جستجوی استاد راهنمای دانشگاهی

Lars Rohwedderمشاهده پروفایل

دانشیار

• Algorithms
• Approximation Algorithms
• Online Algorithms
• +۳ مورد دیگر

Lars Rohwedder is an Associate Professor in the Algorithms Group at the University of Southern Denmark (SDU) in Odense. He previously held positions as an Assistant Professor at Maastricht University (Netherlands) and postdoc researcher at EPFL, Lausanne (Switzerland). He earned his Ph.D. in Computer Science from CAU Kiel (Germany), advised by Klaus Jansen, and is a recipient of the 2019 PhD of the year award from Förderverein der TF of Kiel University. His research focuses on algorithms for combinatorial optimization, including approximation algorithms, online algorithms, parameterized algorithms, and integer programming. He has contributed to solving scheduling problems, resource allocation, and optimization under uncertainty. Rohwedder has served on program committees for conferences like MAPSP, SODA, STACS, and ICALP. He is funded by NWO's Open Competition M1 project on quasi-polynomial time algorithms. His teaching includes courses on advanced algorithms, operations management, and optimization at SDU and Maastricht University. Key achievements include a quasi-polynomial approximation for the restricted assignment problem, FPT algorithms for scheduling, and contributions to the Submodular Santa Claus problem. His work bridges theoretical foundations and practical applications, with a focus on algorithmic efficiency and robustness.

Yann Disserمشاهده پروفایل

استاد

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

Professor Yann Disser is a faculty member in the Department of Mathematics at TU Darmstadt since 2021. He previously held an Assistant Professor (tenure-track) position at TU Darmstadt (2016-2021), a PostDoc position at TU Berlin (2012-2016), and a Visiting Professor role at Augsburg University (2015). His research spans Combinatorial Optimization , Online Algorithms , Graph Exploration , Computational Complexity , and Robust Optimization . Current position: Professor (W2), TU Darmstadt Previous: Assistant Professor (2016-2021), TU Darmstadt PostDoc & Habilitation: TU Berlin (2012-2016) His research focuses on algorithmic approaches to optimization problems, including: Combinatorial Optimization for problems like Steiner trees and knapsack variants Online Algorithms with applications to scheduling and transportation Graph Exploration by mobile agents and complexity bounds Computational Complexity of linear programming pivot rules Network Flows and geometric reconstruction Recent publications analyze incremental maximization with greedy methods, lower bounds for active-set methods , and universal circuit designs . His work appears in top venues like IPCO , ESA , and SODA . He advises a team of researchers including David Weckbecker, Farehe Soheil, and Alexander Birx. Current and past advisees often focus on algorithmic theory, with placements at institutions like HPI Potsdam and Merck.

• Combinatorial Optimization
• Integer Programming
• Quadratic Programming
• +۴ مورد دیگر

Cédric Soutil is a Researcher at the Conservatoire National des Arts et Métiers (CNAM) , affiliated with the CEDRIC Laboratory. His work spans combinatorial optimization , integer programming , quadratic programming , and algorithm design , with a focus on solving complex optimization problems in scheduling and graph theory. Recent publications highlight his expertise in non-separable and non-convex quadratic integer programming , knapsack problems , and online computation . His research trends emphasize mathematical reformulations , upper bound algorithms , and optimization models for real-world applications like horse race scheduling and hydrogen production . He has collaborated extensively with researchers such as A. Houdayer , D. Quadri , and P. Tolla , contributing to over two decades of academic output in operations research and combinatorial optimization .

• Algorithms and Complexity
• Parameterized Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

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.

Martin Schmidtمشاهده پروفایل

استاد

• Mathematical Optimization
• Energy Systems
• Mixed-Integer Nonlinear Optimization
• +۳ مورد دیگر

Martin Schmidt is a Full Professor (W3) for Nonlinear Optimization at the Department of Mathematics, Trier University, since 2019. He has held leadership roles in research training groups and international committees, focusing on mathematical modeling and optimization of energy systems, gas networks, and market equilibria. His work bridges mixed-integer nonlinear optimization , bilevel optimization , and robust methods with applications to real-world energy challenges. Education: PhD in Mathematics (2013), Diplom in Mathematics (2008), both from Leibniz University Hannover. Editorial Roles: Editorial Board member of Journal of Optimization Theory and Applications and Optimization Letters , Associate Editor for OR Spectrum and EURO Journal on Computational Optimization . His research integrates complex physical systems (e.g., gas transmission networks) with game-theoretic models to analyze energy markets. Recent publications emphasize robust optimization , decomposition techniques , and machine learning integration in bilevel frameworks. Awards highlight his contributions to gas market feasibility , linear bilevel optimization , and practical applications in energy systems. Collaborations span institutions like Universidad Zaragoza, Sapienza University, and Forschungszentrum Jülich.

• Mixed-Integer Optimization
• Combinatorial Optimization
• Discrete Mathematics
• +۳ مورد دیگر

Timm Oertel is a Professor in the Department of Data Science at Friedrich Alexander University Erlangen-Nuremberg (FAU), holding the Chair of Analytics & Mixed-Integer Optimization. His office is located in Room 03.344 at Cauerstraße 11, Erlangen, and he can be contacted via email at timm.oertel@fau.de or phone at +49 9131 85-67313. His research focuses on mixed-integer optimization, combinatorial optimization, and discrete mathematics, with significant contributions to sparse solutions in lattices and semigroups, integer Carathéodory rank, knapsack polyhedra, and parametric integer optimization. His work bridges theoretical computer science, operations research, and discrete geometry, emphasizing structural properties of integer solutions and algorithmic efficiency. Professor Oertel's publication record (2013-2025) reveals consistent trends in theoretical integer programming, with recent work (2020-2025) concentrating on sparsity patterns, approximation in algebraic structures, and complexity bounds. He frequently collaborates with leading researchers including Iskander Aliev, Robert Weismantel, and Joseph Paat, publishing in top venues like Mathematical Programming and SIAM Journal on Optimization. His research demonstrates deep connections between combinatorial geometry and optimization theory.

• Combinatorial Optimization
• Approximation Algorithms
• Online Algorithms
• +۳ مورد دیگر

Prof. Dr. Sven Oliver Krumke is a Full Professor of Mathematics and currently serves as Dean of the Faculty of Mathematics at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU). His research focuses on Combinatorial Optimization, Approximation Algorithms, Online Algorithms, Complexity, Algorithmic Game Theory, and Graph Theory with Applications. He leads the Optimization Group (AG Optimierung) within the Department of Mathematics. Education and Academic Path: PhD (Dr. rer. nat.) in Mathematics, University of Würzburg (1997) Habilitation in Mathematics, Technische Universität Berlin (2002), Thesis: 'Online Optimization: Competitive Analysis and Beyond' Professor at RPTU since 2004 Research Projects: Principal investigator in the Research Training Group (GRK 2982) 'MIMO: Mathematics of Interdisciplinary Multiobjective Optimization' Project lead for 'ONE PLAN: Optimization in Emergency Medical Services in Rhineland-Palatinate' Teaching includes courses on Analysis, Mathematical Modeling in Economics, and Reading Courses. He supervises Bachelor's and Master's theses in Optimization-related topics. He has held roles such as Scientific Researcher at the Konrad-Zuse-Zentrum Berlin (1998–2004), and has extensive international collaborations, including a Fulbright-funded stay at SUNY Albany (1992–1993). His work emphasizes practical applications in healthcare logistics, emergency services optimization, and algorithmic solutions for real-world problems.

• Mathematical Optimization
• Game Theory
• Mechanism Design
• +۷ مورد دیگر

Max Klimm is an Assistant Professor for Discrete Optimization at Technische Universität Berlin, affiliated with Faculty II – Mathematics and Natural Sciences and the Department of Mathematics. He leads the research group in Discrete Optimization and holds editorial roles at journals like the International Journal of Game Theory and Operations Research Forum . His academic journey includes a PhD in Mathematics from TU Berlin (2012), followed by roles as an Assistant Professor at Humboldt-Universität zu Berlin and Head of the Junior Research Group at the Einstein-Center for Mathematics. His research focuses on mathematical optimization, game theory, and mechanism design applied to multi-agent systems in traffic, telecommunications, and economics. Recent work addresses equilibrium computation in congestion games, stochastic optimization, and algorithmic challenges in network design. Key projects include Combinatorial Network Flow Methods for Gas Markets and the Math+ projects on mechanism design and evolutionary models for networks. Teaching responsibilities include courses on Discrete Optimization, Algorithmic Game Theory, and introductory mathematical courses. His research has been funded by DFG, Einstein Center, and Math+ initiatives. Notable contributions include advancements in parametric flow algorithms, impartial selection mechanisms, and reconstructing historical road networks using cost-benefit models.

Stefan Voßمشاهده پروفایل

استاد

• Logistics Optimization
• Metaheuristics
• Sustainable Port Operations
• +۳ مورد دیگر

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.

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.

• Mathematical Optimization
• Algorithmic Game Theory
• Multi-Agent Systems
• +۳ مورد دیگر

Max Klimm is an Assistant Professor for Discrete Optimization at Technische Universität Berlin, affiliated with the Department of Mathematics within Faculty II – Mathematics and Natural Sciences. He holds a PhD in Mathematics from TU Berlin (2012) and previously served as an Assistant Professor for Operations Research at Humboldt-Universität zu Berlin (2014–2016) and led the Junior Research Group for Optimization under Uncertainty at the Einstein-Center for Mathematics (2014–2016). His research focuses on algorithmic game theory, mathematical optimization of multi-agent systems in traffic, telecommunications, and economics. Key areas include network flows, congestion games, mechanism design, and infrastructure networks. He actively contributes to academic activities as an associate editor for journals like International Journal of Game Theory and Operations Research Forum , and has served on program committees for conferences such as AAAI, EC, and WINE. Recent work includes studies on evolutionary road network reconstruction, robustness of potential-based flows, and algorithmic solutions for knapsack and assignment problems. His research bridges theoretical foundations with practical applications in transportation and resource allocation.

• Optimization
• Mixed-Integer Programming
• Lattice Theory
• +۵ مورد دیگر

Professor Timm Oertel is a leading academic at the Department of Data Science (DDS) at Friedrich Alexander University Erlangen-Nuremberg, where he holds the Chair of Analytics & Mixed-Integer Optimization. His research has established him as a significant contributor to the field of mathematical optimization, with a particular focus on integer programming and its applications. Professor Oertel's research interests center on mathematical optimization , specifically mixed-integer programming , lattice theory , semigroups , and combinatorial optimization . His work explores fundamental questions about sparsity in integer solutions, properties of lattice points in polyhedra, and the theoretical foundations of optimization algorithms. His research bridges pure mathematics with practical applications in operations research and computer science. An analysis of Professor Oertel's publication record reveals a strong thematic consistency with evolving depth. His work consistently addresses sparsity phenomena in integer programming, structural properties of lattices and semigroups, and computational complexity aspects of optimization problems. The publications demonstrate increasing sophistication in handling block-structured problems and parametric optimization scenarios, with recent work extending to colorful variants of classical geometric lemmas applied to integer programming. Professor Oertel has established productive collaborations with leading researchers including Iskander Aliev, Robert Weismantel, and Joseph Paat. His research has been consistently published in top-tier venues including Mathematical Programming , SIAM Journal on Optimization , and the prestigious IPCO (Integer Programming and Combinatorial Optimization) conference series. These publications reflect rigorous theoretical contributions with potential applications across operations research, computer science, and discrete mathematics.

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).

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

Steffen Goebbelsمشاهده پروفایل

استاد

• 3D City Modeling
• Computer Graphics
• Numerical Analysis
• +۵ مورد دیگر

Prof. Dr. Steffen Goebbels is a Professor of Mathematics and Computer Science at Niederrhein University of Applied Sciences, Faculty of Electrical Engineering and Computer Science in Krefeld, Germany. He maintains an office in room F 202 and is actively involved in teaching and research. His academic work spans multiple disciplines with a strong focus on applied mathematics and computer science. His research interests center around 3D city modeling, mathematical optimization, and computer graphics. He has made significant contributions to the field of CityGML data processing and has developed algorithms for calculating 3D building models from land registry data and laser scan data. His work with the iPattern Institute has led to practical applications in cities like Krefeld, Leverkusen, and Dortmund. He has also contributed to neural network approximation theory and various optimization problems. Prof. Goebbels has published extensively in recent years, with publications spanning computer graphics, mathematical optimization, and machine learning. His research shows a consistent pattern of applying mathematical techniques to solve practical problems in 3D modeling and computer vision. He has also co-authored several influential textbooks on mathematics for computer science students. He has received recognition for his work through publications in reputable journals and conference proceedings, though specific awards are not mentioned in the available information. His research has practical applications in urban planning, architectural visualization, and manufacturing processes. Prof. Goebbels is actively involved in teaching mathematics courses (Mathematics 1-3), Numerical Analysis, Logic Programming, Functional Programming, and Scientific Computing. He has developed teaching materials including online courses and textbooks that are widely used in his institution.