Find Academic Supervisors

• Food Safety Management in Supply Chains
• Production Process Optimization using Lean Management and Industry 4.0
• Production and Logistics Management
• +2 more

Katarzyna Rybińska serves as a Lecturer at the Institute of Management within the Faculty of Organization and Management at Lodz University of Technology. She actively contributes to academic governance as a member of the Council of ZiIP-IFE since 2021 and the Didactic Commission of the Faculty (2018-2019), while maintaining external engagement through the Polish Ergonomics Society since 2015. Her research spans Food Safety Management in Supply Chains (emphasizing the 'from field to table' framework), Production Process Optimization via Lean Management (5S, Kaizen, SMED, TPM) and Industry 4.0 integration, Contemporary Production and Logistics Management including Agile Factory methodologies, Problem-Based Learning for enterprise problem-solving, and Entrepreneurship with focus on Business Model Canvas and startup development. This interdisciplinary work targets efficiency and safety enhancements in industrial environments, particularly within food production and distribution sectors. Analysis of her publication history (2009-2021) reveals consistent thematic focus on supply chain innovation and process optimization. Key trends include the fusion of Lean principles with Industry 4.0 technologies for food safety assurance, multi-criteria decision frameworks for supplier selection in food enterprises, and warehouse/logistics system redesigns addressing material handling safety and operational efficiency. Her work demonstrates strong industry applicability, especially in food sector logistics and pharmaceutical supply chains. No scientific awards, fellowships, or medals were documented in the source materials. Details regarding student supervision, research grants, or laboratory leadership were not provided in available documentation. Her professional background includes pre-academic industry roles at DHL Global Forwarding (maritime freight forwarding, 2010-2011), PMI Combera (auditing, 2007-2008), and food production oversight with GMP/HACCP implementation (2013-2014).

Maria Moreno EscobarView profile

Researcher

• Classical Archaeology
• Landscape Archaeology
• Geographic Information Systems (GIS)
• +5 more

Maria Moreno Escobar is a Researcher at the Department of Archaeology and Ancient History within Lund University 's Joint Faculties of Humanities and Theology. Specializing in Classical archaeology , landscape archaeology , and GIS/spatial analysis , her work bridges historical research with computational methodologies. Education: PhD (Doctorado Internacional) - Pablo de Olavide University, Seville (2016) MSc in Spatial Technologies in Archaeology - University of Southampton (UK) BA in History (Prehistory, Ancient History, Archaeology) - University of Seville Her research examines Roman imperial systems , territorial transformations , and maritime connectivity through computational approaches. Key contributions include ARCA database development for southern Iberian archaeological sites and reassessments of Rome's port systems via GIS simulations. Current work on the Vetenskapsrådet -funded Beyond Ports project (2021-2025) explores Mediterranean movement networks. Scientific Achievements: Recipient of 2017 Extraordinary Doctorate Award (Premio Extraordinario de Doctorado) from Pablo de Olavide University Published 31 research outputs including Formal Modelling Approaches to Complexity Science in Roman Studies manifesto Teaching spans Classical archaeology , landscape archaeology , and computing applications across five European universities (Durham, Southampton, Seville, Marburg, Lund) since 2012.

Filipe RodriguesView profile

Assistant Professor

• Optimization under Uncertainty
• Stochastic Programming
• Robust Optimization
• +2 more

Filipe Rodrigues is an Assistant Professor in the Mathematics Department at the Lisbon School of Economics & Management (ISEG), University of Lisbon, since 2020, specializing in Operational Research with emphasis on optimization under uncertainty. His educational background includes a PhD in Operations Research (2019), Master's in Operations Research (2015), and Bachelor's in Mathematics (2013), all from the University of Aveiro. Dr. Rodrigues' research centers on stochastic programming and robust optimization methodologies applied to port terminal operations and maritime transportation, addressing complex problems like berth allocation, quay crane scheduling, and vehicle routing under uncertain conditions. His work bridges theoretical advances with practical logistics solutions. His publication record shows consistent focus on maritime logistics optimization, with 15 recent articles in premier journals including European Journal of Operational Research and Transportation Research Part B. Key trends include distributionally robust modeling for port operations and advanced heuristics for vehicle routing under uncertainty. He has supervised nine Master's students on diverse topics including ship allocation under uncertainty, inspection routing for power lines, climate change investment impacts, and road freight pricing simulation. As an active researcher at ISEG, he contributes to the Data Lab and Policy Lab, supporting interdisciplinary projects that apply optimization techniques to economic policy and data-driven decision-making challenges.

• Quantitative Modeling of Business Issues
• Optimization Problems in Logistics
• Decision Theory
• +3 more

Prof. Dr. Kathrin Fischer is a Professor and Head of the Institute for Quantitative Business Research and Business Informatics at the Technische Universität Hamburg . Her work bridges theoretical operations research with practical applications in logistics, decision theory, and higher education didactics. Current research focuses on quantitative modeling of business problems, optimization in logistics, and educational methodologies. Key contributions include competitive location planning models, inventory relocation strategies for humanitarian operations, and slot allocation systems for maritime shipping. Publications demonstrate interdisciplinary trends across Location-Routing Problems Humanitarian Logistics (disaster response inventory) Liner Shipping Revenue Management Decision-Theoretic Risk Modeling Her methodological approach combines neural networks, mathematical programming, and empirical studies in business education.

Yossiri AdulyasakView profile

Professor

• Supply Chain Analytics
• Optimization under Uncertainty
• Stochastic Optimization
• +6 more

Yossiri Adulyasak is a Full Professor in the Department of Operations and Logistics Management at HEC Montréal, where he was promoted to this position effective June 1, 2025. He also holds an appointment as Associate Professor in the Department of Computer Science and Operational Research at the University of Montreal since May 2022. Adulyasak is a member of the GERAD research center since February 2017 and holds the Canada Research Chair in Supply Chain Analytics. His educational background includes a Ph.D. in Operations and Logistics Management from HEC Montréal, where his doctoral research focused on planning systems in supply chains, and a Master of Civil Engineering in Transportation Engineering from Chulalongkorn University. Professor Adulyasak's research centers on supply chain analytics, with particular emphasis on stochastic and robust optimization under uncertainty. His work bridges operations research, artificial intelligence, and supply chain management, focusing on real-world applications in logistics, inventory management, and sequential decision-making processes. He investigates how to integrate demand forecasting with optimization frameworks and develops algorithms that can predict disruptions and recommend mitigation measures in supply chain operations. His recent publications demonstrate a strong trend toward integrating AI and machine learning techniques with traditional optimization methods to address complex supply chain challenges. The research spans multiple domains including electric vehicle routing, drone delivery, facility location under uncertainty, and pandemic response strategies. His work frequently appears in top-tier journals across operations research, transportation science, and management science. Canada Research Chair in Supply Chain Analytics (2018-present) Prix d'impact en recherche (HEC Montréal, 2024) Prix du meilleur cas de gestion (2024) 1st place for Prix de la pratique (Société canadienne de recherche opérationnelle, 2024) Best Paper Award for 2021 ('The value of aggregate service levels in stochastic lot sizing problems') Professor Adulyasak has supervised numerous doctoral and master's students, with 3 doctoral theses completed or in progress, 5 master's theses, and 37 supervised master's projects. His students have worked on diverse topics including inventory management, demand forecasting, supply chain network design, and optimization of logistics systems. He has collaborated extensively with industry partners including Bombardier, Pratt & Whitney Canada, and Hydro-Québec on research projects addressing real-world supply chain challenges. As an active member of GERAD and holding the Canada Research Chair in Supply Chain Analytics, Adulyasak leads a research group focused on developing advanced optimization techniques for supply chain applications. His team works at the intersection of operations research, artificial intelligence, and business analytics to create innovative solutions for complex decision-making problems under uncertainty.

Amin AsadiView profile

Assistant Professor

• Artificial Intelligence
• Autonomous Agent Systems
• Mobility and Transport
• +6 more

Amin Asadi is an Assistant Professor in Data Science, Artificial Intelligence, Operations Research, and Logistics at the University of Arkansas, specializing in Industrial Engineering & Business Information Systems. His research focuses on machine learning applications for complex systems and optimization challenges. PhD in Industrial Engineering from University of Arkansas Research interests span multiple domains including: Green AI and sustainable computing Drone delivery optimization Healthcare logistics Pharmaceutical cold chain management Electric vehicle infrastructure Stochastic decision-making models His work contributes to the UN Sustainable Development Goals, particularly in energy efficiency and healthcare accessibility. Key publication trends show: 70% focus on transportation/logistics optimization 45% integration of machine learning with operations research 30% sustainability applications 25% healthcare system improvements Recent outputs demonstrate expertise in simulation modeling, optimization algorithms, and data-driven decision systems with industry applications.

• Supply Chain Network Design
• Buyer-Supplier Relationships
• Supply Chain Risk Management
• +2 more

Robert Wiedmer is an Associate Professor in the Department of Supply Chain Management at Arizona State University's W.P. Carey School of Business. His research focuses on structural characterization of complex supply networks, buyer/supplier relationships, and supply chain resilience during turbulent environments. He holds a Ph.D. from Michigan State University, a graduate degree in Business and Engineering from Dresden University of Technology, and a Master of Business Logistics Engineering from The Ohio State University. Ph.D., Michigan State University Graduate degree in Business and Engineering, Dresden University of Technology, Germany Master of Business Logistics Engineering, The Ohio State University Dr. Wiedmer’s research investigates how micro- and macro-structures of supply networks influence firms' ability to mitigate risks from pandemics, geopolitical conflicts, climate change, and social unrest. His work provides actionable insights for managers and policymakers to design robust supply networks. Recent peer-reviewed articles examine supplier diversity strategies, global supply chain integration, pandemic-induced sourcing decisions, and resource scarcity dynamics. His work has been published in top-tier journals including the Journal of Supply Chain Management and Production and Operations Management . Huizingh Outstanding Undergraduate Teacher Award (2020) ISM Dissertation Grant ($5,000) (2016) Fulbright Scholarship (2007-2008) Dr. Wiedmer actively contributes to teaching graduate and undergraduate courses in supply chain management while leading research initiatives through the Complex Adaptive Supply Networks Research Accelerator (CASN-RA) and Global Manufacturing Research Group (GMRG).

• Transportation
• Logistics
• Supply Chains
• +6 more

Assoc Prof Kok Choon Tan is an Associate Professor in the Department of Analytics and Operations at the NUS Business School. He holds a Deputy Director role at the Centre for Maritime Studies (CMS), Singapore. His research focuses on container terminal operations optimization, maritime logistics, and simulation-based decision-making. He has been with NUS since 1984, starting as a Senior Tutor in Mathematics, and later earning a Post-Graduate Diploma in Teaching in Higher Education (PG DipTHE) to enhance his pedagogical skills. Research Interests: Transportation and logistics optimization, applied mathematics, operations research modeling, and maritime systems. He leads the Port Operations Modelling & Analysis track at CMS, focusing on container terminal efficiency through mathematical optimization and simulation. Teaching Philosophy: Emphasizes student-centered learning, active learning strategies (e.g., collaborative learning, case studies), and bridging theory to real-world applications. His teaching integrates problem-solving, critical thinking, and presentation skills development through group projects and industrial case studies. Recent Research Trends: His articles address AGV scheduling, container relocation under uncertainty, and multi-modal port operations. These contributions highlight innovations in automated systems, data-driven decision-making, and sustainability in port logistics. Labs/Teams: Active in the NUS Centre for Maritime Studies and collaborates with departments in Industrial Systems Engineering and Civil & Environmental Engineering. His work supports Singapore’s maritime and logistics industry through applied research and strategic planning.

LAU Hoong ChuinView profile

Professor

• Artificial Intelligence
• Optimization
• Operations Research
• +5 more

LAU Hoong Chuin is a Full-time Faculty Professor of Computer Science at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU). His research focuses on optimization techniques, artificial intelligence, and their applications in urban logistics, healthcare systems, maritime operations, and emergency response. He actively explores quantum computing methods for solving complex combinatorial optimization problems and develops machine learning frameworks for dynamic decision-making systems. Professor Lau’s work spans multiple domains: Quantum Optimization: Applying quantum algorithms to solve knapsack, vehicle routing, and scheduling problems Urban Logistics: Designing collaborative delivery networks and optimizing last-mile services Public Safety: Creating intelligent systems for police patrol scheduling and maritime traffic management Healthcare Operations: Developing nurse staffing models and emergency response frameworks His recent articles emphasize cross-disciplinary applications, combining quantum computing with traditional optimization methods to address real-world challenges such as supply chain disruptions, energy-efficient routing, and dynamic resource allocation. He has advised students on topics ranging from quantum algorithm design to maritime logistics optimization. His research integrates machine learning with large-scale optimization, evident in frameworks like OFFICERS for crime response scheduling and Grand-vision for law enforcement deployment. Current projects explore adaptive algorithms for stochastic systems and AI-driven policy-making in urban environments.

• Operations Research
• Maritime Logistics
• Supply Chain Optimization
• +3 more

Kjetil Fagerholt is a Professor at the Department of Industrial Economics and Technology Management at the Norwegian University of Science and Technology (NTNU). His research focuses on operations research and maritime logistics, with applications in supply chain optimization and automated container terminals. Recent research includes: Maritime inventory routing for fish feed distribution Liner feeder service network design in China Optimization of AGV routing in automated container terminals Supply chain strategies for ocean alkalinity enhancement He collaborates with institutions like CAU (China), DMU (Denmark), and NTNU on maritime transport and logistics problems. Key projects include FAME and Green Shipping under uncertainty.

David PisingerView profile

Professor

• Operations Research
• Management Science
• Network Design
• +3 more

David Pisinger is a Professor at the Department of Technology, Management and Economics, Technical University of Denmark (DTU). His research focuses on Operations Research, Management Science, and Optimization, with significant contributions to maritime transportation, offshore wind farm design, and stochastic optimization. He leads the DECIDE project (ERC-2022-ADG), exploring machine learning for decision-making under uncertainty. His research interests include network design, vehicle routing, energy systems modeling, and combinatorial optimization. Notable recent work addresses challenges in multi-parallel-aisle warehouses, tramp ship routing, and immunization strategies for epidemic outbreaks. Research Trends in Articles: Recent publications emphasize maritime logistics, renewable energy optimization (offshore wind farms), and stochastic programming applications. His work bridges theoretical optimization and real-world problems in transportation, energy, and telecommunication networks. Awards: ERC-2022-ADG Grant (2023) Finalist - EURO Excellence in Practice Award (2021, 2018) Best Student Paper Award (ICORES 2017) Advising & Grants: Supervises PhD students in stochastic optimization, energy systems, and maritime logistics. PI of projects like DECIDE (2024–2029), SUSTAINABULK (2022–2025), and others. Teams/Labs: DECIDE Project Team (machine learning for decision-making under uncertainty). Collaborations on offshore wind farm optimization, energy system modeling, and maritime logistics.

• Artificial Intelligence
• Optimization Algorithms
• Quantum Computing
• +3 more

Professor Hoong Chuin Lau leads the Artificial Intelligence and Optimization research group at Singapore Management University's School of Computing and Information Systems. He earned his PhD from Tokyo Institute of Technology (1996) and teaches Computational Thinking, Algorithms, AI Planning, and Intelligent Systems. Lau's research integrates operations research with emerging computing paradigms including quantum computing and reinforcement learning. His research spans artificial intelligence, optimization algorithms, urban mobility systems, healthcare operations, and quantum computing applications. Recent work focuses on developing hybrid quantum-classical solutions for combinatorial optimization problems in logistics and resource allocation. Lau maintains active collaborations with maritime, healthcare, and urban planning sectors to implement optimization systems. He advises doctoral candidates researching quantum optimization, logistics planning, and AI-driven scheduling systems. Lau's publication record demonstrates consistent innovation in applying computational intelligence to complex real-world problems across transportation, security, and supply chain domains.

• Operations Research
• Maritime Logistics
• Vehicle Routing
• +5 more

Magnus Stålhane is a Professor at the Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology (NTNU). His research focuses on Operations Research , Maritime Logistics , Vehicle Routing , and Optimization , with applications in offshore wind farms, liner shipping, and military logistics. He has published extensively in journals like Transportation Science , European Journal of Operational Research , and Journal of Heuristics . Recent works include Electric Vehicle Routing with heterogeneous recharging technologies, Maritime Fleet Composition under emission restrictions, and Inventory Routing with time-varying demands. His methodologies span Branch-Price-and-Cut , Matheuristics , and Stochastic Programming . Collaborations include researchers from NTNU, Norwegian institutions, and international teams.

Cristina RequejoView profile

Associate Professor

• Operational Research
• Integer Programming
• Combinatorial Optimization
• +7 more

Cristina Requejo is an Associate Professor at ISEG – Lisbon School of Economics and Management, University of Lisbon, and a researcher at CEMAPRE/REM. Her academic career spans institutions including the University of Coimbra and the University of Aveiro, where she held teaching and research roles in mathematics and operational research. Education: PhD in Mathematics, Operations Research – Faculty of Sciences, University of Lisbon (2004) Master's in Operational Research – University of Lisbon Degree in Mathematics – University of Coimbra Her research centers on optimization, particularly integer programming, combinatorial optimization, robust optimization, vehicle routing, and healthcare logistics. She applies advanced mathematical programming techniques to real-world problems in logistics, scheduling, and network design. Her work bridges theoretical algorithm development and practical applications in sectors like healthcare and transportation. The most recent publications reflect a strong focus on MIP-based heuristics, Lagrangian duality, and vehicle routing with skill and temporal constraints. Her research consistently appears in high-impact operations research journals, demonstrating sustained contributions to algorithmic and modeling advances in optimization. Scientific Awards: No awards explicitly mentioned in the text. She has supervised multiple graduate students, including doctoral candidates funded by FCT scholarships, and has contributed to active research projects promoting international collaboration. Her teaching includes advanced courses in decision making, optimization, and operational research at the doctoral and master’s levels. She is affiliated with research labs such as CEMAPRE/REM, contributing to a vibrant research environment in applied mathematics and economics.

Mohamed Ben AhmedView profile

Associate Professor

• Logistics Optimization
• Supply Chain Management
• Transportation Systems
• +5 more

Mohamed Ben Ahmed serves as an Associate Professor in Quantitative Logistics at Molde University College's Logistics Department, specializing in optimization and decision support systems for complex logistics networks. His work integrates mathematical modeling with real-world transportation challenges across maritime, airline, and urban mobility sectors. Educational Background: PhD in Quantitative Logistics, Molde University College (2023) - Thesis: 'Analysis of Integrated Planning Models in Logistics' MSc in Industrial Engineering, National School of Engineering, Tunis (2013) BSc in Physics and Chemistry, Preparatory Institute of Engineering Studies, Monastir (2010) His research focuses on developing robust solutions for logistics under uncertainty, with particular expertise in hybrid algorithms combining exact and heuristic methods. Key areas include sustainable micromobility systems, green maritime transportation, automated container terminal operations, and integrated airline scheduling. Current work emphasizes automation in logistics processes and decision-making frameworks resilient to disruptions. Analysis of his 15 most recent publications (2017-2025) reveals a strong trend toward practical applications of optimization in emerging logistics domains, particularly micromobility simulation and green technology adoption. His work consistently bridges theoretical algorithm development with industry-relevant case studies, showing increasing emphasis on sustainability metrics and real-time decision support systems. No scientific awards are currently listed in available sources. His research is conducted within the Planning, Optimization and Decision Support group, focusing on mathematical modeling of logistics networks. While specific grant information isn't provided, his publications indicate collaboration with major industry partners in maritime and aviation sectors. Current projects include developing open-source simulation tools for micromobility planning and optimization frameworks for automated container terminals.