جست‌وجوی استاد و پژوهشگر

Michele Cosciaمشاهده پروفایل

دانشیار

• Network Science
• Complex Networks
• Digital Humanities
• +۱۰ مورد دیگر

Michele Coscia is an Associate Professor in the Department of Computer Science at the IT University of Copenhagen (ITU), where he conducts research at the intersection of network science, digital humanities, and data analytics. He leads the NERDS research group and supervises PhD students and postdoctoral researchers working on financial crime detection, archaeological networks, and work environment modeling. PhD in Computer Science, University of Pisa (2012) Former researcher at the Center for International Development (CID), Harvard University (6 years) Visiting researcher at Barabási Lab, Northeastern University His research focuses on developing and applying network science methodologies such as noise-corrected backboning , node attribute analysis , and network variance to study complex systems. His work spans diverse domains including: Archaeology : Inferring social and biological relationships from material culture at Neolithic sites like Çatalhöyük. Cultural Analytics : Mapping Italian music networks, analyzing Wikipedia’s gender bias, and studying ideological polarization on social media. Social Media Dynamics : Investigating meritocracy vs. topocracy, intolerance feedback loops, and information virality on platforms like Reddit and Twitter. Sports Analytics : Analyzing predictability trends in team sports and the impact of economic systems on league competitiveness. His publications appear in high-impact journals such as Science Advances , EPJ Data Science , and Applied Network Science . He is the author of The Atlas for the Aspiring Network Scientist , a comprehensive open-access textbook now in its second edition, which covers graph theory, machine learning on graphs, and statistical foundations of network analysis. Recent trends in his work show a growing emphasis on interdisciplinary applications of network science, particularly in archaeology and cultural studies, often in collaboration with institutions such as Aarhus University and the National Research Center for Work Environment. His research consistently promotes open science, with datasets and code publicly shared. Co-PI on a Villum Synergy project applying network analysis to Roman Empire archaeological data Active contributor to the CUDAN (Cultural Data Analytics) community Developing methods for uncertain and incomplete network data Michele Coscia’s work demonstrates a strong commitment to methodological innovation and real-world impact across the humanities, social sciences, and computational domains.

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.

Gerth Stølting Brodalمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Computational Geometry
• +۶ مورد دیگر

Gerth Stølting Brodal is a Professor in the Department of Computer Science at Aarhus University, Denmark, holding this position since January 2016. Previously, he served as an Associate Professor (tenured) at the same department from 2004 to 2015. His career includes a PostDoc at the Max-Planck-Institute for Computer Science in Saarbrücken, Germany (1997-1998) and long-term affiliations with research centers BRICS (1998-2005) and MADALGO (2007-2017). Education: PhD in Computer Science, Aarhus University (1997). Thesis: "Worst Case Efficient Data Structures". Research Focus: Brodal specializes in the design and analysis of algorithms and data structures. His work spans fundamental data structures (dictionaries, priority queues, persistent structures), computational geometry, graph/string algorithms, I/O-efficient and cache-oblivious methods, algorithm engineering, and computational biology. He is renowned for worst-case efficient solutions and external memory algorithm contributions, with a fingerprint emphasizing data structures (100%), worst-case analysis (42%), and I/O efficiency (27%). Recent Publication Trends: His 2024-2025 output reveals sustained innovation in advanced data structures—dynamic convex hulls, binary search trees with finger search capabilities, strict Fibonacci heaps, and cache-oblivious selection algorithms—demonstrating theoretical rigor with practical engineering applications in massive data processing. Academic Leadership: Brodal has supervised PhD students (evidenced by one thesis in his output) and contributed to major collaborative initiatives. His 141 research outputs include journal articles, conference papers, and book chapters, reflecting deep engagement with algorithmic theory and its real-world implementations.

• Theoretical Computer Science
• Algorithms
• Computational Complexity
• +۴ مورد دیگر

Nutan Limaye is a Professor at the Department of Theoretical Computer Science , IT University of Copenhagen , specializing in Algorithms , Computational Complexity , and Algebraic Circuits . She actively contributes to research on polynomial complexity, quantum computation, and lower bound techniques. Key Research Areas : Algebraic Circuit Complexity, Polynomial Computation, Graph Isomorphism, Boolean Satisfiability Current Projects : FLows : Formula complexity and lower bounds (2024-2026) DIREC: OnlineAlgo : Digital research initiatives (2022-2025) BARC2 : Basic Algorithms Research Copenhagen (2024-2029) Scientific Recognition includes the FOCS Best Paper Award (2022) . Her work frequently appears in top conferences like CCC , FSTTCS , and SIGACT News , with recent collaborations in Denmark and international institutions. She contributes to public understanding through media appearances on topics like basic computer science research and BARC's initiatives .

• Algorithms
• Graph Theory
• Theoretical Computer Science
• +۳ مورد دیگر

Paloma Thomé de Lima is a Lecturer in Theoretical Computer Science at IT University of Copenhagen. Her research focuses on graph theory, algorithms, and computational complexity, particularly in chordal graphs, induced subgraphs, and graph modification problems. Her work includes studies on bounded degree constraints, matching numbers, and polynomial time algorithms. Recent publications address problems in claw-free graphs, min-cut optimization, and structural graph theory. She has received the Best Paper Award at IPEC 2022 for collaborative research. Current projects include Unifying Theories for Graph Modification Problems funded by Danmarks Frie Forskningsfond (2023–2027).

Roberto Naboniمشاهده پروفایل

دانشیار

• Additive Manufacturing
• Sustainable Construction
• Robotic Assembly
• +۴ مورد دیگر

Roberto Naboni is an Associate Professor and Head of Centre at the SDU CREATE and a member of the SDU Climate Cluster . Affiliated with the Department of Technology and Innovation at the University of Southern Denmark, his work bridges advanced digital design, robotic fabrication, and sustainable construction methodologies. Research Interests include: Additive manufacturing in architecture and construction Low-carbon concrete and timber structures Algorithmic design and computational methods Space architecture applications (e.g., lunar habitats) Behavioral robotics for construction automation Material innovation for climate resilience Scientific Awards Villum Young Investigator Grant (2022) Teaching & Supervision spans courses on architectural geometry, digital fabrication, and sustainable materials. He leads PhD projects like Bio-Inspired Behavioural Additive Construction and collaborates on interdisciplinary initiatives such as FSSoV: Football as Health and Welfare Innovator . His research output includes 76 publications and active participation in 3 projects focused on adaptive robotics and sustainable construction systems.

• Computational Chemistry
• Catalysis
• Quantum Chemistry
• +۳ مورد دیگر

Julius Johannes Seumer is a Postdoctoral Research Fellow in the Department of Chemistry at the Faculty of Science, University of Copenhagen. His research focuses on computational approaches to catalyst design and chemical synthesis optimization, with expertise in quantum mechanics simulations and evolutionary algorithms. His primary research interests include computational chemistry, catalysis, quantum chemical modeling, and machine learning applications in chemical synthesis. Key areas involve regioselectivity prediction, transition metal complex analysis, nitrogen fixation catalysts, and automated synthesis planning using genetic algorithms. Analysis of his recent publications reveals strong trends in computational catalyst discovery, particularly using genetic algorithms for exploring chemical space beyond traditional libraries. His work spans organic, inorganic, and physical chemistry domains with emphasis on Morita-Baylis-Hillman reactions, C-H activation, and dinitrogen fixation. Seumer collaborates extensively with Professor Jens H. Jensen and other researchers at the University of Copenhagen, with publications appearing in high-impact journals including Angewandte Chemie , Chemical Science , and Beilstein Journal of Organic Chemistry . His computational methodologies have garnered attention across academic networks, with citations in Scopus and engagement on platforms including X (Twitter), Bluesky, and Mendeley. His work demonstrates significant interdisciplinary impact across chemistry and computational sciences.