جست‌وجوی استاد و پژوهشگر

Ian Gentمشاهده پروفایل

استاد

• Constraint Programming
• Artificial Intelligence
• Combinatorial Search
• +۴ مورد دیگر

Prof Ian Gent is a Professor in the School of Computer Science at the University of St Andrews. His research focuses on combinatorial search problems in artificial intelligence, particularly integrating computational group theory with constraint programming for applications like scheduling and timetabling. He holds academic qualifications including an M.A. in Mathematics from the University of Cambridge, an M.Sc. in Knowledge-Based Systems from the University of Edinburgh, and a Ph.D. in Computer Science from the University of Warwick. He supervises PhD student Mustafa Abdelwahed and has contributed to projects such as the development of the CONJURE tool for automated constraint model generation. His work spans constraint satisfaction, puzzle-solving AI, and interdisciplinary research between AI and mathematics. Notable publications include advancements in tabulation techniques (TabID) and explanations for pen-and-paper puzzles using MUSes. He is affiliated with the Centre for Research into Equality, Diversity & Inclusion and the Centre for Interdisciplinary Research in Computational Algebra. Education: M.A. in Mathematics, University of Cambridge M.Sc. in Knowledge-Based Systems, University of Edinburgh Ph.D. in Computer Science, University of Warwick Research Interests: Constraint programming and automated modelling Applications of AI to puzzles and games Interdisciplinary computational methods Key Projects: CONJURE: Automatic generation of constraint models Integration of computational group theory with constraint programming Development of tools for puzzle-solving explanations

Nysret Musliuمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Combinatorial Optimization
• Heuristic Optimization
• +۵ مورد دیگر

Associate Professor Dr. Nysret Musliu is a faculty member at TU Wien's Faculty of Informatics, leading the Christian Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling. He holds a PhD (2001) and habilitation (2007) from TU Wien. His research focuses on AI techniques, combinatorial optimization, scheduling, and heuristic methods applied to real-world problems like workforce scheduling and timetabling. Education: PhD in Computer Science (2001) TU Wien Habilitation in Applied Computer Science (2007) TU Wien Master's degree (1996) University of Prishtina Research Interests: Artificial Intelligence Techniques Combinatorial Optimization Heuristic Algorithms Machine Learning Integration Hybrid Techniques for Scheduling Problems Grants: Christian Doppler Laboratory (2017-2024), FWF Projects, Softnet Austria, and industry collaborations. Advises PhD students in optimization and scheduling domains. Labs/Teams: Christian Doppler Laboratory, Databases and Artificial Intelligence Group.

David Laiمشاهده پروفایل

دانشیار

• Operations Research
• Logistics Optimization
• Operations Management
• +۳ مورد دیگر

Dr. David Lai is an Associate Professor of Operations Management at Queen Mary University of London (QMUL), affiliated with the School of Business and Management and the Department of Business Analytics and Applied Economics. He holds a PhD in Systems Engineering and Engineering Management from the Chinese University of Hong Kong (2014). Before joining QMUL, he served as Assistant Professor at the University of Southampton (2022–2024), Eindhoven University of Technology (2020–2022), and VU Amsterdam (2014–2020). His research focuses on optimization challenges in logistics, transportation systems, and operations management, including vehicle routing problems, scheduling, and heuristic algorithm development. Key interests include dynamic routing under stochastic conditions, green logistics, and real-time rescheduling for public transit. Dr. Lai’s work spans theoretical contributions (e.g., tabu search heuristics, graph-based formulations) and applied studies (e.g., construction industry logistics, public transport disruption management). His publications highlight innovations in metaheuristics, multi-objective optimization, and network design. He currently holds no explicitly listed scientific awards but has a robust academic portfolio with over 15 peer-reviewed articles since 2009. His teaching and supervision focus on operations management and analytics, though specific advisee names are not documented here.

Anita Schöbelمشاهده پروفایل

استاد

• Operations Research
• Mathematical Optimization
• Robust Optimization
• +۱۲ مورد دیگر

Anita Schöbel is a Professor in the Department of Mathematics at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU) and serves as the Director of the Fraunhofer Institute for Industrial and Financial Mathematics (ITWM) in Kaiserslautern. She is a leading figure in operations research and mathematical optimization, with a strong focus on public transportation systems, robust optimization, and multi-objective decision-making. Her dual roles bridge academic research and industrial application, particularly in logistics, healthcare, and energy systems. Her research interests include: Robust and integer optimization Public transport planning (timetabling, line planning, delay management) Facility and hub location problems Multi-objective optimization under uncertainty Algorithmic methods in transportation networks The analysis of her recent publications reveals a consistent focus on integrating robustness into transportation planning, using machine learning to enhance schedule reliability, and advancing theoretical frameworks for multi-objective optimization. Her work often combines mathematical rigor with real-world applicability, especially in public transit and pandemic modeling. She has contributed significantly to the development of optimization models for public health during the COVID-19 crisis. Her scientific awards include leadership roles in major professional societies: President of the European Association of Operational Research Societies (EURO), 2022–2023 President of the German Society for Operations Research (GOR), 2019–2020 Anita Schöbel has been actively involved in grant-funded research and collaborative projects, including the DFG Research Group FOR2083 on integrated transportation planning, the EU project EASIER, and the BMBF project SynphOnie. She is currently co-spokesperson of the DFG Graduate College 2982 on 'Mathematics of Interdisciplinary Multiobjective Optimization'. She also serves on advisory boards such as the steering committee of HLRS and the Fraunhofer Strategic Research Field on Next Generation Computing. She leads the research group 'Optimization' at RPTU and is associated with initiatives like LinTim (software for transport planning), QuanTUK (quantum computing applications), and GRK 2982. Her leadership extends to academic governance, including membership in the RPTU University Council and the Departmental Council of Mathematics.

Egidio Quagliettaمشاهده پروفایل

استادیار

• Railway Traffic Management
• Advanced Simulation Methods
• Railway Infrastructure Optimization
• +۴ مورد دیگر

Egidio Quaglietta is an Assistant Professor in Railway Traffic Management at the Department of Transport and Planning, TU Delft. He holds a PhD from the University of Naples, Federico II, and has extensive experience in railway signalling and traffic management, including roles at Ansaldo STS and Network Rail. His work focuses on advanced simulation, automated algorithms, and innovative technologies for railway optimization. He leads projects like MOVINGRAIL (EU Shift2Rail) and contributed to FP7 projects like ON-TIME and Capacity4Rail, developing tools for traffic planning and disruption management. Research interests include railway automation, real-time control systems, and capacity enhancement through technologies like ERTMS/ETCS and Virtual Coupling. He advises on EU and national projects, including the UK’s Digital Railway initiative. Teaching includes the master’s course CIE5803 on Railway Traffic Management. Notable projects include optimizing UK railway capacity through ETCS Level 2/3 integration, leading strategic planning for enhanced railway automation, and developing frameworks for integrated traffic management. His work emphasizes data-driven decision-making and interoperability in rail systems.

Philine Schieweمشاهده پروفایل

استادیار

• Operations Research
• Public Transport Optimization
• Algorithmic Discrete Mathematics
• +۳ مورد دیگر

Philine Schiewe is an Assistant Professor at Aalto University's Department of Mathematics and Systems Analysis, School of Science. Her research focuses on algorithmic methods for public transport optimization, including line planning, timetabling, and vehicle scheduling. She has contributed to integrated optimization frameworks for transport networks, emphasizing computational efficiency and real-world applicability. Her work spans theoretical algorithm design (e.g., fixed-parameter tractability, graph-based methods) and practical applications in transportation systems. Key research areas include fare structure optimization, user equilibrium modeling, and infrastructure investment strategies. She collaborates on open-source tools like TimPassLib for periodic timetabling and passenger routing. Recent publications address non-pool-based line planning algorithms, bi-objective fare design models, and combined truck-cargo-bike routing optimizations. Her research bridges operations research, discrete mathematics, and transportation engineering to improve urban mobility systems.

Pierre Fouilhouxمشاهده پروفایل

استاد

• Combinatorial Optimization
• Mathematical Programming
• Polyhedral Approaches
• +۴ مورد دیگر

Pierre Fouilhoux is a Full Professor in Computer Science and Discrete Mathematics at Sorbonne Paris Nord University (formerly Paris 13 University), affiliated with the LIPN Laboratory and the Algorithmics and Combinatorial Optimization (AOC) Team. He previously held a position at Sorbonne Université's LIP6 Laboratory. His research focuses on Combinatorial Optimization, Mathematical Programming, Polyhedral Approaches, and Operational Research, with contributions to scheduling, network design, and robust optimization. Education: PhD in Computer Science (2004): Université Blaise Pascal, Clermont-Ferrand. Habilitation à Diriger des Recherches (HDR, 2018): Sorbonne Université. DEA in Computer Science and Operational Research, License and Master in Computer Science, and Mathematics License. Research Interests: His work addresses polyhedral structures, exact algorithms, and combinatorial optimization problems such as scheduling, unit commitment, and network reliability. He has developed Branch-and-Cut methods and symmetry-breaking techniques for integer programming. Publications: Over 30 peer-reviewed articles in journals like European Journal of Operational Research , Mathematical Programming , and Discrete Applied Mathematics . Recent work includes anchor-robust scheduling, unit commitment polytopes, and orbitopal fixing. Awards: 2006 Grand Prize for Young Researcher from Clermont-Ferrand for his contributions to science popularization and research communication. Teaching: Courses on Operations Research, Combinatorial Optimization, and Linear Programming at Sorbonne University and SUP Galilée. Supervised over 20 graduate and doctoral students, including topics like multi-objective optimization and virtual network embedding. Labs/Teams: Active in the AOC Team at LIPN, GDR-RO research group, and ISCO conferences. Collaborates with institutions like EDF R&D and Colt-Telecom on applied optimization problems.

Nikola Bešinovićمشاهده پروفایل

مدرس

• Railway Transport Systems
• Transportation Optimization
• Artificial Intelligence in Transport
• +۳ مورد دیگر

Dr. Nikola Bešinović serves as the acting head of the Chair of Rail and Public Urban Transport at TU Dresden's Friedrich List Faculty of Transport and Traffic Sciences. He previously held roles as a lecturer and researcher at TU Delft's Faculty of Civil Engineering and Geosciences, where he earned his PhD in Railway Science (2017). His research focuses on optimizing railway systems through advanced analytics and AI, with an emphasis on resilience, sustainable operations, and disruption management. Education: BSc in Railway Transport and Traffic Engineering, University of Belgrade (2004–2009) MSc in Operations Research in Transport, University of Belgrade (2009–2011) PhD in Railway Science, TU Delft (2012–2017) Research Interests: Resilient transport systems and infrastructure criticality analysis Data-driven decision-making in railway operations AI applications in timetabling and scheduling Passenger-centric disruption management strategies Electrification strategies for regional rail networks Awards: Young Railway Operations Researcher Award (IAROR) First Prize TRAVISIONS Young Researcher Competition Best Student Paper (INFORMS Railway Application Section) 3rd Best IEEE ITS Dissertation Award His work integrates mathematical modeling with real-world challenges, aiming to advance rail transport as a sustainable and efficient mobility solution. Current projects explore AI-driven solutions for adaptive timetables and post-disaster network recovery.

• Operations Research
• Mathematical Programming
• Combinatorial Optimization
• +۷ مورد دیگر

Jose Manuel Tamarit Goerlich is an Associate Professor in the Department of Statistics and Operations Research at the Universitat de València. He has been actively contributing to the field of operations research since the late 1980s, with a strong focus on combinatorial optimization and heuristic methods for scheduling and packing problems. His research interests include Operations Research , Mathematical Programming , Combinatorial Optimization , Heuristic Algorithms , Project Scheduling , and Bin Packing . His work often involves developing exact and metaheuristic algorithms for complex resource-constrained and logistics problems. The recent publications reflect a consistent trend in cutting and packing problems , project scheduling , and metaheuristic development such as GRASP, VNS, and path relinking. These works span applications in container loading, strip packing, and berth allocation, demonstrating both theoretical depth and practical relevance in industrial and logistical settings. He has collaborated extensively with researchers such as Ramon Alvarez-Valdes and Francisco Parreño, leading to numerous joint publications in leading journals like European Journal of Operational Research and Computers & Operations Research . No scientific awards or student advisees are listed in the available data. He has advised on or conducted research involving algorithm design for timetabling, pallet loading, and job-shop scheduling, particularly in industrial contexts such as glass manufacturing and airport operations.

• STEM Education
• Student Engagement
• Curriculum Development
• +۳ مورد دیگر

Darryl Morgan is a Senior Lecturer at the Faculty of Computing, Engineering and Science, focusing on pedagogical innovation and student engagement in STEM and Built Environment education. His role as Head of Learning, Teaching and Student Experience underscores his leadership in enhancing educational experiences through research-driven strategies.

• mathematics
• Modeling and simulation
• University didactics

Georg Gutenbrunner serves as Professor and Scientific Director of the Institute for University Didactics (IHD) at Ulm University of Applied Sciences, where he also functions as Timetable Planner. His primary institutional affiliation centers on Faculty T, with teaching responsibilities spanning multiple engineering programs. His research focuses on mathematics education , modeling and simulation methodologies , and university didactics . This interdisciplinary work bridges theoretical mathematics with practical applications in engineering education, particularly through curriculum development for technical degree programs. As Scientific Director of the Institute for University Didactics, he leads initiatives to enhance teaching methodologies across the institution. His operational role as Timetable Planner demonstrates administrative engagement with academic scheduling systems. Responsible for recognition of mathematical achievements from external degree programs for Faculty T students Supervises seminar papers in the Computational Science and Engineering program Contact information shows active institutional presence with office in Room Q225 at Albert-Einstein-Allee 53-55, Ulm, Germany.

Laëtitia JOURDANمشاهده پروفایل

استاد

• Combinatorial Optimization
• Multi-objective Optimization
• Data Mining
• +۳ مورد دیگر

Professor Laëtitia JOURDAN is affiliated with the University of Lille , where she works in the College of Science and Technology within the Department of Computer Science . She leads the ORKAD team at the CRIStAL laboratory (UMR 9189). Her research focuses on synergies between combinatorial optimization and knowledge extraction , aiming to enhance optimization methods through domain knowledge while solving complex knowledge extraction problems using operational research techniques. Her work includes both mono-objective and multi-objective optimization approaches, with applications in software development and data science. Recent publications highlight her expertise in evolutionary algorithms for multiobjective scheduling problems and biomedical data analysis for lung cancer detection through exhaled breath profiling. As a faculty member, her work bridges theoretical research in automated machine learning with practical implementations in optimization software tools.

• Public Transportation Optimization
• Electric Vehicle Scheduling
• Operations Research
• +۳ مورد دیگر

Dr. Marcel van Kooten Niekerk serves as an Assistant Professor in the Department of Information and Computing Sciences within the Faculty of Science at Utrecht University. His academic appointment focuses on the Simulation of Complex Systems subgroup, where he applies computational methods to solve challenging transportation problems. He also maintains a professional connection with the transportation industry as a Consultant Logistics and Innovation at Qbuzz BV, demonstrating his commitment to bridging academic research with practical applications in public transport. Van Kooten Niekerk's research spans two primary domains: transportation optimization and theoretical computer science. His more recent work centers on public transportation systems, particularly focusing on the integration of electric vehicles into existing public transit networks. His expertise encompasses complex scheduling challenges including electric bus operations, platform assignments across multiple stations, and the integration of timetabling with vehicle scheduling. Earlier in his career, he made significant contributions to theoretical computer science, particularly in graph theory and combinatorial optimization problems such as partitioning graphs into triangles. His publication record reveals a clear evolution from theoretical computer science toward applied transportation research, with a growing emphasis on sustainability. The most recent publications demonstrate sophisticated approaches to handling uncertainty in electric bus operations, optimizing platform assignments across multiple bus stations in Utrecht, and developing comprehensive frameworks for reliable and sustainable public transport systems. His work consistently applies operations research methodologies, particularly integer linear programming and stochastic optimization techniques, to solve real-world transportation challenges. Van Kooten Niekerk has established himself as a researcher who effectively bridges theoretical computer science with practical transportation applications. His work has gained significant attention, with some publications accumulating over 100 citations and reader captures, indicating substantial impact in the transportation research community. His doctoral thesis on optimizing for reliable and sustainable public transport represents a comprehensive contribution to the field of electric vehicle integration in public transportation systems.

Ivana Kuzmanović Ivičićمشاهده پروفایل

استادیار

• Applied Mathematics
• Numerical Linear Algebra
• Matrix Equations
• +۲ مورد دیگر

Ivana Kuzmanović Ivičić is an Assistant Professor at the School of Applied Mathematics and Informatics, Josip Juraj Strossmayer University of Osijek. Her academic roles include teaching undergraduate courses in computational thinking, linear optimization, and mathematics education methodology. She currently serves as President (2025–present) and previously as Vice President (2021-2025) of the Udruga matematičara Osijek (Association of Mathematicians Osijek). Education: PhD in Mathematics, University of Zagreb (2012) BSc in Mathematics and Computer Science, University of Osijek (2005) Her research focuses on applied mathematics with specialization in numerical linear algebra, matrix equations, and perturbation theory. She develops computational methods for mechanical systems stability analysis, damping optimization, and eigenvalue problems. Her work bridges theoretical mathematics with engineering applications in vibration control and system dynamics. Publications demonstrate consistent focus on matrix perturbation theory, gyroscopic systems analysis, and computational optimization methods. Recent work explores stability bounds in mechanical systems while earlier publications address mathematical education and linear algebra applications. Research consistently appears in numerical analysis and computational mathematics journals. Research Projects: Vibration Reduction in Mechanical Systems (Croatian Science Foundation, 2020-2023) Optimization of Parameter Dependent Mechanical Systems (Croatian Science Foundation, 2015-2019) Nonlinear Parameter Estimation in Mathematical Models (Ministry of Science, 2007-2013) She has supervised 18 undergraduate theses covering topics in numerical methods, matrix theory, mathematical education, and computational tools. Regularly participates in international conferences on numerical analysis and maintains collaborations with European research institutions.

• Quality Management
• Supply Chain Management
• Business Economics
• +۵ مورد دیگر

Dr. Sandra Milunović Koprivica is an Associate Professor at the Department of Social and Human Sciences, Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. With over two decades of academic experience, she specializes in quality management, supply chain systems, and business economics. She teaches across undergraduate, master's, and doctoral programs, delivering courses in Quality Management, Engineering Economic Analysis, Supply Chain Management, and Integrated Quality Management. Her educational journey includes: B.Sc. in Industrial Management (2002, Technical Faculty in Čačak) M.Sc. in Quality Management (2005, Technical Faculty in Čačak) Ph.D. in Quality Management (2013, Faculty of Organizational Sciences, University of Belgrade) Dr. Milunović Koprivica's research primarily focuses on quality management systems and their application in manufacturing industries, with particular emphasis on uncertainty modeling. She has made significant contributions to biomass utilization for energy production, exploring the techno-economic aspects of converting agricultural waste into sustainable energy sources. Her work bridges theoretical frameworks with practical industrial applications, especially in conditions of uncertainty. Analysis of her recent publications reveals an evolving research trajectory that maintains core expertise in quality management while increasingly incorporating computational methods. Her work demonstrates a strong interdisciplinary approach connecting engineering principles with business management and environmental sustainability. Recent publications span from FMEA methods in process quality management to applications of optimization algorithms and natural language processing. Her scholarly impact is evident through her extensive publication record: Over 90 published works including conference papers and journal articles 8 publications in journals indexed in the Science Citation Index Co-author of 2 monographs Active participation in numerous international conferences Dr. Milunović Koprivica has served as a researcher on five projects funded by the Ministry of Science and Environmental Protection of Serbia, covering areas from risk management systems to biomass utilization. She has also participated in quality management system implementation projects as a consultant, holding certificates as a quality management system assessor from Nigel Bauer and AFNOR. While specific laboratory affiliations aren't detailed, her research collaborations with colleagues like Š. Ćurčić, O. Ristić, and A. Marić indicate active participation in interdisciplinary research teams within the Faculty of Technical Sciences.