جستجوی استاد راهنمای دانشگاهی

Christian Mendlمشاهده پروفایل

استادیار

• Quantum Computing
• Computational Physics
• Statistical Physics
• +۲ مورد دیگر

Christian Mendl is a Rudolf Mößbauer Tenure Track Assistant Professor at the Technical University of Munich (TUM) , affiliated with the School of Computation, Information and Technology and the Institute for Advanced Study (TUM-IAS) . His career includes a postdoctoral position at Stanford University (2015-2017) under a Feodor Lynen Fellowship from the Alexander von Humboldt Foundation, a Junior Professorship at TU Dresden (2017-2019), and a PhD in Physics from LMU Munich (2012). Education : Physics and Mathematics (TUM) Appointments : Rudolf Mößbauer Assistant Professor (TUM, 2019), Junior Professor (TU Dresden, 2017), Postdoc (Stanford, 2015-2017) Research Focus : Mendl specializes in Quantum Computing , Computational Physics (tensor networks, quantum Monte Carlo, neural-network quantum states), Statistical and Non-Equilibrium Physics , and Numerical Simulation . His work bridges quantum information theory with condensed matter physics, emphasizing efficient quantum algorithms and simulators for complex systems. Scientific Contributions : Recent publications highlight advancements in quantum circuit optimization , tree tensor network simulations , block encoding of operators , and quantum-assisted optimization for problems like the capacitated vehicle routing and Toda lattice dynamics. His methods often integrate machine learning with quantum information to address challenges in Hamiltonian simulation and quantum error analysis . Awards : Alexander von Humboldt Feodor Lynen Fellowship, Boehringer Ingelheim Fonds PhD Fellowship, TopMath Graduate Program, Studienstiftung des deutschen Volkes Grants : Rudolf Mößbauer Tenure Track Fellowship (TUM-IAS), Dieter Schwarz Fellowship

• Algorithms
• Computational Geometry
• Wireless Communication
• +۴ مورد دیگر

Stefan Funke is a researcher at the University of Stuttgart, Germany, with a focus on algorithms and computational geometry. His work spans wireless communication, route planning, and trajectory analysis. Research Interests: Algorithms, Computational Geometry, Wireless Communication, Route Planning, Trajectory Segmentation His recent publications (2024-2025) explore topics like 3D epithelial cell dynamics, graph radius computation, and polyline simplification, emphasizing scalability and efficiency. Earlier works (2017-2019) investigate contraction hierarchies, energy-efficient routing, and trajectory storage systems. Stefan collaborates frequently with Sabine Storandt, Claudius Proissl, and Tobias Rupp. He applies geometric methods to problems in wireless networks, road systems, and data structures, with a recurring emphasis on optimization and robustness.

• Logistics
• Supply Chain Management
• Mobile Business
• +۴ مورد دیگر

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.

• Organic Computing
• Evolutionary Algorithms
• Learning Classifier Systems
• +۶ مورد دیگر

Professor Jörg Hähner holds the Chair of Organic Computing at the University of Augsburg's Faculty of Applied Computer Science within the Institute of Computer Science. He leads a research team focused on evolutionary computation, self-organizing systems, and intelligent computing approaches. His educational background includes computer science studies at TU Darmstadt. His academic career progression shows steady advancement in the field of organic and self-organizing computing systems. Prof. Hähner's research spans multiple interconnected domains in computational intelligence. His primary focus is on Organic Computing, which involves developing systems that can adapt and self-organize in complex environments. Within this framework, he has made significant contributions to Evolutionary Algorithms, particularly Cartesian Genetic Programming and Learning Classifier Systems. His work explores how these techniques can be applied to real-world problems such as predictive maintenance, energy systems optimization, and industrial automation. The research demonstrates a strong emphasis on both theoretical foundations and practical applications of self-adaptive systems. An analysis of his recent publications reveals a strong concentration on evolutionary computation techniques, particularly Cartesian Genetic Programming variants and Learning Classifier Systems. His research group has been actively developing frameworks like CRust_GP and GRAHF to advance modular construction of evolutionary algorithms. There's a clear trend toward applying these techniques to industrial problems including predictive maintenance, resource allocation in networks, and energy management systems. The publications show consistent exploration of fundamental questions about algorithm behavior while maintaining strong connections to practical applications. Prof. Hähner leads an active research group with numerous PhD students and collaborators, including Karen Poloczek, Henning Cui, Victor Gerling, Dr. Michael Heider, Marco Hüller, Neele Kemper, Helena Stegherr, Jonathan Wurth, and Roman Sraj. His team regularly publishes in top-tier conferences and journals in evolutionary computation, intelligent systems, and industrial applications. The Organic Computing research group maintains a strong presence in both theoretical and applied research, with projects spanning from foundational algorithm development to industrial applications in manufacturing, energy systems, and network optimization. The group's work demonstrates a cohesive research vision centered on creating adaptive, self-organizing computational systems that can operate effectively in complex real-world environments.

Thomas Kirschsteinمشاهده پروفایل

استاد

• Logistics Management
• Supply Chain Sustainability
• Operations Research
• +۴ مورد دیگر

Introduction Prof. Dr. Thomas Kirschstein is a Professor at Martin Luther University Halle-Wittenberg (MLU), affiliated with the Faculty of Law, Economics and Business, and a researcher at the Center for Economics of Materials (CEM), Fraunhofer-Zentrum IMW. His work focuses on logistics, emission management, and robust statistical methods. He holds a PhD in Economics (2014) and a habilitation in eco-oriented logistics management (2020). Education 2002–2003: Diploma in Mathematics at MLU 2003–2008: Diploma in Economics at MLU 2014: PhD in Economics (thesis: 'Integrated Supply Chain Planning in Chemical Industry') 2020: Habilitation (thesis: 'Papers on the Eco-oriented Management of Logistics Operations') Research Interests Kirschstein's research integrates logistics and environmental sustainability, including emission reduction in freight transport, robust statistical methodologies, and supply chain optimization. His work combines simulation-based planning with empirical analysis, addressing challenges in complex production networks and intermodal transportation. Awards and Recognition Christian Wolff Award (2020) for habilitation thesis Werner Kern Award (2013/2014) for production management research Best Paper Award (2013) from the Faculty of Law and Business Administration Teaching and Academic Contributions He teaches courses in production management, logistics, and data science. Notable roles include: Lecturer: 'Production & Logistics' (2014–2019) Organized conferences like Logistics Management 2019 and Robust Statistics 2014 Labs and Collaborations Active collaborations with Dow Olefinverbund GmbH and Fraunhofer IMW, focusing on integrated logistics systems and robust estimator development.

Ahmet Cürebalمشاهده پروفایل

پژوهشگر

• Operations Research
• Linear Programming
• Mixed-Integer Programming
• +۵ مورد دیگر

Ahmet Cürebal is an External Doctoral Researcher at the Institute of Information Systems, part of the Business School at the University of Hamburg. He holds B.S. and M.S. degrees in Industrial Engineering from Kirikkale University, Turkey, and is currently pursuing his Ph.D. His research focuses on Operations Research with specializations in Linear Programming (LP), Mixed-Integer Programming (MIP), Combinatorial Optimization, Scheduling, Assignment, and Routing problems within Supply Chain contexts. Key research interests include solving real-world optimization challenges such as staff scheduling in retail sectors, driver workload balancing in logistics firms, and pandemic-era security personnel allocation. His work often involves applying metaheuristic methods like Variable Neighborhood Search (VNS) and Fixed Set Search (FSS) to complex operational problems. Notable publications explore applications such as straddle carrier routing in container terminals, bus route optimization for high-speed rail integration, and competency-based scheduling during crises. His methodologies frequently integrate Goal Programming and Analytical Network Process (ANP) for multi-criteria decision-making scenarios. Cürebal’s research demonstrates a strong emphasis on practical implementations across diverse industries, including healthcare, logistics, and retail, with a focus on balancing efficiency and real-world constraints through advanced mathematical modeling and algorithmic approaches.

Jens Vygenمشاهده پروفایل

استاد

• Combinatorial Optimization
• Approximation Algorithms
• Chip Design
• +۴ مورد دیگر

Prof. Jens Vygen is a full Professor of Discrete Mathematics at the University of Bonn's Research Institute for Discrete Mathematics. He specializes in combinatorial optimization, approximation algorithms, and their applications to chip design and vehicle routing. He has directed large-scale industrial collaborations and supervised over 20 PhD students, including Vera Traub. His work includes co-authoring influential textbooks like Combinatorial Optimization: Theory and Algorithms and Approximation Algorithms for Traveling Salesman Problems . Research highlights include advancements in TSP approximation algorithms, Steiner tree optimization, and network flow algorithms. He has organized major events like the IPCO conference and served on editorial boards of leading journals. Awards include teaching excellence and best paper recognitions at SODA and IPCO. Teaching focuses on advanced topics in discrete mathematics, approximation algorithms, and combinatorial optimization. Courses span undergraduate to graduate levels, emphasizing algorithm design, graph theory, and practical implementations. Labs/teams: Core contributor to Bonn's Hausdorff Center for Mathematics and Bonn's discrete optimization research group. Active in developing algorithms for VLSI routing (BonnRoute) and chip design tools (BonnPlace).

Petra Mutzelمشاهده پروفایل

استاد

• Graph Algorithmics
• Graph Learning
• Combinatorial Optimization
• +۳ مورد دیگر

Petra Mutzel is a Professor of Computer Science at the University of Bonn. Her research focuses on graph algorithmics, temporal networks, and combinatorial optimization with applications in data science and bioinformatics. She holds a PhD in Computer Science from the University of Cologne (1994) and a Diplom in Mathematics from the University of Augsburg (1990). Her work emphasizes algorithmic solutions for complex graph problems, including temporal graph analysis, graph learning, and optimization frameworks for real-world networks. She has contributed to open-source libraries like Tglib for temporal graph processing and frameworks like Scaffold Hunter for medicinal chemistry. Her research spans theoretical foundations and practical implementations, with notable contributions to graph drawing, vehicle routing optimization, and protein complex analysis. Mutzel’s recent publications (2022-2025) explore temporal network dynamics, robust combinatorial optimization, and scalable graph kernel methods. She actively engages in academic leadership, organizing conferences such as WALCOM 2022, and serves on editorial boards for journals in algorithms and computational geometry.

Yann Disserمشاهده پروفایل

استاد

• Combinatorial Optimization
• Online Algorithms
• Graph Exploration
• +۶ مورد دیگر

Yann Disser is a Professor (W2) at the Department of Mathematics, Technische Universität Darmstadt. His research focuses on combinatorial optimization, online algorithms, and graph theory. He holds a PhD in Theoretical Computer Science from ETH Zurich (2011) and has held academic positions at TU Berlin and ETH Zurich. Disser has led numerous DFG-funded research projects, including work on incremental maximization and potential-based flow networks. His teaching includes courses on discrete optimization, algorithmic discrete mathematics, and online optimization. He supervises a research group with members such as Júlia Baligács and Annette Lutz, and has advised multiple PhD students including David Weckbecker. His recent work explores competitive analysis, algorithmic lower bounds, and graph exploration. Education: PhD in Theoretical Computer Science (ETH Zurich, 2011), MSc in Physics (TU Darmstadt), Diplom in Computer Science (TU Darmstadt). Research Interests: Combinatorial Optimization, Online Algorithms, Graph Exploration, Computational Complexity, Incremental Algorithms, Approximation Algorithms. Grants: DFG TRR 154 (2022–2026), DFG Individual Grants (2019–2023), EU EFRE Project (2016–2019). Labs: Deep Learning Lab (TU Darmstadt), Algorithms Lab (ETH Zurich).

Stefan Irnichمشاهده پروفایل

استاد

• Logistics Management
• Operations Research
• Vehicle Routing Problems
• +۵ مورد دیگر

Prof. Stefan Irnich is a Professor at the Chair of Logistics Management, Johannes Gutenberg University Mainz. His research focuses on logistics optimization, vehicle routing problems, and operations research. He leads projects like the DFG-funded 'BiPISh: Bin Packing with Irregular Shapes' (2025), aiming to develop methods for packing irregular 2D shapes. His work bridges theoretical advancements and practical applications, such as integrating drones into routing systems and optimizing last-mile delivery networks. Notably, his former students Dr. Katrin Heßler and Dr. Timo Hintsch won the 2025 EURO Excellence in Practice Award for their BinPACKER project. Dr. Jeanette Schmidt received the Alfred Teves Foundation Prize for her dissertation on routing problem solutions. Irnich also organizes academic events like the SynchroTrans 2013 workshop on synchronization in transport. He maintains an active role in teaching, overseeing Master’s and Bachelor’s seminars in logistics. His research spans algorithm design (e.g., branch-price-and-cut methods), network optimization, and sustainability in transportation. Recent publications address challenges in scattered storage systems, multi-depot routing, and public transport integration.

Christian Grimmeمشاهده پروفایل

دانشیار

• Multiobjective Evolutionary Computation
• Social Media Analysis
• Disinformation Detection
• +۴ مورد دیگر

Prof. Dr.-Ing. Christian Grimme is an Associate Professor and Extraordinary Professor in the Department of Information Systems at the University of Münster. He leads the Computational Social Science and Systems Analysis research group. His roles include acting professorships, research group leadership, and academic co-direction of the ERCIS Competence Center for Social Media Analytics. He holds a Dr.-Ing. in Computer Science and has extensive postdoctoral and habilitation experience. Education Timeline: 2015–2018: Habilitation and venia legendi in Information Systems 2006–2012: PhD in Computer Science (Dr.-Ing.) 1999–2006: Diploma in Computer Science Research Interests focus on Multiobjective Evolutionary Computation, Social Media Analysis, Disinformation Detection, and AI Ethics. His work bridges algorithmic innovation (e.g., optimization algorithms) with societal challenges (e.g., automated propaganda detection). Recent projects include analyzing Large Language Models' role in disinformation mitigation and real-time social media content analysis using human attention mechanisms. Awards include the Best Teaching Award (2024), PPSN XIV Best Paper Award (2016), and multiple travel grants from ACM and DAAD. He actively participates in conferences like GECCO and EMO, contributing to both theoretical and applied research. Advising and grants highlight his role in guiding over 20 theses, spanning Master's and Bachelor's projects in IS/WI. Notable grants include DAAD-funded collaborations and internal university funding for projects like MODERAT! (moderation tools) and ERCIS SMA Competence Center. Labs/Teams: Leads the Computational Social Science & Systems Analysis group, collaborating with global partners via ERCIS. Engages in initiatives like CLAIRE and the Integrity & Security Initiative to address AI ethics and information security challenges.

Tobias Mömkeمشاهده پروفایل

استاد

• Algorithmic Optimization
• Theoretical Computer Science
• Resource-Aware Computing
• +۴ مورد دیگر

Tobias Mömke is a Professor for Theoretical Computer Science at the University of Augsburg , Germany. His research focuses on algorithmic optimization for problems with limited resources , particularly in Traveling Salesman Problem (TSP) variants , approximation algorithms , and online computation . He leads the Resource Aware Algorithmics team. Fields of Interest : TSP, Approximation Algorithms, Online Algorithms, Graph Theory Advising : Mentors students like Michael Ruderer, Aida Roshany-Tabrizi, and Morteza Alimi. Scientific Contributions : His recent work includes path cover techniques for TSP variants, bridge lemmas in algorithm design, and normalizing graphs for edge coloring. He has developed linear-time and polynomial-time solutions for scheduling and flow problems. Awards : DFG Heisenberg Grant (2020) , DFG Sachbeihilfe (2020) Email : moemke@informatik.uni-augsburg.de

Martin Middendorfمشاهده پروفایل

استاد

• Swarm Intelligence
• Bioinformatics
• Genome Rearrangement Analysis
• +۷ مورد دیگر

Prof. Dr. Martin Middendorf is a faculty member at the Department of Computer Science , Faculty of Mathematics and Computer Science , Leipzig University , Germany. He leads the Swarm Intelligence and Complex Systems Group and focuses on interdisciplinary research at the intersection of computational methods and biological systems. Fields of Interest Swarm Intelligence Bioinformatics Genome Rearrangement Analysis Combinatorial Optimization Evolutionary Algorithms Task Allocation in Multi-Agent Systems His recent research emphasizes mitochondrial genome annotation , predator-prey dynamics in swarm systems , and metaheuristic algorithms for dynamic optimization . Key trends include de-Bruijn graph applications , pheromone-dependent movement modeling , and automated behavior tracking in social insects . Supervised Students Dr. Nicolas Wieseke Dr. Hoang Thanh Le Dr. Fatma Turna Tobias Jagla Carsten Seemann Prof. Middendorf's group develops tools like DeGeCI 1.1 for mitochondrial gene annotation and explores swarm-controlled emergence in ant clustering systems. They apply swarm intelligence principles to solve real-world problems in vehicle routing , sewer network design , and biomedical signal processing .

• Logistics Optimization
• Material Handling Systems
• Discrete-Event Simulation
• +۳ مورد دیگر

Slaheddine Mestiri is a Researcher at the Chair of Material Handling and Logistics (Lehrstuhl für Fördertechnik Materialfluss Logistik) at the Technical University of Munich (TUM), located at Boltzmannstraße 15, Garching. Holding an M.Sc. degree, he actively contributes to logistics research through publications and the PlaKAT project, focusing on simulation-based solutions for transport systems and warehouse automation. Research Profile His work centers on discrete-event simulation, data-driven modeling, and AI applications in logistics. Key contributions include developing frameworks for material handling system modeling, transport system dimensioning, and order assignment strategies for heterogeneous fleets. Recent publications demonstrate increasing focus on warehouse AI scalability and feasibility assessment. Publication Trends Analysis of his 2021-2025 publications reveals consistent methodology: simulation-driven approaches applied to material flow challenges. Dominant themes include transport system optimization (43% of works), warehouse innovation (29%), and decision-support tool development (28%). His research shows progressive integration of AI concepts, particularly in 2024-2025 works addressing warehouse automation scalability. Projects & Collaboration Primary contributor to PlaKAT project (funded by German Federal Ministry for Economic Affairs and Climate Action) developing a transport means selection compass Regular collaborator with Prof. Johannes Fottner and researchers including Soufi, David, and Küster Publications presented at German Material Flow Congress and in journals like Flexible Services and Manufacturing Journal Research Infrastructure Mestiri operates within TUM's Chair of Material Handling and Logistics, a research unit specializing in material flow systems. The chair maintains industry partnerships for applied logistics research, with Mestiri focusing on simulation model development and transport system analysis within this ecosystem.

Stefan Minnerمشاهده پروفایل

استاد

• Logistics
• Supply Chain Management
• Inventory Management
• +۹ مورد دیگر

Prof. Stefan Minner is a Full Professor of Logistics and Supply Chain Management at the TUM School of Management, Technical University of Munich since 2012. His academic career includes professorships at the University of Vienna (2008–2012) and University of Mannheim (2004–2008), with prior roles at the University of Calgary and University of Magdeburg. He holds a Ph.D. (1999) and Habilitation (2003) from Magdeburg, focusing on supply chain optimization and inventory management. Research focuses on data-driven logistics network design, inventory management under uncertainty, and urban logistics. Key areas include blockchain in supply chains, commodity procurement strategies, and automation in retail operations. He serves as Editor-in-Chief for the International Journal of Production Economics and holds leadership roles in logistics societies like the German Logistics Association (BVL) and International Society for Inventory Research (ISIR). His honors include Fellow of ISIR (2016), Wirtschaftswoche Top Researcher (2020), and the M&SOM Practice-based Research Competition (2019). Research output spans 25+ years, with recent work addressing AI in logistics, sustainable supply chains, and pandemic-era ambulance dispatching systems. Teaching includes courses on inventory management, transportation analytics, and sustainable supply chains. His lab's work integrates optimization, simulation, and empirical methods to solve real-world logistics challenges in automotive, retail, and manufacturing sectors.