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Frank MeiselView profile

Professor

• Supply Chain Management
• Logistics
• Operations Research
• +4 more

Prof. Dr. Frank Meisel holds the Chair for Supply Chain Management at the Christian-Albrechts-University of Kiel, within the Faculty of Law, Economics and Business. His research focuses on mathematical modeling and quantitative solution methods for the design and operation of production, distribution, and service networks. 1998-2003: Studied Traffic Engineering at the Technical University of Dresden 2008: Received Dr. rer. pol. with thesis "Seaside Operations Planning in Container Terminals" 2014: Completed Habilitation in Business Economics with thesis "Papers on the Design and Operations of Production-, Distribution- and Service-Networks" Since 2013: Professor of Supply Chain Management at Kiel University Prof. Meisel's research spans multiple areas of logistics and operations research. His primary interests include maritime logistics, particularly container terminal operations; vehicle routing problems with synchronization requirements; and integrated planning of production-distribution networks. He develops mathematical models and optimization algorithms to address complex logistical challenges in various industry contexts, from seaport operations to healthcare logistics and urban waste management. His work bridges theoretical operations research with practical logistics applications across diverse sectors. His publication record demonstrates a progression from specialized maritime logistics problems to broader supply chain applications. Recent work shows increasing focus on sustainability considerations and the integration of multiple operational decisions across different parts of supply networks. His research has significant practical implications for container terminal operations, intermodal transportation, and service logistics. Prof. Meisel actively contributes to the academic community through conference presentations at major events including EURO, IFORS, and specialized workshops on maritime logistics. His work appears in top-tier journals such as Transportation Science, European Journal of Operational Research, and Computers & Operations Research. He teaches courses including Supply Chain Management, Production and Logistics, and Operations Management at both undergraduate and graduate levels. His educational contributions include developing curriculum for English-language business programs and supervising student research projects in logistics optimization.

Andreas S. SchulzView profile

Professor

• Mathematical Optimization
• Algorithm Design
• Operations Research
• +5 more

Prof. Dr. Andreas S. Schulz is a faculty member at Technische Universität München (TUM), holding a chair in the Department of Mathematics and the Department of Business and Economics. He previously served as the Patrick J. McGovern Chair of Management and Professor of Mathematics at MIT. His research focuses on mathematical optimization, algorithm design, and their applications in logistics, production, healthcare systems, and online advertising. He has held visiting professorships at institutions such as the Sauder School of Business (UBC) and ETH Zurich. Prof. Schulz’s research bridges operations research, theoretical computer science, and economics. He develops analytical methods to solve complex decision-making problems in business, including scheduling, resource allocation, and network optimization. A key interest is applying mathematical approaches to enhance healthcare delivery and system efficiency. Education: PhD in Operations Research (MIT), prior academic roles at MIT and visiting institutions. Key Achievements: Alexander von Humboldt Professorship (2014), Humboldt Research Award (2010), Glover-Klingman Prize (2006). Research Themes: Robust optimization, approximation algorithms, scheduling theory, and algorithmic game theory. His publications span topics like integer programming, optimal transport, and congestion games. He collaborates across disciplines, emphasizing practical applications of theoretical insights.

• Business Administration
• Operations Research
• Supply Chain Management
• +6 more

Prof. Dr. Julia Rieck is a Full Professor of Business Administration at the University of Hildesheim , leading the Department of Business Administration and Operations Research within the Faculty of Mathematics, Natural Sciences, Economics and Computer Science. As Dean of the Faculty , she oversees academic programs, quality management, and research initiatives. Her roles include academic advising for the Business Information Systems (B.Sc./M.Sc.) programs and active participation in examination boards and quality committees. Education: PhD in Political Science (Dr. rer. pol.) with summa cum laude (2008), Habilitation at Clausthal University of Technology (2014), and studies in Business Mathematics (Diploma, University of Hamburg, 2003) and Mathematics (Georg-August-University Göttingen, 2000). Research: Focuses on Operations Research , Supply Chain Management , Project Planning , and Logistics . Her work integrates mathematical modeling , machine learning , and real-world applications , particularly in disaster response , dynamic transportation , and sustainable e-commerce . Projects: Leads third-party funded initiatives like "IT für die sorgende Gesellschaft" (AI in healthcare/social sectors) and contributes to the HULLS real-lab (AI in aging societies). Collaborates with regional companies (e.g., Youco, ADITUS) and institutions (HAWK, University of Hannover). Teaching: Emphasizes practical application through case studies, industry partnerships, and the IT-Speed Dating event for student-company connections. Her courses cover project resource planning , logistics , and digital transformation . Labs & Teams: Active in the Institute of Business Administration & Business Information Systems , contributing to the KET Kompetenzwerkstatt (entrepreneurship support) and interdisciplinary teams in AI and sustainability research.

Niels AgatzView profile

Professor

• Last-Mile Logistics
• Supply Chain Management
• Transportation Analytics
• +5 more

Niels Agatz is a Full Professor of last-mile supply chain analytics at Rotterdam School of Management (RSM), Erasmus University Rotterdam, within the Department of Technology and Operations Management. He serves as the scientific director of TKI Dinalog, the Dutch national institute for collaborative logistics research, and as an area editor for Transportation Science . His academic career includes a Ph.D. from RSM and an M.Sc. in industrial engineering from Eindhoven University of Technology, with visiting positions at Georgia Tech and the Pontifical Catholic University of Chile. Professor Agatz's research focuses on developing innovative and sustainable last-mile supply chains through advanced analytics, with particular expertise in transportation-enabled services, urban delivery systems, and demand management. His work bridges theoretical operations research with practical applications in logistics and transportation. The breadth of his research is evident in his publications spanning topics from drone delivery optimization to sustainable time slot management and truck platooning. His publications demonstrate significant impact in the field of transportation and logistics, with several highly cited papers on ride-sharing systems, drone delivery optimization, and sustainable logistics practices. The research consistently addresses practical industry challenges while advancing methodological approaches in operations research. NWO Rubicon Grant INFORMS TSL Stella Dafermos Achievement Award Professor Agatz teaches courses on distribution networks and management science at RSM. His research has been widely featured in leading academic journals and international media outlets, reflecting the practical relevance of his work to industry challenges in last-mile delivery and sustainable logistics. He collaborates extensively with industry partners to translate academic insights into practical solutions for complex logistics problems.

• Algorithms and Complexity
• Parameterized Algorithms
• Approximation Algorithms
• +7 more

Matthias Mnich is a Professor and Head of the Institute for Algorithms and Complexity at Hamburg University of Technology (TUHH), within the School of Electrical Engineering, Computer Science and Mathematics. He also serves as Deputy Dean International, reflecting his leadership in academic administration and international collaboration. He is a principal investigator at the Helmholtz Graduate School for the Structure of Matter, further emphasizing his interdisciplinary impact. His research lies at the intersection of theoretical computer science and practical algorithm design, focusing on parameterized algorithms , approximation algorithms , combinatorial optimization , scheduling , and algorithmic game theory . His work often bridges theoretical guarantees with real-world applications in energy systems, quantum computing, and logistics. The recent publications (2023–2025) highlight his sustained excellence in top-tier venues such as FOCS, ICALP, ESA, STACS, and journals like Mathematical Programming and ACM Transactions on Algorithms . These works explore foundational problems in vector bin packing , integer programming , graph algorithms , and kernelization , while also applying algorithmic techniques to microgrid energy optimization and quantum algorithm engineering . He is deeply embedded in the theoretical computer science community, having served on program committees of major conferences including: STACS 2023 ESA 2024 FOCS 2023 ICALP 2024 IJCAI 2019–2025 AAAI 2018 SWAT 2018 He has successfully supervised several PhD students to completion, including Matthias Kaul , Roland Vincze , and Alexander Göke , many of whom have taken postdoctoral positions at institutions like the University of Bonn and University of Augsburg. His current research projects include PATTERN (2025–2031) , Hamburg Quantum Computing (2024–2029) , and Kernelization for Big Data , indicating long-term funding and strategic research directions. He leads the Institute for Algorithms and Complexity (E-11) , fostering a research environment focused on high-impact algorithmic research.

• Logistics Optimization
• Transportation Planning
• Operations Research
• +3 more

Prof. Michael Schneider is Universitätsprofessor and Chair of Computational Logistics at RWTH Aachen University since 2016. Previously, he held positions at TU Darmstadt (2013-2016) and earned his doctoral degree from TU Kaiserslautern (2012). His research focuses on logistics optimization, including transportation routing, warehouse management, and metaheuristic methods for solving complex operational challenges. He leads the Global Challenges Lab and serves as communication chair of VeRoLog (EURO's vehicle routing group). Research interests include: quantitative modeling for supply chains, heuristic/exact optimization methods, electric vehicle routing, territory design, and production planning. Notable achievements include the INFORMS Journal on Computing Meritorious Paper Award (2021) and editorial roles in journals like Applied Mathematical Modelling. Publications span topics like vehicle routing with time windows, electric logistics networks, and warehouse automation strategies. His work integrates advanced algorithms with real-world industry applications (e.g., DHL, Picnic). The Computational Logistics group collaborates on projects addressing sustainability, autonomous systems, and modern warehousing challenges. Education: Business Admin & Computer Science (University of Mannheim), PhD (TU Kaiserslautern) Professional Roles: VeRoLog Communication Chair, EURO Working Group Key Projects: Electric vehicle routing optimization, warehouse automation, and sustainable logistics networks

Michael RitterView profile

Researcher

• Combinatorial Optimization
• Integer Programming
• Operations Research
• +4 more

Dr. Michael Ritter is a researcher and academic staff member at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology and the Department of Mathematics. His primary role involves advising Master's students in Mathematics programs and coordinating administrative duties for academic affairs. He is part of the Discrete Optimization research group and collaborates with professors like Stefan Weltge and Peter Gritzmann on advanced optimization projects. His research focuses on Combinatorial Optimization, Integer Programming, and real-world applications such as flight schedule design, semiconductor manufacturing optimization, and logistics systems. He has contributed to projects involving automated driving systems, production network resilience, and low-power semiconductor design. Ritter teaches courses on Discrete Optimization and Case Studies in Optimization, balancing theoretical instruction with practical problem-solving. He has co-advised numerous theses on topics ranging from supply chain optimization to timetabling algorithms, demonstrating his commitment to both academic research and student mentorship. His work bridges mathematical theory with industrial applications, addressing challenges in manufacturing, transportation, and electronics through rigorous optimization frameworks. He maintains an active publication record in reputable journals and conferences, reflecting his expertise in interdisciplinary optimization research.

• Theoretical Computer Science
• Algorithm Engineering
• Parallel Computing
• +3 more

Prof. Dr. Peter Sanders is a full professor in Theoretical Computer Science at the Karlsruhe Institute of Technology (KIT), leading the Algorithm Engineering group. His academic career includes a doctoral degree from Karlsruhe University and research stints at institutions like the Max Planck Institute for Informatics. He specializes in algorithm theory and engineering, focusing on parallel computing, large-scale data processing, and graph partitioning. His research bridges theoretical foundations with practical implementations, emphasizing real-world applications in optimization, route planning, and distributed systems. Education: Ph.D. in Computer Science, Karlsruhe University (1996) Bachelor/Master studies at Karlsruhe University (1988-1996) Research Interests: Algorithm design and analysis Parallel and distributed algorithms Graph algorithms and partitioning Algorithm engineering for big data High-performance computing Publications: Over 250 papers, emphasizing parallel algorithms, distributed systems, and graph theory. Recent work includes scalable SAT solving, hypergraph partitioning, and distributed string sorting. His contributions have advanced practical applications in route planning, load balancing, and large dataset processing. Awards: Recipient of the prestigious Leibniz Prize (DFG) and Baden-Württemberg State Research Prize. He coordinated the DFG Priority Program on Algorithm Engineering and is an active reviewer for major funding bodies. Consulting: Engages with companies like SAP and Google, focusing on optimization, route planning, and database algorithms. Leads projects on algorithm scalability and real-world problem-solving. Labs/Teams: Heads the Algorithm Engineering group at KIT, fostering collaborations in distributed computing and algorithmic research.

Hanno FriedrichView profile

Associate Professor

• Freight Transport Modelling
• Transport Economics
• Risk Management in Logistics
• +6 more

Prof. Dr. Hanno Friedrich is an Associate Professor of Freight Transportation - Modelling and Policy at Kühne Logistics University (KLU) in Hamburg, Germany. He holds a Diplom-Wirtschaftsingenieur from the Karlsruhe Institute of Technology (KIT) and a Ph.D. in Economics from KIT (2010), focusing on logistics simulation in food retailing. Prior to academia, he worked at McKinsey & Company (2004-2010) and served as a Junior Professor at TU Darmstadt (2011). Affiliations: Kühne Logistics University, World Conference on Transport Research Society (SIG B5), European Transport Conference (Freight & Logistics Committee) Education: PhD in Economics (KIT, 2010), Diplom-Wirtschaftsingenieur (KIT, 2003), ERASMUS exchange at EM Lyon (2001-2003) Research Interests: His work focuses on freight transport demand modelling, food logistics resilience, risk management in supply chains, and intermodal transport networks. Notable projects include FoodDecide (digital food safety tools), HeGeL (German logistics hypernetworks), and SEAK (food supply chain disruptions). Recent Trends: Articles emphasize spatial analysis of organic food demand, machine learning for ETA predictions in intermodal transport, and computational methods for tracing foodborne outbreaks. Recent work explores regional food self-sufficiency and electric mobility in commercial transport. Grants/Projects: Over 15 projects funded by BMBF, BMVI, and EU, including NutriSafe (blockchain in food logistics) and SMECS (ETA forecasting for seaports). Labs/Teams: Leads research groups in food supply chain resilience, freight transport policy, and intermodal logistics innovation at KLU.

• Optimization under uncertainty
• Robust optimization
• Scenario generation
• +8 more

Christina Busing is a Full Professor for Combinatorial Optimization at RWTH Aachen University, a position she has held since 2021. Previously, from 2016 to 2021, she served as a Junior Professor for Robust Planning in Medical Care at the same institution. She leads the Teaching and Research Group on Combinatorial Optimization, contributing significantly to the academic community through her research and teaching activities. Her educational background includes Mathematics studies at WWU Münster, Universidad Comlutense de Madrid, and the Technical University of Berlin. Her doctoral work was completed under the supervision of Prof. Möhring, focusing on Recoverable Robustness in Combinatorial Optimization. She has also held postdoctoral positions at institutions in Aachen, Lancaster, and Vienna. Professor Busing's research spans multiple areas of optimization theory and application. Her work focuses on optimization under uncertainty, robust optimization, scenario generation, combinatorial optimization, complexity theory, optimality criteria, and both exact and heuristic algorithms. She has made significant contributions to applying these theoretical frameworks to practical problems in healthcare, energy systems, and transportation networks. Her interdisciplinary approach bridges theoretical computer science with real-world operational challenges. Her extensive publication record demonstrates a consistent focus on robust combinatorial optimization, with recent work emphasizing applications in healthcare systems, particularly in patient-to-room assignment, primary care scheduling, and pharmacy services. She has developed novel methodologies for handling uncertainty in optimization problems, including recycling valid inequalities and designing consistent decision frameworks for two-stage optimization problems. RWTH Aachen Brigitte Gilles Award for contributions to the advancement of women in science (2022) RWTH Aachen FAMOS Award for excellent family-friendly leadership (2019) RWTH Aachen university-wide Best Teaching Award (2018) TU Berlin Best Diploma Excellence Award in Mathematics (2008) German National Scholarship (Cusanuswerk) (2003-2007) Professor Busing serves on multiple program committees including EURO (2019), INOC (2018), and ESA (2017). She is also involved with the UnRAVeL Graduate College since 2018. Her teaching portfolio includes courses on Graph and Network Optimization, Mathematical Heuristics for Discrete Optimization Problems, and Combinatorial Optimization. She has developed problem-based learning approaches for heuristic methods in decision problems across mathematics, computer science, and industrial engineering. Her research group actively collaborates on interdisciplinary projects addressing operational issues in healthcare, energy systems, and transportation networks, developing mathematically optimized solutions for complex real-world challenges.

Stefan VoßView profile

Professor

• Logistics Optimization
• Metaheuristics
• Sustainable Port Operations
• +3 more

Prof. Dr. Stefan Voß is a Professor at the Institute of Information Systems within the Hamburg Business School (HBS) at the University of Hamburg. He serves on the HBS Dean's Office and focuses on logistics optimization, metaheuristics, and sustainable port operations. His work integrates AI, machine learning, and operations research to address challenges in transportation, supply chain management, and public infrastructure. Research Interests: Dr. Voß specializes in: Metaheuristic algorithms (e.g., fixed set search, GRASP, VNS) Optimization of port and maritime logistics (berth allocation, quay crane scheduling) AI applications in transportation (predictive analytics, emotion recognition) Sustainable operations (green port infrastructure, EV charging networks) Public transport efficiency (bus scheduling, delay prediction) Publications: Recent work emphasizes AI-driven logistics, robust optimization under uncertainty, and digital twin applications in ports. His 2025 studies explore domain-generalized emotion recognition and dynamic seaport automation. 2024 articles highlight multi-objective scheduling, EV fleet optimization, and sustainable container storage. Labs/Teams: Leads research at the Institute of Information Systems, collaborating on port sustainability projects (e.g., Port of Hamburg) and digital innovation in logistics systems.

Robert KleinView profile

Professor

• Operations Research
• Revenue Management
• Logistics Optimization
• +4 more

Prof. Dr. Robert Klein is a Professor at the University of Augsburg within the Faculty of Business and Economics . He holds the Chair of Analytics & Optimization , focusing on the application of mathematical models from operations research to solve real-world decision problems. Research Interests: Pricing and revenue management, last-mile logistics, mobility-on-demand systems, integration of demand management and vehicle routing, discrete choice analysis, integer programming, and approximate dynamic programming. Teaching: Undergraduate mathematics for business, advanced courses in operations research, logistics, and revenue management. His chair offers seminars on Smart Logistics & Mobility and supervises bachelor’s and master’s theses. Publications: Over 20 years, he has co-authored 25+ peer-reviewed articles in journals like Transportation Science , European Journal of Operational Research , and OR Spectrum . His work spans theoretical advancements and practical applications in revenue management and logistics. Students: Supervised 15+ PhD students including David Fleckenstein (2025), Julia Heger (2025), and Jochen Mackert (2019). Collaborations: Works with IBM on mathematical software applications and has co-edited textbooks such as Decision Optimization with IBM ILOG CPLEX (2022).

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +7 more

Prof. Dr. Michael Guckert is a Professor of Business Informatics - Artificial Intelligence at the Department of MND (Management, Natural Sciences, Design) at Technische Hochschule Mittelhessen (THM). He serves as Spokesperson of the KITE Competence Center, Board member at hessian.AI, and Director at StudiumPlus. His research spans multiple domains with a strong focus on AI applications in medical contexts and multi-agent systems. Dr. Guckert's research interests center on applying artificial intelligence to solve complex problems across multiple domains. His primary focus is on medical applications, particularly using AI for electrocardiogram (ECG) analysis, cardiac pathology detection, and clinical decision support systems. He also maintains significant research in multi-agent systems for traffic simulation, model-driven development approaches, and trustworthy/explainable AI systems. His work bridges theoretical AI development with practical applications in healthcare, manufacturing, and transportation. Analysis of Dr. Guckert's recent publications reveals a clear trend toward medical AI applications, particularly in cardiology. His work on the RisKa project demonstrates how AI can interpret ECG data to detect heart conditions, with significant emphasis on explainability and trustworthiness. Parallel to this medical focus, he maintains active research in multi-agent traffic simulation systems (AGADE), acoustic emission analysis, and model-driven development approaches. The publications show increasing collaboration with medical researchers, indicating a strategic focus on interdisciplinary AI applications in healthcare. Dr. Guckert leads the RisKa project (2022-2024), a €736,682 initiative funded by the Ministry for Digital Strategy and Development, which develops an AI-based clinical decision support system for ECG analysis. His research group at THM KITE Competence Center collaborates with Justus Liebig University in Giessen on biomarker research. He has secured multiple research grants for projects involving AI in medical diagnostics, traffic simulation, and manufacturing quality control. His work demonstrates strong industry-academia collaboration, particularly in applying AI to solve real-world problems in healthcare and transportation. Dr. Guckert directs the KITE Competence Center at THM, which focuses on information technology research and applications. His team includes researchers specializing in medical AI, multi-agent systems, and model-driven development. The RisKa project team specifically brings together computer scientists and cardiologists to develop clinically useful AI tools. His work with hessian.AI positions him at the forefront of AI development in the Hesse region of Germany, facilitating collaboration between academic and industry partners.

Rainer KolischView profile

Professor

• Airport Operations Management
• Health Care Operations Management
• Project Management and Scheduling
• +2 more

Rainer Kolisch is a Professor of Operations Management at the TUM School of Management, Technical University of Munich , where he has held a chair since 2002. He currently serves as Head of the Operations & Technology Department (since 2024) and previously as Dean of the QTEM Masters Network (2016–present) and Vice Dean of International Affairs (2007–2020). His career includes academic roles at Technical Universities of Dresden (Full Professor, 2002) and Darmstadt (Associate Professor, 1999–2002). Affiliations: TUM School of Management, Technical University of Munich Editorial Roles: Editor-in-Chief of OR Spectrum (2014–2020), Member of editorial boards for journals like International Journal of Production Research Research Interests focus on Airport Operations Management , Health Care Operations Management , Project Management and Scheduling , and Engineer-to-Order Manufacturing . His work addresses dynamic scheduling, resource allocation, and robust optimization in transportation and healthcare systems, with recent studies on electric vehicle charging networks and agile project management. Scientific Awards include: Best Teaching Award (2022) Excellence in Reviewing (2022) OMEGA Best Paper Award (2021) Handelsblatt Research Recognition (2005) DFG Habilitation Fellowship Advising spans numerous PhD and Master’s students , including Christopher Bersch, Robert Brachmann, and Giacomo Dall'Olio. His grants likely include DFG funding, though specifics are not detailed here.

Frauke LiersView profile

Professor

• Optimization under Uncertainty
• Distributionally Robust Optimization
• Quantum Computing
• +5 more

Prof. Dr. Frauke Liers holds the Professorship of Optimization under Uncertainty & Data Analysis at the Department of Data Science (DDS), Friedrich-Alexander-University Erlangen-Nürnberg. Her research focuses on robust and distributionally robust optimization, mathematical programming, and applications in energy systems, healthcare logistics, and quantum computing. Email: frauke.liers@fau.de ResearchGate: Frauke Liers Research Interests span optimization under uncertainty, data-driven mathematical programming, and interdisciplinary applications. Key areas include: Distributionally robust optimization with scenario reduction and chance constraints Quantum computing optimization for gate routing and noise suppression Energy system modeling (photovoltaics, gas networks, electricity networks) Healthcare logistics (patient transport scheduling under uncertainty) Nanoparticle technology and chemical process optimization Recent Publications emphasize: Advancements in quantum circuit optimization (2025) Explainable optimization methods (2024) Robust approaches for particle precipitation control (2024) Dynamic trajectory optimization (2023) Time-expanded models for network flows (2022)