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Junkai HEView profile

Assistant Professor

• Operations Research
• Supply Chain Management
• Remanufacturing
• +3 more

Junkai HE serves as an Assistant Professor in the Operations, Supply Chain and Information Management department at KEDGE Business School and is affiliated with the CESIT research center since September 2024. He earned his PhD in mathematics and computer science from Paris-Saclay University (France) in 2020, following which he conducted postdoctoral research at IRT SystemX and Télécom SudParis. His research specializes in decision making under uncertainty through advanced modeling and algorithm design , with primary applications in supply chain management , remanufacturing , and maintenance optimization . Key methodologies include stochastic programming, multi-objective optimization, and predictive maintenance modeling for complex industrial systems. Analysis of his 2019-2024 publications reveals a consistent trajectory in applying operations research to sustainable industrial practices. His work increasingly focuses on uncertainty integration in disassembly line balancing and remanufacturing systems, while maintaining strong foundations in classical scheduling problems for manufacturing and logistics. Publications predominantly appear in top-tier journals like the International Journal of Production Economics and Computers & Operations Research. He teaches core operations management courses including operations research, production planning, and logistics, demonstrating active educational engagement. His research at CESIT likely involves industry collaborations addressing real-world supply chain challenges, though specific grant details are unmentioned. As a CESIT researcher, he contributes to KEDGE's industrial technology research initiatives, bridging theoretical optimization methods with practical applications in manufacturing and logistics systems. Current work appears oriented toward sustainable supply chain innovations and digital transformation of maintenance practices.

Ahmed El-SayedView profile

Associate Professor

• Robotics
• Artificial Intelligence
• Fuzzy Systems
• +4 more

Dr. Ahmed El-Sayed is an Associate Professor in the Department of Electrical and Computer Engineering at the School of Engineering, University of Bridgeport. He holds a Ph.D. in Computer Science and Engineering (2016) and M.Sc. degrees in Computer Engineering (2011) and Engineering Mathematics (2006). Ph.D. in Computer Science and Engineering, University of Bridgeport (2016) M.Sc. in Computer Engineering, University of Bridgeport (2011) M.Sc. in Engineering Mathematics, Alexandria University (2006) B.Sc. in Electrical Engineering, Alexandria University (2003) His academic work focuses on robotics , artificial intelligence , and computer vision , with specific emphasis on fuzzy systems , machine learning , and soft computing . His research spans theoretical developments and practical implementations in autonomous systems , medical imaging , and industrial automation . The 15 most recent publications highlight his contributions to generative models , medical diagnostics , disassembly sequencing , and high-dimensional feature analysis . These works intersect disciplines such as robotics , machine learning , and sustainable manufacturing . Professional Memberships: IEEE ASEE Phi Kappa Phi Upsilon Pi Epsilon Egyptian Engineering Syndicate (lifetime member) He teaches courses including Embedded Systems Design , Computer Vision , and Introduction to Autonomous Vehicles .

Erdal ErelView profile

Professor

• Production Operations Management
• Manufacturing Systems Design
• Assembly and Disassembly Line Balancing
• +4 more

Erdal Erel is a Professor of Operations Management (OM) and currently serves as the Vice Rector in charge of administrative and financial affairs at Bilkent University's Faculty of Business Administration. He holds a B.S. in Industrial Engineering from Istanbul Technical University (1981), an M.S. from Stanford University (1983), and a Ph.D. from Virginia Polytechnic Institute and State University (1987). His academic career has been dedicated to advancing research in Production Operations Management, focusing on manufacturing systems design, assembly/disassembly line balancing, scheduling, and project management. Erel's educational background includes: B.S. in Industrial Engineering, Istanbul Technical University (1981) M.S. in Industrial Engineering, Stanford University (1983) Ph.D. in Industrial Engineering and Operations Research, Virginia Polytechnic Institute and State University (1987) His research interests span several critical areas of operations management, including manufacturing systems design, assembly and disassembly line balancing, scheduling and sequencing methodologies, and project management. He has made significant contributions to robust optimization techniques applied to time-cost trade-offs and stochastic modeling in production systems. His work emphasizes practical solutions for complex operational challenges through advanced algorithms like ant colony optimization and beam search methods. Erel's publications reflect a focus on optimization in production systems, scheduling algorithms, and decision models under uncertainty. His research bridges theoretical advancements with real-world applications in manufacturing and service industries, addressing issues such as cost minimization, robust scheduling, and efficiency improvements in assembly line operations. Erel has contributed extensively to his field but no specific scientific awards are mentioned in the provided text. No specific information about advising students or grants is provided in the text. Erel's involvement in collaborative projects, including work with colleagues like I. Sabuncuoglu and J.B. Ghosh, highlights his role in interdisciplinary research teams focused on operational efficiency and advanced manufacturing technologies.

• Industrial Logistics
• Supply Chain Management
• Digitalization in Logistics
• +7 more

Fabio Sgarbossa is a Full Professor of Industrial Logistics at NTNU's Department of Mechanical and Industrial Engineering, Faculty of Engineering. He holds editorial roles in journals like the International Journal of Production Research and has authored over 150 publications. His research focuses on industrial logistics systems, supply chain resilience, and Industry 4.0 technologies, with a strong emphasis on human-centric design and digital transformation. Education: Master's in Management Engineering (2005) and PhD in Industrial Engineering (2010), both from the University of Padova, Italy. Research Interests: Design and management of industrial logistics; supply chain optimization; digitalization in manufacturing; human factors in production systems; autonomous mobile robots (AMRs); predictive maintenance; and circular economy integration. He leads NTNU's Logistics 4.0 Lab and collaborates on EU-funded projects. Key Contributions: Developed frameworks for Industry 4.0 adoption in logistics, decision support systems for additive manufacturing, and human-centric warehouse design. His work bridges operational efficiency with worker well-being. Grants & Collaborations: Active in EU and national projects focusing on smart manufacturing, resilient supply chains, and aging workforce challenges. Supervises graduate students in logistics systems and technology integration. Labs/Teams: Head of Logistics 4.0 Lab at NTNU, collaborating with industry partners on AMR implementations and digital twin applications.

Yuvin Adnarain ChinniahView profile

Professor

• Occupational Health and Safety
• Industrial Safety
• Machine Safety
• +5 more

Dr. Yuvin Adnarain Chinniah serves as a Full Professor and Department Director in the Department of Mathematical and Industrial Engineering at Polytechnique Montreal. His expertise spans occupational health and safety, industrial safety engineering, and machinery risk assessment. He actively contributes to the Research Group on Globalisation and Management of Technology (GMT) and Laboratoire Poly-Industries 4.0. Dr. Chinniah's research focuses on occupational health and safety with particular emphasis on machinery safety, risk assessment methodologies, human-robot collaboration, and safety standards implementation. His work bridges theoretical frameworks with practical applications in industrial settings, addressing critical issues like confined space safety, lockout/tagout procedures, and safety in Industry 4.0 environments. His research integrates ISO and CSA standards into practical safety solutions for industrial machinery. His recent publications demonstrate a clear trajectory from traditional machine safety toward advanced applications involving robotics, digital transformation, and human-robot collaboration. The research consistently addresses safety optimization in manufacturing processes, with increasing focus on cyber-physical systems, AI integration for hazard detection, and safety-driven production planning. His work maintains strong connections to industrial standards while pushing boundaries in collaborative robotics safety. Dr. Chinniah has successfully supervised 9 Ph.D. students and 10 Master's students, with thesis topics covering confined space safety, lockout/tagout procedures, human-robot collaboration safety, and machinery risk assessment. His teaching portfolio includes key courses in safety engineering, ergonomics, and maintenance engineering. He leads significant research projects related to occupational safety in industrial settings, with particular focus on machinery safety standards implementation and risk assessment methodologies.

• Operations Research
• Optimization under Uncertainties
• Scheduling Algorithms
• +4 more

Faicel HNAIEN is a Full Professor at the Université de Technologie de Troyes (UTT), where he leads the Computer Science and Applied Mathematics Academic Department since December 2024. He also heads the Optimization Axis (LIST3N laboratory) with 30 members and oversees the International Master's Track in Logistics and Transport in Togo since 2023. His research focuses on optimization under uncertainties, scheduling algorithms, inventory control, wireless sensor networks, and quantum optimization. His work bridges theoretical advances with practical applications in manufacturing systems, energy management, and logistics. Responsibilities include academic leadership roles, strategic planning for research initiatives, and international program coordination. His recent projects address challenges like energy cost optimization in production scheduling, robust supply chain management under uncertainty, and deployment strategies for sensor networks in hazardous environments. He actively contributes to interdisciplinary research, integrating stochastic modeling, combinatorial optimization, and quantum computing approaches. His publications span high-impact journals such as Annals of Operations Research and European Journal of Industrial Engineering. Research trends emphasize hybrid methods (exact/ heuristic), stochastic programming for inventory systems, and multi-objective optimization in dynamic environments. Current efforts explore quantum formulations for scheduling problems and AI-driven solutions for supply chain resilience.

• Production Systems Engineering
• Supply Chain Design and Optimization
• Operational Research
• +3 more

Professor Alexandre Dolgui is the Director of the Department of Automation, Production, and Computer Science (DAPI) at IMT Atlantique, France. A Fellow of IISE and Highly Cited Researcher (Clarivate), he serves as Editor-in-Chief of the International Journal of Production Research. His expertise spans production systems, supply chain engineering, and operational research, with over 360 journal articles and 37 books. Education: HDR (University of Technology of Compiègne, 2000), PhD in Cybernetics (Academy of Science of Belarus, 1990) Research focuses on production system design , supply chain resilience , and discrete optimization , addressing challenges in human-robot collaboration, Industry 5.0, and yield uncertainty. His work integrates machine learning with stochastic programming for adaptive manufacturing solutions. Key contributions include constraint programming models for assembly lines, robust optimization frameworks for biorefineries, and digital twin methodologies for supply chain risk management. He has received multiple best paper awards and led international research projects like DREAMS and DISC. Scientific leadership: Board member of IFPR, Senior advisor to Chinese Academy of Sciences, founder of EVI European Virtual Institute

Süleyman MeteView profile

Associate Professor

• Operations Research
• Modeling and Optimization
• Multi-criteria Decision Making
• +4 more

Süleyman Mete is an Associate Professor in the Industrial Engineering Department at Gaziantep University's Faculty of Engineering. He has been serving in this position since 2021, following previous roles as a Doctor Lecturer at Gaziantep University (2019-2021) and Munzur University (2017-2019). His academic career began as a Research Assistant at Gaziantep University (2011-2016) and Tunceli University (2010-2011). Dr. Mete earned his Doctorate in Industrial Engineering from Gaziantep University (2013-2017), followed by a Master's degree in Industrial Engineering from the same institution (2011-2013). He completed his undergraduate studies in Industrial Engineering at Selcuk University (2005-2010). Dr. Mete's research focuses on Operations Research, Modeling and Optimization, and Multi-criteria Decision Making. His work spans several specialized areas including disassembly line balancing, humanitarian logistics, risk assessment, and fuzzy logic applications. His research integrates mathematical programming with practical industrial applications, particularly in disaster response, sustainable manufacturing, and supply chain optimization. He has developed innovative approaches combining various multi-criteria decision-making methods with fuzzy logic to address complex real-world problems in occupational safety, transportation, and humanitarian aid distribution. His extensive publication record demonstrates a clear trajectory toward increasingly complex applications of optimization techniques, particularly in humanitarian contexts. Recent work shows a strong focus on drone-assisted logistics, urban mobility sustainability, and advanced risk assessment methodologies using various fuzzy set approaches. His research consistently bridges theoretical methodological development with practical applications in industrial engineering problems. University 2% Most Influential Scientist (2023) University 2% Most Influential Scientist (2022) Dr. Mete has successfully supervised numerous graduate students through their thesis work, with a particular focus on humanitarian logistics, disassembly line balancing, and risk assessment applications. His research projects include "Sustainable, Digital, and Smart Humanitarian Logistics in Disaster Relief Operations" (EU-funded) and "Data-Driven and Web-Based Decision Support System Development for Integrated Optimization of Vector Control Process" (Tübitak 1505). He has also served as a visiting researcher at Karlsruhe Institute of Technology (KIT) in Germany under the TÜBİTAK 2219 Postdoctoral Research Program. Dr. Mete's work demonstrates strong integration between theoretical methodological development and practical applications, particularly in humanitarian contexts and industrial engineering problems. His research group appears to focus on optimization techniques applied to real-world challenges in disaster response, sustainable manufacturing, and supply chain management.

Olga BATTAIAView profile

Professor

• Operations Management
• Supply Chain Management
• Production Systems Optimization
• +7 more

Olga Battaïa is Senior Professor in the Department of Operations Management and Information Systems at KEDGE Business School, where she also serves as Associate Dean for Research. Her academic journey includes a PhD in Industrial Engineering from École nationale supérieure des mines de Saint-Étienne (2007) and accreditation to supervise research (HDR, 2014). Education PhD in Industrial Engineering, École nationale supérieure des mines de Saint-Étienne, 2007 HDR (Accreditation to Supervise Research), 2014 Research Focus Professor Battaïa’s research lies at the intersection of operations management , supply-chain optimization , and decision-science methods . She develops mathematical models and algorithms that improve the design and performance of production systems, reconfigurable manufacturing lines, closed-loop supply chains, and collaborative human-robot systems. Her work embraces sustainability challenges, ergonomic considerations, and uncertainty management. Recent investigations include: Dynamic vaccine-allocation models responding to pandemic realities Ergonomic integration in human-robot collaborative workstations Electric-bus charging-network design for sustainable urban mobility Robust resource-leveling techniques under project uncertainty Publication Impact Across 200+ refereed publications, her 2023–2025 output alone spans International Journal of Production Economics , IJPR , Computers & Industrial Engineering , Transportation Research Part E , and flagship conferences such as CIRP ANNALS. Thematic trends reveal deepening emphasis on (i) sustainable and resilient supply-chain design, (ii) advanced exact and heuristic optimization for reconfigurable manufacturing, and (iii) human-centric production systems. Editorial & Professional Service Associate Editor, Journal of Manufacturing Systems (Elsevier) Associate Editor, IISE Transactions Associate Editor, Omega—The International Journal of Management Science Associate Member, International Academy for Production Engineering (CIRP) Member, IFAC Technical Committee on “Manufacturing Modelling for Management and Control” Doctoral Advising & Research Leadership Professor Battaïa has co-supervised 11 PhD thestrong>ses to completion and delivered more than 15 invited lectures worldwide. She coordinates multi-partner research projects with industry and academic institutions, securing sustained funding for large-scale optimization and sustainability initiatives. Laboratories & Teams She leads research activities within KEDGE’s Operations, Supply Chain and Information Management group, collaborating closely with the Reconfigurable Manufacturing Systems and Sustainable Supply Chain Design research teams.

Olga BattaiaView profile

Professor

• Supply Chain Management
• Sustainable Manufacturing
• Operations Research
• +7 more

Prof. Olga Battaia is a Full Professor in the Department of Operations Management and Information Systems at Kedge Business School, serving as Associate Dean for Research. She holds a PhD from École des Mines de Saint-Étienne (2007), recognized with the Best PhD Thesis Award. Her expertise spans Supply Chain Management, Sustainable Manufacturing, Operations Research, and Combinatorial Optimization. She has co-authored over 200 publications and supervised 11 PhD students. Current research focuses on reconfigurable manufacturing systems, human-robot collaboration, and sustainability in supply chains. Editorial Roles: Associate Editor for Journal of Manufacturing Systems, IISE Transactions, Omega. Memberships: CIRP (International Academy for Production Engineering), IFAC Technical Committee 5.2. Research highlights include optimizing vaccine allocation (2025), human-robot ergonomics (2024), and closed-loop supply chain equity (2023). Awards include the 2007 Best Thesis Award. Advising: Co-supervised 11 PhD students. Active in European projects and international conference organization.

Robert RiggsView profile

Assistant Professor

• Systems Engineering
• Integer Programming
• Combinatorial Optimization
• +6 more

Robert Riggs is an Assistant Professor and Director of Undergraduate Programs in Systems Engineering at the University of Virginia's School of Engineering and Applied Science. He holds a Teaching Track position and serves as Systems ME and VEO Advisor. His research focuses on integer programming, combinatorial optimization, healthcare systems engineering, Six Sigma, lean enterprise applications, and disassembly optimization. He has advised on projects spanning healthcare clinic efficiency, AI-driven systems, and logistics optimization. Education details are not explicitly provided in the text, but his roles indicate advanced academic training in engineering disciplines. His research explores topics such as healthcare patient flow optimization, AI applications in recommenders, and disaster management systems. Recent work includes refining an AI restaurant recommender system (2025), redesigning emergency department layouts (2025), and analyzing post-COVID-19 healthcare workflows (2023). Riggs' articles reflect a multidisciplinary approach, addressing challenges in healthcare, logistics, and sustainability. His work on truck scheduling in cross-docking centers (2024) and maritime electrification (2023) highlights expertise in supply chain systems. He has also explored ethical AI applications and threats (2023) and nonprofit employment strategies for adults with autism (2024). No scientific awards are mentioned, but his active research portfolio spans over a decade with contributions to disassembly line balancing (2015) and parameter-coupling models in manufacturing (2013).

• Revenue Management and Pricing
• Reinforcement Learning
• Operations Research
• +5 more

Prof. Dong Li is a Professor of Operational Research at Lancaster University Management School (LUMS). He previously held academic roles at Loughborough Business School and the University of York, alongside industry experience at Avis Budget Group and Intel Corp. His research focuses on Revenue Management, Reinforcement Learning, and Resource Allocation, with methodological expertise in Markov Decision Processes and Stochastic Programming. Education: BEng/MEng in Mechanical Engineering (Xi’an Jiaotong University), MEng in Industrial Engineering (National University of Singapore), and PhD in Management Science (Lancaster University). Research Interests include: Revenue Management & Dynamic Pricing in Sharing Economies Discrete Choice Modelling Healthcare Operations Management Reinforcement Learning and Approximate Dynamic Programming He leads the STOR-i Doctoral Training Centre and serves as Associate Editor of Computational Management Science . Notable grants include a UKRI/EPSRC-funded project on medical resource rationing during public health emergencies (2020–2022). External Roles: External examiner at Strathclyde University (2020–present) and Xi’an Jiaotong Liverpool University (2020–2024). Research Groups: Centre for Transport & Logistics (CENTRAL), Health Systems Optimisation, and STOR-i.

Hui WangView profile

Associate Professor

• Stochastic Optimization
• Mathematical Finance
• Game-Theoretic Importance Sampling
• +4 more

Hui Wang is an Associate Professor of Applied Mathematics at Brown University, specializing in stochastic optimization, mathematical finance, and game-theoretic importance sampling. He holds a PhD from Columbia University (2000) and an MS from Tsinghua University (1996). His research focuses on variance reduction techniques in Monte Carlo simulations, particularly through a game-theoretic lens developed with Paul Dupuis. He has received the Manning Assistant Professorship (2004) and held grants from NSF and DOE. Teaching interests include probability theory, stochastic processes, and financial mathematics courses such as APMA 1720 and APMA 1655. His work intersects with queuing networks, simulation methodologies, and stochastic games. Recent efforts explore robust control in high-dimensional systems and extensions of importance sampling to complex network models. He actively referees for top journals like Annals of Applied Probability and SIAM Journal on Control and Optimization. Key contributions include explicit solutions for path-dependent options and convex duality methods in incomplete markets. Current research priorities involve advancing differential game frameworks for adaptive sampling algorithms and addressing scalability challenges in stochastic network optimization.

• Quality Management
• Production and Service Systems Management
• Manufacturing Systems Management
• +5 more

Prof. Emre Çevikcan is a Professor at the Department of Industrial Engineering at Istanbul Technical University. His roles include serving as Dean (2020–present), Vice Dean (2018–2020), and Head of Department (2014–2018). He holds a PhD in Industrial Engineering from Istanbul Technical University (2006–2010) and has extensive academic and administrative experience. Research Interests: Quality Management Production and Service Systems Management Manufacturing Systems Management Lean Production Systems Disassembly Line Design and Balancing Fuzzy Decision-Making Methodologies Key Projects: "Modelling, Analysis and Planning of Emergency Evacuation Processes in Different Conditions for Bulk Maritime Transportation" (TUBITAK-funded, 2015–2017) Research on Seru Production Systems, Autonomous Maintenance, and Kraljic Portfolio Matrix Applications Teaching: Designs advanced courses like Facade Production System Design & Management and Term Project Supervision at the postgraduate level. Collaborations: Editor for books like Business Analytics for Professionals and Industry 4.0: Managing the Digital Transformation .

Nico SCHMIDView profile

Assistant Professor

• Operations Management
• Logistics
• Manufacturing Systems
• +3 more

Nico SCHMID is an Assistant Professor in the Department of Operations Management at IÉSEG School of Management, France. His research focuses on operations management, logistics, manufacturing systems, and assembly systems optimization. He holds a Ph.D. in Management Sciences from Ghent University (2021), a Master in Industrial Engineering from University Duisburg-Essen (2015), and a Bachelor in Industrial Engineering from Rheinische Fachhochschule Köln (2013). His research interests include in-house logistics, production planning, and decision-making in assembly systems. He has contributed to advancing methodologies for assembly line balancing, transportation optimization, and facility sizing. His work bridges theoretical operations research with practical industrial applications, particularly in mixed-model manufacturing environments. Key contributions include studies on part feeding strategies, in-house transportation routing, and the integration of assembly line feeding with facility design. His 2022 Commended Paper Award from the International Federation of Automic Control highlights his impactful research on transportation optimization in assembly systems. Teaching: Operations Management and Managing Resources courses at IÉSEG's Grande Ecole program. Professional Experience: Research roles at Georgia Tech (2019), Ghent University (2016–2021), and teaching/research at Philipps University Marburg (2015–2016). Leveraging interdisciplinary methods, his research addresses complex challenges in production systems, aiming to enhance efficiency and adaptability in manufacturing processes.