جست‌وجوی استاد و پژوهشگر

• Supply Chain Management
• Sustainable Supply Chain Management
• Reverse Logistics
• +۱۲ مورد دیگر

Kannan Govindan is a Professor at the Department of Technology and Innovation, University of Southern Denmark (SDU), where he is affiliated with the SDU Centre for Sustainable Supply Chain Engineering, SDU Climate Cluster, and SDU SCC Elite Center CUHRE. He serves as Director of Indian Relations and leads extensive research in sustainable supply chain management, optimization, and circular economy. His work bridges academic rigor with real-world industrial applications, particularly in SMEs and green logistics. Professor, SDU Centre for Sustainable Supply Chain Engineering Professor, SDU Climate Cluster Professor, SDU SCC Elite Center CUHRE Director, Indian Relations, Department of Technology and Innovation His research interests include supply chain optimization, reverse logistics, green and circular supply chains, decision-making models, and sustainability in SMEs. He employs quantitative methods, network modeling, and AI to develop frameworks that enhance supply chain resilience and environmental performance. The recent publications reflect a strong focus on sustainable supply chain performance, circular economy integration, IoT and blockchain applications, and optimization techniques such as Lagrangian relaxation and metaheuristics. His work increasingly emphasizes digital transformation (Industry 4.0/5.0), business resilience, and the role of technology in enabling sustainable practices across industries. Highly Cited Researcher Award (2018) Best Paper Award (2018) 2018 Most Cited Paper Award (2019) Influential Paper Awards (2018) for seminal works in green supplier evaluation and reverse logistics Emerald Citations of Excellence (2017) Professor Govindan has supervised numerous research projects and PhD students, and he actively contributes to the academic community as an editor for leading journals such as Journal of Cleaner Production and Industrial Management & Data Systems . He has secured significant research grants, particularly in sustainability and circular economy initiatives, including projects like SDG Tools and DecomBlades . He teaches courses on supply chain decisions, sustainability, and circular economy, including a summer school program for engineers and business professionals. He is a key member of several research teams and centers at SDU, including the Elite Centre CUHRE, where he collaborates on interdisciplinary research integrating sustainability, education, and industrial innovation. His network spans global collaborations, particularly with institutions in India and Southeast Asia, reflecting his role in international academic relations.

Yu Jiangمشاهده پروفایل

دانشیار

• Transportation Science
• Transit Assignment
• Traffic Assignment
• +۱۳ مورد دیگر

Yu Jiang is an Associate Professor in the Department of Transportation Systems Modelling at the Technical University of Denmark (DTU), within the Department of Technology, Management and Economics. He is actively engaged in research and supervision, with a strong focus on transportation science and systems optimization. He is accepting PhD students and maintains an active research profile with numerous ongoing projects and publications. Education: PhD, The University of Hong Kong (2010–2014) His research interests include static and dynamic transit/traffic assignment, network design, infrastructure resilience and vulnerability, multi-objective optimization, and metaheuristics. These areas are central to improving urban mobility, public transport efficiency, and sustainable transportation systems. His work contributes to UN Sustainable Development Goals related to sustainable cities and responsible consumption. Recent publications (2025) reflect a strong trend in applying advanced optimization and machine learning techniques to urban transportation challenges, including traffic signal control, last-mile delivery, intermodal travel behaviour, and demand prediction across shared mobility systems. The research spans both theoretical modelling and practical case studies. Scientific Awards: No scientific awards listed in the provided text. Advising and Grants: Yu Jiang is the main supervisor for several PhD projects, including 'Development of an integrated optimisation model for operating urban transit system (SmoothTrip)', 'Crowdsourced Delivery as an Activity for Sustainable Cities', and 'Network Optimisation for Connected, Cooperative and Automated Mobility'. He is also a co-investigator in the NEMESYS project funded by the European Commission, focusing on dynamic pricing and tradable credits for emissions management. His academic activities include organizing conferences, presenting at international events, serving as a journal editor, and conducting peer reviews. Labs and Research Teams: He is part of the research network at DTU's Department of Technology, Management and Economics, collaborating on projects related to urban transit optimization, shared mobility, and sustainable freight. His work involves close collaboration with researchers from institutions such as Oxford University, NUS, and HKU, as well as international partners in ongoing research initiatives.

• Programming Languages
• Compilers
• Type Systems
• +۴ مورد دیگر

Nikolaj Hey Hinnerskov is a PhD Fellow in the Programming Languages and Theory of Computation (PLTC) section at the Department of Computer Science, University of Copenhagen. His research is embedded within DIKU's PLTC group, focusing on foundational and applied programming language systems. His core research spans: Programming Language Theory and Type Systems Compiler Design for Array-Based Languages Automatic Differentiation Techniques GPU-Accelerated Algorithm Development Rank-Polymorphic Function Inference Time Series Analysis Optimization Recent work demonstrates a strong convergence of programming language theory and high-performance computing, particularly in advancing compiler techniques for functional array languages like Futhark and optimizing scientific computations on GPUs. His publications address critical challenges in type inference, automatic differentiation, and parallel time-series decomposition. No scientific awards are documented in available sources. As a doctoral researcher, he operates under faculty supervision without independent advisees or grant leadership. His contributions align with DIKU's PLTC projects, including language design and performance optimization initiatives. He actively collaborates within the PLTC research ecosystem, contributing to GPU-based computational methods and programming language innovations alongside DIKU faculty and international researchers.

Jakob Nordströmمشاهده پروفایل

استاد

• Computer Science
• Algorithms and Complexity
• Proof Complexity
• +۵ مورد دیگر

Jakob Nordström is a full-time Professor at the Department of Computer Science , University of Copenhagen , and holds a part-time affiliation with Lund University since 2020. His research lies at the intersection of theoretical computer science , proof complexity , and combinatorial optimization . His work focuses on SAT solving , Pseudo-Boolean optimization , and formal verification of algorithms. Recent research includes polynomial calculus lower bounds , dynamic programming certification , and MIP-based presolve techniques . Publications span journals like the Journal of the ACM and conferences including SAT and CADE . Scientific awards include the STOC '06 Best Student Paper Award and the Ackermann Award 2009 . He is a member of the Young Academy of Sweden (since 2018). Research funding comes from the Independent Research Fund Denmark and the Swedish Research Council . He has contributed to proof complexity , resolution trade-offs , and algebraic reasoning in combinatorial search. His work bridges theoretical lower bounds with practical Pseudo-Boolean solvers and certified algorithms .

• Operations Research
• Logistics Optimization
• Heuristic Algorithms
• +۳ مورد دیگر

Associate Professor Dario Pacino is affiliated with the Technical University of Denmark (DTU), specifically within the Department of Technology, Management and Economics under the Operations Research Section. His research focuses on optimization challenges in logistics and transportation systems, including container stowage planning, berth allocation, and the application of AI techniques like reinforcement learning. He holds a position at DTU's Management Science Division and is based in Lyngby, Denmark. His work emphasizes heuristic and metaheuristic algorithms for solving complex logistics problems. Notable areas include Roll-on/Roll-off (RoRo) ship stowage planning, dynamic berth allocation, and discrete event simulation for healthcare logistics. He has contributed to mathematical models addressing draft limits in shipping and stochastic fleet optimization for urban mobility. Publications from 2022 onward highlight advancements in reinforcement learning integration with traditional operations research methods, demonstrating a trend toward AI-driven logistics solutions. His work bridges theoretical optimization with practical applications in maritime and healthcare sectors. No scientific awards are explicitly listed in the provided text. His advising and grants sections remain unspecified, though his research collaborations are evident through multi-institutional projects. He is part of the Operations Research Section's research team, focusing on decision support systems and optimization under uncertainty.

Rune Møller Jensenمشاهده پروفایل

دانشیار

• Container Vessel Stowage Planning
• Operations Research
• Optimization Methods (Metaheuristics, Constraint Programming)
• +۳ مورد دیگر

Rune Møller Jensen is an Associate Professor in Data Science and Head of The Maritime Hub at the IT University of Copenhagen. He specializes in container vessel stowage planning optimization, with expertise in metaheuristics, constraint programming, and mathematical programming. His work bridges academia and industry through projects like churn prediction and AIS-based ETA forecasting. He co-founded Sealytix, a leading stowage analytics firm, and previously led Optivation until 2022. Jensen holds awards including the Hede Nielsen Prize (2005) and The McKinsey Award (1998). Education: Studied Symbolic AI at Carnegie Mellon University (CMU). Research focuses on optimizing maritime logistics, energy-efficient transportation, and decision support systems for liner shipping. Key projects include Greenship (2014-2016), REALCAP (2016-2018), and BAYSTOW (2008-2012). Media engagements include discussions on AI ethics and industry collaboration. His research portfolio spans 86 publications and 10+ projects, emphasizing optimization algorithms and real-world maritime applications. As head of The Maritime Hub, he supports emerging researchers through interdisciplinary initiatives.

• Chemical Informatics
• Computational Chemistry
• Graph Theory
• +۳ مورد دیگر

Prof. Daniel Merkle is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark. His research focuses on computational systems chemistry, algorithmic methods for chemical reaction networks, and graph-based approaches in computational biology. He is actively involved in interdisciplinary projects addressing microbiome-driven diseases and computational systems chemistry. Merkle has held leadership roles in EU-funded initiatives and international research networks, including the COST Actions on complex chemical systems and origins of life. He contributes to teaching committees and organizes international conferences like the Dagstuhl Seminar on Algorithmic Cheminformatics. His research interests span chemical graph rewriting, pathway realizability, reaction database curation, and algorithmic design for biochemical systems. Recent work includes advancements in synthetic chemistry frameworks (e.g., ChemReservoir), efficient extraction of reaction rules (SynTemp), and formal modeling of unbalanced chemical reactions using ITS Graphs. Merkle’s projects, such as MATOMIC and TACsy, address microbial community metabolism and train computational systems chemists. He has published over 110 research outputs and actively engages in peer review and editorial roles. Key collaborations include work with Flamm, Stadler, and international research teams on computational methods for chemical systems. His contributions to open-source tools and algorithmic frameworks have advanced both theoretical and applied aspects of systems chemistry.

Marco Chiarandiniمشاهده پروفایل

دانشیار

• Operations Research
• Optimization Algorithms
• Integer Programming
• +۱۰ مورد دیگر

Marco Chiarandini is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), with a secondary affiliation to the SDU Climate Cluster. His research focuses on Operations Research, Optimization Algorithms, and their applications in domains such as transportation, healthcare, and education. He has led or contributed to projects addressing dynamic traffic estimation, dementia care app design, and sustainable software development. Chiarandini has supervised students including P. Tampakis and C. McCarthy, and his work has been featured in interdisciplinary collaborations with institutions globally. His recent articles explore topics like goal-scoring prediction in football and urban traffic modeling, reflecting his expertise in data science and algorithmic design. His academic contributions span over 50 publications, emphasizing methodological advancements in optimization and heuristic algorithms. He actively participates in conferences and peer review, and has coordinated EU-funded projects like Data Science for University Management (2019–2023). Chiarandini’s teaching includes courses on linear programming and metaheuristics, integrating practical applications with theoretical foundations.

Rolf Fagerbergمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Computational Biology
• +۷ مورد دیگر

Rolf Fagerberg is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU). His research centers on algorithms, data structures, and their applications in computational biology and cheminformatics. His research interests include: Algorithms and data structures, particularly dynamic and geometric data structures Graph theory with emphasis on subgraphs, Yao graphs, and hypergraphs Algorithmic cheminformatics and modeling of chemical reaction networks Computational biology, including metabolic pathway analysis Theoretical computer science and discrete mathematics Recent publications highlight a strong trend toward interdisciplinary research combining computer science with chemistry and biology, particularly in modeling chemical reaction networks using hypergraphs and mixed-integer linear programming. His work also includes algorithmic solutions for palindromic subsequence problems and efficient extraction of reaction rules from large databases, reflecting a blend of theoretical and applied algorithm design. Rolf Fagerberg has served as senior coordinator on multiple research projects, including 'Algorithmic Cheminformatics' and 'Fundamental Data Structures', funded by the Danish Ministry of Higher Education and Research. He has also contributed to peer review and editorial work for major conferences such as the ACM Symposium on Parallelism in Algorithms and Architectures and the International Symposium on Experimental Algorithms. He has supervised PhD students and is actively involved in academic service, including membership in assessment committees at Aarhus University and IT University of Copenhagen. His research has received media attention, including coverage of a 'mathematical breakthrough' and applications in understanding intestinal systems in obesity.