Dr. Natalie Simpson is Professor and Associate Dean for Graduate Programs at the University at Buffalo's School of Management, Department of Operations Management and Strategy. She holds a PhD and MBA from the University of Florida, and a BFA from North Carolina School of the Arts. Her research explores emergency response systems , supply chain logistics , and educational technology , with particular focus on operational challenges in crisis management. She investigates hyper-project coordination in emergency contexts and resource allocation frameworks for incident commanders. Simpson's scholarly contributions show strong emphasis on: Modeling emergency response operations and supply chain vulnerabilities Developing pedagogical innovations for operations management education Analyzing healthcare workflow efficiency and disaster management systems Her extensive recognition includes: Decision Sciences Institute's Best Case Studies Award (2005) National Instructional Innovation Award (2004) SUNY Chancellor's Award for Excellence in Teaching (2002) Grinter Fellowship and Matherly Scholarship As Academic Director of Digital Access Education, she leads technology-enhanced learning initiatives and advises graduate programs. Administrative responsibilities include heading the Digital Access Working Group and serving on editorial boards for Decision Sciences.
Jim Luedtke is a Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. His research focuses on operations research, integer programming, and stochastic optimization methods for solving discrete and uncertain decision problems. Educational Background: BS in Industrial Engineering from University of Wisconsin-Madison MS in Operations Research from Georgia Institute of Technology PhD in Industrial and Systems Engineering from Georgia Institute of Technology Postdoctoral Research at IBM T.J. Watson Research Center His work spans applications in power systems optimization, healthcare analytics, and network design, with particular emphasis on developing cutting-edge algorithms for chance-constrained and multistage stochastic programming problems. Recent publications demonstrate strong focus on Benders decomposition techniques, Lagrangian dual methods, and distributionally robust optimization frameworks. Scientific Awards: NSF CAREER Award (2010) for "Risk Management via Stochastic Programming: Models, Computation, and Applications"
Prof. Dr. Sandra Transchel is a Full Professor of Supply Chain and Operations Management at Kühne Logistics University (KLU) in Hamburg, Germany. She has held this position since 2019, previously serving as Associate Professor (2011-2019) and Dean of Programs (2014-2015). Her academic journey includes appointments as Assistant Professor at Pennsylvania State University (2008-2011) and Visiting Assistant Professor at Tuck School of Business at Dartmouth (2011). Education includes: PhD in Business Administration, University of Mannheim (2008) Diploma in Business Mathematics, Otto-von-Guericke University Magdeburg (2004) Her research integrates supply chain management, inventory control, and revenue management with a strong focus on retail operations optimization and food supply chain sustainability . Key investigations examine perishable inventory systems, demand-supply synchronization, and substitution behavior. Current projects address food waste reduction through contract-based coordination in fresh food supply chains and development of urban food production networks (FabCity). Publications demonstrate consistent focus on inventory optimization under uncertainty, with recent work extending into pandemic impacts on humanitarian logistics and perishable inventory systems with lead-time variability. Research consistently bridges theoretical models with retail/manufacturing applications. Teaching includes Decision Analysis, Inventory and Warehouse Management, and Warehousing and Intralogistics across BSc, MBA, and MSc programs at KLU.
Maria Leonilde Rocha Varela is an Associate Professor with Habilitation at the School of Engineering, University of Minho, Portugal, where she also serves as a Senior Researcher at the Algoritmi Research Centre. She has been an integrated member of the Algoritmi Research Centre since 2012 and works in the Department of Production and Systems. Dr. Varela earned her degree in Production Engineering from the University of Minho in 1994, completed a Master's in Computer Integrated Production at DPS-UMinho in 1999, and received her Ph.D. in Production and Systems from the University of Minho in 2007. Her primary research focuses on Manufacturing Management, particularly Production Planning, Control and Optimization, and Collaborative Paradigms, Networks and Decision Making Models. She maintains extensive international collaborations with institutions worldwide including the National Institute of Industrial Engineering, VSB-Technick Univerzita Ostrava, University of Belgrade, and others. Her research spans Web Applications and Services for supporting Engineering and Production Management, with increasing emphasis on Artificial Intelligence, Robotic Process Automation, and Industry 4.0/5.0 applications. She has made significant contributions to scheduling algorithms, optimization techniques, and decision support systems for manufacturing environments. Analysis of her recent publications reveals a strong trend toward integrating Artificial Intelligence with traditional manufacturing processes, particularly in Robotic Process Automation applications. Her research increasingly focuses on sustainable manufacturing practices, with numerous publications addressing energy efficiency, environmental sustainability, and resource optimization. There is a clear emphasis on multi-objective optimization approaches to solve complex manufacturing problems, particularly in distributed job shop scheduling. Her work demonstrates an evolution from traditional production planning methods to more advanced AI-driven approaches for Industry 4.0 and 5.0 environments. Dr. Varela has held significant academic leadership roles, currently serving as the director of the master's course in Engineering and Quality Management at DPS-UMinho. She previously coordinated the industrial management and systems subgroup from 2012 to 2021 and was part of the steering committee for the master's course in systems engineering between 2016 and 2019. She has successfully supervised more than 70 MSc projects, with over 15 currently ongoing, focusing on Production and Systems Engineering. Her supervision encompasses collaborative management models, traditional decision approaches, and web-based platforms incorporating AI techniques. She coordinates research projects including 2 concluded Ph.D. projects and 6 ongoing ones. She collaborates as a research member in several R&D projects with national and international industrial enterprises and institutions, and in international Erasmus projects. Dr. Varela is an active participant in the academic community, serving on editorial boards of several international journals and as a member of organizing and scientific committees for numerous international conferences. She is a member of several prestigious research networks including the Euro Working Group of Decision Support Systems (EWG-DSS), Institute of Electrical and Electronics Engineers (IEEE), Industrial Engineering Network, and the Institute of Industrial and Systems Engineers (IISE).
James B. Orlin is the E. Pennell Brooks (1917) Professor in Management and a Professor of Operations Research at the MIT Sloan School of Management. He specializes in network and combinatorial optimization with applications spanning transportation, computer science, operations, and marketing. BA in Mathematics, University of Pennsylvania MA in Mathematics, California Institute of Technology MMath, University of Waterloo PhD in Operations Research, Stanford University His research focuses on designing efficient algorithms for network optimization problems, including shortest path, max flow, and min cost flow. He has contributed to algorithmic theory in logistics, telecommunications, and inventory management, with work on stochastic demand models and data-driven inventory policies. Recent publications include advancements in directed shortest path algorithms, robust submodular function maximization, and energy storage problem complexity. His seminal textbook Network Flows: Theory, Algorithms, and Applications (1993) remains a foundational reference. Leonard G. Abraham Prize Khachiyan Prize Test of Time Award As a mentor, he has advised numerous researchers through collaborative publications and teaching. His work addresses both theoretical algorithm development and practical implementation across diverse domains including airline scheduling, logistics, and network design.
Prof. Dr. Guido Voigt serves as a Professor at the Institute for Logistics and Supply Chain Management within the University of Hamburg Business School. His office is located at Moorweidenstraße 18, Room 2013, Hamburg, with contact details including phone +49 40 42838-1549 and email guido.voigt@uni-hamburg.de. Office hours are by appointment. His research centers on Supply Chain Management and Behavioral Operations, focusing on contract design under asymmetric information, inventory management, remanufacturing, and sustainability. Key themes include the impact of communication media on supply chain information sharing, carbon footprint reduction strategies, and behavioral modeling of consumer choices in service operations. His work bridges theoretical optimization with empirical assessments of decision-making. Recent publications (2024-2015) reveal a trajectory toward behavioral supply chain dynamics, examining online appointment systems, ratchet effects in contracting, and ambiguity aversion in remanufacturing. The body of work consistently addresses information asymmetry and risk management through experimental and modeling approaches. No scientific awards are documented in the source material. No information regarding student advising or research grants is provided in the available text. Prof. Voigt leads the Institute for Logistics and Supply Chain Management at the University of Hamburg Business School, collaborating with researchers including Alexander Daniels, Hannes Cordes, Victoria Riemer, and Ira Widderich. The institute maintains active research streams in logistics optimization and behavioral supply chain phenomena.
Prof. Jörn Meissner, PhD, is a Full Professor of Supply Chain Management & Pricing Strategy at Kühne Logistics University (KLU) since 2011. He holds a PhD and Master’s in Management Science from Columbia Business School and a Diploma in Business from University of Hamburg . As an academic and entrepreneur, he founded Manhattan Review and Lancaster Executive . Education: PhD in Management Science, Columbia University (2005) Master of Philosophy, Columbia University (2005) Diplom-Kaufmann, University of Hamburg (1997) Research Expertise: Focus on stochastic and dynamic decision-making using mathematical optimization and machine learning Key projects: Global supply chain optimization , Inventory control , Revenue management , and Operations & service management Industry collaborations with British Telecom , British Airways , Apple Europe , and SAP Germany Publication Trends: Recent work addresses intermittent demand forecasting for spare parts, lateral transshipment optimization , and risk-sensitive capacity control Historical contributions include progressive interval heuristics for multi-item lot sizing and dynamic pricing with customer choice models Teaching Experience: Previously held academic positions at Lancaster University Management School , University of Hamburg , and University of Mannheim Developed MBA electives in Advanced Decision Models , Supply Chain Management, and Revenue Management
Selçuk Karabatı is a Professor of Operations Management at the College of Administrative Sciences and Economics, Koç University (Turkey). His research spans retail operations, sustainable supply chains, and production systems optimization. He holds a PhD from the University of Texas at Austin and has previously taught graduate courses in Service Operations Management , Operations Strategy , and Sustainable Operations Management at Koç University. Education : PhD (University of Texas at Austin), MS (University of Southern California), BS (Boğaziçi University) Editorial Roles : Senior/Associate Editor at Production and Operations Management and IIE Transactions His research focuses on Supply Chain Management , Retail Operations , and Sustainable Operations , with applications in inventory control, pricing strategies, and production planning. Recent and historical publications reveal expertise in optimization frameworks , dynamic pricing , portfolio rebalancing , and retail analytics . While no explicit scientific awards are listed in the provided text, his work has consistently addressed challenges in inventory substitution, auction mechanisms, and logistics coordination.
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.
Professor Gábor Rappai is a faculty member at the Department of Economics and Econometrics, University of Pécs. He serves as Head of the Doctoral School of Business Administration since 2019 and has held significant administrative roles including Vice Dean (1998-2005), Dean (2005-2011), and Senate member (14 years). PhD in Economics (Hungarian Academy of Sciences, 2003) Habilitation in Economics (2003) Candidate of Economics (1997) Graduated in Commodity Trading (Janus Pannonius University, 1987) His research focuses on econometric methodologies applied to financial time series analysis, causal inference in economic systems, and stochastic modeling in sports economics. He has developed frameworks for strategic policy evaluation and integrated quality control with production-marketing interfaces in JIT environments. Publications demonstrate expertise in sports economics (UEFA Champions League dynamics), policy evaluation (Europe 2020 strategic goals), and operations management (JIT production systems). Key methodologies include econometric testing, stochastic modeling, and applied mathematical optimization. Active in professional communities, he contributes to the Hungarian Academy of Sciences' Scientific Committee of Statistics and Prognostics, Hungarian Statistical Society, and Economic Modelling Society.
Irena Okhrin is a Junior Professor at the European University Viadrina Frankfurt (Oder) in the Department of Economics and Business Administration. Her primary focus is on Information & Operations Management, with particular emphasis on logistics and mobile business applications. Dr. Okhrin's research interests center around several key areas: Modeling of Logistic Processes in M-Business Transport Problems with Real-Time Information Exchange Use of Mobile Technologies in Supply Chain Management Her scholarly work demonstrates a consistent focus on the intersection of logistics, mobile technologies, and supply chain management. Over the period 2005-2009, she has published numerous papers examining vehicle routing problems with real-time constraints, inventory management in mobile business environments, and various aspects of supply chain management enhanced by mobile technologies. Her research often employs optimization techniques and explores practical implementations of mobile business concepts in logistics companies. Dr. Okhrin has received recognition for her contributions to the field through publications in reputable journals and conference proceedings, though specific awards are not mentioned in the available information. She has collaborated extensively with K. Richter on many research projects, indicating a productive academic partnership. While specific information about her teaching responsibilities and graduate students is not provided in the available materials, her position as Junior Professor suggests involvement in both undergraduate and graduate education.
Reha Uzsoy is the Clifton A. Anderson Distinguished Professor in the Edward P. Fitts Department of Industrial & Systems Engineering at North Carolina State University. He holds a PhD from the University of Florida (1990) and dual BS/MSc degrees from Bogazici University (Turkey). His research focuses on production planning, scheduling, and supply chain management, with significant contributions to semiconductor manufacturing optimization. He has held visiting roles at Intel, IC Delco, and Hong Kong University of Science and Technology. Awards include Fellow of the Institute of Industrial Engineers (2005), C.A. Anderson Outstanding Faculty Award (2011), and Purdue University's University Faculty Fellow (2001). He transitioned to NC State in 2007 from Purdue, where he directed the Laboratory for Extended Enterprises, an interdisciplinary supply chain research center. Education: PhD in Industrial Engineering, University of Florida, 1990 BS and MS in Industrial Engineering, Bogazici University, 1984-1986 Additional BS in Mathematics, Bogazici University, 1985 Research interests emphasize production systems' dynamic behavior, including new product introductions, congestion effects, and transition management. His work bridges theoretical models (e.g., clearing functions) with industrial applications in semiconductor fabrication and supply chain coordination. Recent projects include optimizing order acceptance/scheduling in additive manufacturing and developing equity-focused food distribution models. Awards: Fellow of the Institute of Industrial Engineers (2005) Outstanding Young Industrial Engineer in Education (1997) C.A. Anderson Outstanding Faculty Award (2011) Purdue University Faculty Fellow (2001) Contributions extend beyond academia: he co-developed NC State's Master of Supply Chain Engineering and Management (MSCEM) program and pioneered methodologies for production planning under stochastic demand. His research has been funded by NSF, Intel, Hitachi, and others. Labs/Teams: Former director of Purdue's Laboratory for Extended Enterprises; collaborates with NC State's industrial partners on semiconductor and healthcare supply chain initiatives.
Professor Kenneth Brown is affiliated with the Department of Computer Science at University College Cork (UCC) , Ireland. He holds the academic rank of Professor and is a Principal Investigator at the Insight Centre for Data Analytics and the CTVR (Telecommunications Research Centre) . BSc (Hons) Mathematics, University of Glasgow, 1986 MSc Mathematical Logic and the Foundations of Computation, University of Manchester, 1987 PhD Artificial Intelligence in Engineering, University of Bristol, 1991 His research focuses on Artificial Intelligence, constraint programming, optimisation, and distributed reasoning , with applications in wireless networking, sensor networks, and dynamic resource management . He also works on smart energy systems, data analytics, and human-centric applications. His recent work includes projects under the SFI-funded Insight Centre and Horizon Europe initiatives like GLACIATION and SEISMEC. His publications span topics from wireless sensor network optimization and cognitive radio to constraint-based decision support and AI in emergency management. He has led and contributed to over 15 recent publications in top-tier journals and conferences, showing a strong trend in AI-driven solutions for networked and intelligent systems. IEEE SECON 2015 Best Demonstration 2014 TAOS Best Paper Award in Access Networks and Systems Best paper, SMARTGREENS 2013 Enterprise Ireland Lifescience and Food Commercialisation Award Best Application Paper, AI2008 Best Application Paper, AI2006 Best paper nomination, ECAI 2004 Best Paper, Intl Conf AI in Design Professor Brown has supervised numerous PhD and MSc students in areas including constraint programming, sensor networks, evacuation modeling, and smart buildings. He has secured significant research funding from SFI, Enterprise Ireland, and IRCSET. He is actively involved in research leadership, serving as Deputy Director of Insight@UCC and PI in multiple national and international projects. He is a member of research groups involved in GLACIATION (green, responsible data operations), SEISMEC (human-centric industry), and SMARTeBuses . His lab supports a team of doctoral students and research staff working on AI, networking, and data analytics for real-world applications.
Timothy S. Vaughan, Ph.D., is a Professor in the Marketing and Supply Chain Management Department at the University of Wisconsin-Eau Claire's College of Business. His academic career spans decades, focusing on operations management, inventory systems, and statistical pedagogy. He holds a Ph.D. from the University of Iowa and a B.A. from the University of Northern Iowa. Ph.D., University of Iowa B.A., University of Northern Iowa Research interests include operations management, analytics, simulation, and statistical quality control. Recent work explores quality control applications in daily habits, workload variability in capacity planning, and dynamic inventory policies for spare parts. His publications span journals like Decision Sciences Journal of Innovative Education and International Journal of Production Research . Scientific awards include the 2021 College of Business Creativity and Innovation Award. He has presented extensively at conferences such as the Winter Simulation Conference and Decision Sciences Institute National Meetings, covering topics from beer game implementations to cyclical scheduling systems.
Jens Heger is a Professor of Engineering specializing in Modeling and Simulation of Technical Systems and Processes at Leuphana University Lüneburg, Germany. He is affiliated with the Institute for Production Technology and Systems (IPTS) and the Research Center for Digital Transformation. His academic career spans over a decade of research and teaching in production engineering, manufacturing systems, and simulation technologies. Dr. Heger completed his Master of Science in Computer Science with a minor in Business Studies at the University of Paderborn (1999-2006). He then earned his doctorate degree at the University of Bremen in the Department of Production Engineering. His dissertation focused on "Dynamic selection of rules for sequence planning in workshop and flexible flow production" under the supervision of Prof. Scholz-Reiter and Prof. Jürgen Branke from the University of Warwick, UK. Professor Heger's research interests center around the intersection of manufacturing engineering, simulation, and artificial intelligence. His work demonstrates a strong focus on applying advanced computational methods to solve complex production challenges. Key research areas include: Manufacturing process optimization through simulation and modeling Application of machine learning and reinforcement learning in production scheduling Development of intelligent control systems for manufacturing processes Energy efficiency and sustainability in production systems Quality control and prediction in sheet metal forming processes Integration of AI technologies in traditional manufacturing environments Analysis of Professor Heger's recent publications reveals a clear trajectory toward increasingly sophisticated applications of artificial intelligence in manufacturing. His work has evolved from traditional simulation and optimization techniques toward integrating deep learning, reinforcement learning, and computer vision technologies into production systems. A significant portion of his research focuses on dynamic scheduling and optimization problems, particularly using reinforcement learning approaches to address complex manufacturing challenges. His publications also demonstrate a growing interest in sustainable manufacturing practices, energy efficiency, and quality control applications through AI technologies. Professor Heger has contributed significantly to the field through numerous publications in manufacturing engineering, production systems, and AI applications. His work spans both theoretical advancements in scheduling algorithms and practical implementations in industrial settings, particularly focusing on small and medium enterprises.
