) at IMT Atlantique, specializing in logistics and industrial optimization.

Mohammad REIHANEHمشاهده پروفایل

استادیار

• Operations Research
• Logistics and Supply Chain Management
• Optimization Algorithms
• +۳ مورد دیگر

Professor Mohammad REIHANEH is an Assistant Professor of Operations Management at IÉSEG School of Management. He holds a Ph.D. in Operations Management from the University of Massachusetts (USA), an MSc in Industrial Engineering from Isfahan University of Technology (Iran), and a BSc in Applied Mathematics from Ferdowsi University of Mashhad (Iran). His research focuses on optimization algorithms, vehicle routing problems, scheduling theory, and logistics systems. He is a member of the LEM research group and has published extensively in top-tier journals such as the European Journal of Operational Research and the Journal of the Operational Research Society. Education: 2018: Ph.D., Operations Management, University of Massachusetts, USA 2012: MSc, Industrial Engineering, Isfahan University of Technology, Iran 2009: BSc, Applied Mathematics, Ferdowsi University of Mashhad, Iran Research Interests: Mohammad’s work emphasizes practical applications of optimization in logistics and healthcare systems. He develops exact algorithms (e.g., branch-and-price) and heuristic methods for complex routing problems, maintenance scheduling, and resource allocation in healthcare settings. His contributions bridge theoretical advancements in operations research with real-world operational challenges in industries like renewable energy (offshore wind farms) and humanitarian logistics. Publications: His recent work addresses cutting-edge challenges such as multi-period offshore wind farm routing, hemodialysis center scheduling, and food bank distribution optimization. He frequently collaborates with international researchers on projects involving vehicle routing, reliability engineering, and control chart design for manufacturing systems. Advising & Grants: No specific student advisees or grant details are listed in the provided materials.

José Netoمشاهده پروفایل

استاد

• Combinatorial Optimization
• Mathematical Programming
• Operations Research
• +۳ مورد دیگر

Prof. José Neto is a Professor at Télécom SudParis, part of the Institut Polytechnique de Paris, affiliated with the SAMOVAR research department. His work focuses on combinatorial optimization, mathematical programming, and graph theory. He has contributed to polyhedral studies of cut and assignment polytopes, spectral bounds for graph partitioning, and optimization algorithms for mixed-variable and blackbox problems. His research spans topics like network pricing complexity, domination in graphs, and robustness verification in neural networks. He has published extensively in top journals such as Mathematical Programming, Discrete Applied Mathematics, and Networks. Key contributions include developing efficient algorithms for combinatorial pricing, analyzing optimization relaxations, and exploring structural properties of discrete mathematical objects. His work bridges theoretical foundations and practical applications in operations research, with recent interests in binarized neural network verification and mixed-variable optimization. He has collaborated on projects related to cloud virtual machine mapping and combinatorial pricing models. Labs/Teams: Active member of the SAMOVAR laboratory, specializing in applied mathematics and optimization research.

• Mathematical Optimization
• Decomposition Methods
• Machine Learning
• +۳ مورد دیگر

Emiliano Traversi is an Associate Professor in the Department of Information Systems, Data Analytics and Operations at ESSEC Business School. He holds a PhD in Operations Research from the University of Bologna and previously served as a Full Professor at LIRMM, University of Montpellier. His research focuses on mathematical optimization, decomposition methods, and machine learning, with recent emphasis on network slicing in UAV-based 5G systems and multi-drone formation strategies. His work bridges theoretical optimization frameworks with practical applications in telecommunications and autonomous systems. Education: PhD in Operations Research, University of Bologna Habilitation à diriger des recherches, Business Administration, Sorbonne Université (2023) Research Interests: Mathematical Optimization (Convex/Non-Convex) Decomposition Algorithms (e.g., Benders, Dantzig-Wolfe) Network Slicing & Resource Allocation for 5G/6G Autonomous Systems & Multi-Agent Coordination Applications in Telecommunications and Transportation Recent Research Trends: His 2025 publications highlight advancements in UAV-enabled 5G network slicing frameworks (EASIER) and mathematical foundations for drone fleet formations. Earlier work extends to optimization methods for transportation systems, quantum computing challenges, and power grid management through semidefinite relaxations. Professional Contributions: 20+ peer-reviewed articles in top journals/conferences (e.g., Computer Networks, AICA) Development of optimization frameworks with real-world applications Labs/Teams: Active collaborations in ESSEC's data analytics initiatives and international projects on UAV communication systems.

Shahin Gelarehمشاهده پروفایل

دانشیار

• Operations Research
• Logistics and Supply Chain Management
• Transportation Planning
• +۹ مورد دیگر

Shahin Gelareh is an Associate Professor in Operations Research and Logistics at the Université d'Artois, France, affiliated with the Department of Networks and Telecommunications at the IUT de Béthune. He holds a PhD in Optimization from the Technical University of Kaiserslautern (2008), an MSc in Applied Mathematics from the University of Sistan and Baluchestan (2005), and a BSc from Ferdowsi University of Mashhad (2003). His research focuses on Locational Analysis , Integer Programming , Metaheuristics , Global Network Design , and applications in Maritime Transport , Supply Chain , and Telecommunications . Notable areas include hub-and-spoke network optimization, liner shipping fleet deployment, and competitive analysis using game theory. Recent publications emphasize innovations in Neural Benders Decomposition for optimization, cross-docking systems , and hub location routing . His work spans theoretical advancements and industry collaborations in transportation and telecom sectors. Professional activities include memberships in leading OR societies (EWGLA, EWGT, VeRoLog) and roles as an ad-hoc reviewer for high-impact journals like Transportation Research Part E and European Journal of Operational Research .

Odile Bellenguezمشاهده پروفایل

استاد

• Computer Science
• Ethics in Technology
• Operations Research
• +۳ مورد دیگر

Professor Odile Bellenguez is a faculty member in the Automation, Production and Computer Sciences department at IMT Atlantique. Her work focuses on integrating ethical considerations into algorithm design, particularly in personnel scheduling and decision support systems. She holds a University Diploma in Philosophy from Université Paris Nanterre, enhancing her interdisciplinary approach. Her research bridges computer science, discrete mathematics, and social sciences, with collaborations in sociology, psychology, and management science. Notable projects include co-supervising a thesis on ethical inclusion in healthcare scheduling and developing fair nurse rostering algorithms. She also pioneered a philosophy-infused framework for algorithmic ethics, addressing fairness and equity in automated systems. Professor Bellenguez actively engages in pedagogy, designing courses that teach ethical implications of algorithms through case studies like traffic navigation and workforce scheduling. Her recent work emphasizes cross-disciplinary dialogue to address societal challenges posed by algorithmic systems. Her contributions span over 50 publications, with a focus on scheduling optimization (RCPSP variants, nurse rostering) and ethical frameworks for automated decision-making. She plans to host a summer school for PhD students exploring ethics in algorithmics.

Axel Parmentierمشاهده پروفایل

مدرس

• Operations Research
• Machine Learning
• Data-Driven Optimization
• +۵ مورد دیگر

Axel Parmentier is a Lecturer and researcher at the École Nationale des Ponts et Chaussées, where he founded the AI for Air Transport industry research chair with Air France. His work focuses on the intersection of operations research and machine learning, particularly in data-driven combinatorial optimization and stochastic optimization, with industrial applications in air transportation, supply chain, and predictive maintenance. He holds a Ph.D. and has been recognized with awards including the AMIES Dissertation Award (2017) for applied mathematics with industrial impact and the Robert Faure Prize (under 35) from ROADEF. His research also includes contributions to structured reinforcement learning, optimization layers in machine learning, and explainable AI for operational decisions. Awards: AMIES Dissertation Award, Robert Faure Prize Labs/Teams: CERMICS laboratory, AI for Air Transport Chair (collaboration with Air France) Grants/Projects: Continent-scale inventory routing solutions, Renault’s logistics optimization His advising includes students like Victor Cohen, whose work on predictive maintenance was featured on France Culture.

• Operations Research
• Logistics
• Supply Chain Management
• +۳ مورد دیگر

Remy Dupas is a Professor at the University of Bordeaux , affiliated with the IMS Bordeaux - Integration, Material to System Laboratory within the Production Engineering research group. His work focuses on Operations Research , Logistics , and Transportation Systems , developing advanced algorithms for complex routing and supply chain optimization problems. Research Highlights: Innovative Branch-Cut-and-Price algorithms for Two-Echelon Vehicle Routing Problems with drones and time windows City Logistics models for sustainable urban freight distribution in Tokyo MultiAgent Systems for supply chain coordination 3D Loading Constraints integration in pickup-and-delivery problem solving Rail-Rail Transshipment scheduling methodologies Key Publications (2024-2007) demonstrate expertise in Combinatorial Optimization , Dynamic Routing , and Interoperability Metrics for enterprise systems. His research is characterized by strong Algorithm Development and Real-Time Transportation solutions.