جست‌وجوی استاد و پژوهشگر

Jan Østergaardمشاهده پروفایل

استاد

• AI and Sound
• Acoustic Signal Processing
• Information Theory
• +۴ مورد دیگر

Jan Østergaard is a Full Professor in Information Theory and Signal Processing at Aalborg University's Department of Electronic Systems. He leads the AI and Sound research section and directs the CASPR center. His expertise spans AI-driven acoustic signal processing, information theory, and EEG signal analysis. Østergaard holds a M.Sc. from Aalborg University and a PhD (cum laude) from Delft University of Technology. Major awards include the Danish Young Researcher’s Award and a EURASIP Best Thesis honor. His work focuses on speech enhancement, sound zone technologies, and neural tracking of auditory attention. Recent research emphasizes low-latency speech transmission, deep learning for sound field control, and robust voice activity detection. He serves on editorial boards and national committees, advancing Denmark’s sound technology initiatives. Education: M.Sc. (Aalborg, 1999), PhD (Delft, 2007) Research interests emphasize practical AI applications in sound systems, including hearing aid improvements, data-efficient acoustic modeling, and feedback control in networked systems. Over 210 publications and 17 active projects reflect his interdisciplinary impact across academia and industry.

Aage Hill-Madsenمشاهده پروفایل

دانشیار

• Translation Studies
• Medical Communication
• Systemic Functional Grammar
• +۵ مورد دیگر

Aage Hill-Madsen is an Associate Professor at the Department of Culture and Learning, Aalborg University (Denmark), affiliated with the Communication, Language, and Discourse (CLD) research unit. His work focuses on translation studies, medical communication, and systemic-functional linguistics. He holds a Cand.mag. et ling.merc. and a PhD in English linguistics. Research Interests: Translation theories (especially intralingual translation) Medical terminology simplification and communication Systemic-functional grammar applications Legitimation Code Theory in educational contexts Genre analysis of specialized texts Semiotic approaches to knowledge transmission Recent Publications Trends: His 2024-2025 work emphasizes medical translation between technical and lay audiences, with studies on EPAR summaries, patient information leaflets, and historical East-West medical terminology exchanges. He combines functionalist translation theory with systemic-functional frameworks to analyze textual transformations. Grants & Projects: Participated in the 2024-ongoing project Udvikling af kommunikative kompetencer gennem frivilligt brobygningsarbejde i NGO’en Social Sundhed , exploring communication skills through NGO activities. Academic Engagement: Active peer reviewer for journals like Globe and Across Languages and Cultures , with conference presentations on intralingual translation strategies and medical text accessibility.

Kunihiko Kanekoمشاهده پروفایل

استاد

• Theoretical Biophysics
• Complex Systems
• Chaos
• +۶ مورد دیگر

Kunihiko Kaneko is a Professor at the Niels Bohr Institute, University of Copenhagen, with a distinguished career in theoretical biophysics and complex systems. He received his PhD and MSc in Physics from the University of Tokyo, and has held leadership roles at the Universal Biology Institute and Center for Complex Systems Biology. PhD Physics, 1984 - University of Tokyo MSc Physics, 1981 - University of Tokyo His research spans five primary areas: Universal Biology, Evolutionary Constraints, Ecosystem Dynamics, Neural Cognition, and Universal Anthropology. He has published extensively on multi-level consistency principles, dimensional reduction in biological systems, and reciprocity between robustness and plasticity across scales. Recent publications show strong focus on microbial ecosystems (2025), evolutionary game theory (2025), neural modular architectures (2024), and dimensional reduction in cellular systems (2024). His work bridges physics and biology through dynamical systems theory applied to diverse phenomena from protocells to human societies.

Mads Leth Jakobsenمشاهده پروفایل

دانشیار

• Public Leadership
• Leadership Development
• Bureaucracy and Debureaucratization
• +۴ مورد دیگر

Mads Leth Jakobsen is an Associate Professor at the Department of Political Science , Aarhus University, specializing in Public Leadership , Leadership Development , and Bureaucracy and Debureaucratization . He serves as a member of the King Frederik Center for Public Leadership management team, focusing on leadership for public value creation and handling complex social challenges like the climate crisis. Academic Rank: Associate Professor Primary Research: Public Leadership, Distributed Leadership, Climate Governance Teaching: Public Leadership and Governance on political science programs Key Projects: Public Value Leadership (2022), Distributed Leadership (2012-2016) His research explores paradox leadership , organizational responses to climate challenges, and leadership credibility. Recent publications examine municipal climate strategies, bureaucratic dynamics, and leadership development frameworks. He emphasizes the interplay between leadership practices and employee outcomes in public sector organizations. Scientific awards and student supervision details are not listed in the available information. His articles highlight a strong focus on reconciling performance regimes with organizational learning, leadership credibility, and innovative governance models in public sector contexts.

• Computer Vision
• Image Analysis
• Machine Learning
• +۵ مورد دیگر

Serge Belongie is a Professor at the Department of Computer Science (DIKU) at the University of Copenhagen, where he holds dual affiliations with the Pioneer AI research section and the Image Analysis, Computational Modelling, and Geometry section. His academic position places him at the forefront of interdisciplinary research connecting computer vision with language models, geospatial analysis, and cultural understanding. Professor Belongie's research program encompasses several critical domains in modern artificial intelligence: Advanced computer vision and image analysis techniques Vision-language model integration and multimodal systems 3D point cloud processing and semantic segmentation Geospatial representation learning for environmental applications Fine-grained object recognition and detection Cultural context understanding in AI systems His recent publication record reveals a sophisticated trajectory toward developing precise control mechanisms for vision-language models, with applications spanning forensic analysis, cultural heritage preservation, and social media understanding. The research demonstrates increasing sophistication in handling cultural context and enabling fine-grained manipulation of visual content through natural language interfaces. Professor Belongie maintains an active research group producing significant scholarly output, with over 280 research publications documented in his academic profile. His work is supported by research funding that enables cutting-edge exploration in multimodal AI systems with practical societal impact. He plays a key role in the Pioneer AI center at the University of Copenhagen, which focuses on advancing artificial intelligence through interdisciplinary collaboration and innovative research approaches that bridge theoretical computer science with real-world applications.

Kantaro Fujiwaraمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Neural Data Analysis
• Machine Learning
• +۱ مورد دیگر

Kantaro Fujiwara serves as Associate Professor at the Graduate School of Medicine, The University of Tokyo, with concurrent appointments at the International Research Center for Neurointelligence (IRCN) and the Department of Mathematical Informatics, Graduate School of Information Science and Technology. He also manages the Data Science Core infrastructure for IRCN. His academic background includes a Ph.D. in Information Science and Technology from the University of Tokyo (2008), followed by postdoctoral research at the University of Tokyo (JSPS) and University of Cambridge, then assistant professorships at Saitama University and Tokyo University of Science before joining the University of Tokyo faculty. Dr. Fujiwara's research bridges computational neuroscience and neural data analysis through mathematical modeling of neural networks, development of neural data analysis methodologies, and exploration of brain-inspired machine learning. His work extends to biological information processing with specific applications in pancreatic beta cell modeling for diabetes research, establishing connections between theoretical frameworks and experimental neuroscience. His publication record (2017-2023) reveals consistent interdisciplinary contributions applying echo state networks, recurrence analysis, and nonlinear dynamics to neural data classification, physiological signal processing, and disease modeling. These works demonstrate strong integration of computer science, neuroscience, and biomedical engineering methodologies to solve complex neurobiological problems. As Data Science Core Manager at IRCN, he oversees computational infrastructure and software resources that enable advanced neurointelligence research across the University of Tokyo ecosystem, providing critical support for data-intensive neuroscience projects.

Rasmus Paghمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Big Data
• +۷ مورد دیگر

Rasmus Pagh is a Professor at the Department of Computer Science, University of Copenhagen, specializing in algorithms and complexity. His career includes a 2002 PhD from Aarhus University under Peter Bro Miltersen and a tenure at IT University of Copenhagen until 2020. He leads theoretical research with practical applications in big data, databases, and modern computer architecture parallelism. His research interests span algorithms, data structures, and privacy-preserving computing. Recent work includes the ERC-funded project on Scalable Similarity Search and contributions to the BARC center for basic algorithms research. He has collaborated with Google Research (2019-2020) and focuses on theoretical foundations with real-world impact. Key research trends in his 2023-2024 publications include privacy-preserving data analysis probabilistic data structures distributed secure computation noise-robust coding hashing efficiency continual privacy mechanisms Scientific recognition includes 2024 ACM Fellowship ERC grant leadership multiple top-tier conference publications

Luis Emilio Bruniمشاهده پروفایل

دانشیار

• Narrative Cognition
• Extended Reality
• Cognitive Processes
• +۶ مورد دیگر

Luis Emilio Bruni is an Associate Professor at Aalborg University’s Department of Architecture, Design and Media Technology, within The Technical Faculty of IT and Design. He leads the Media Cognition and Interactive Systems (MeCIS) research group and coordinates the Master of Science in Medialogy. Bruni is also the founder and director of the Augmented Cognition Lab, focusing on perception, cognition, and immersive technologies. His academic roles include PI on multiple interdisciplinary projects and board memberships in international associations like the Nordic Association for Semiotic Studies (2011–2017) and the International Society for Biosemiotic Studies (founding member, 2005). Academically, Bruni holds a Ph.D. in Molecular Biology and Theory of Science (University of Copenhagen), M.Sc. in International and Global Relations (Universidad Central de Venezuela), and B.Sc. in Environmental Engineering (Pennsylvania State University). His research spans narrative cognition, extended reality, biosemiotics, and the interplay between technology, cognition, and culture. He has conducted projects on neurocinematic analysis, interactive storytelling, and the psychological impact of digital media. Key research contributions include studies on EEG responses to branded advertising, functional connectivity in psychiatric disorders, and the role of narrative in immersive technologies. Bruni’s work bridges cognitive science, computer science, and semiotics, with applications in healthcare (e.g., pediatric counseling tools) and cultural engagement (e.g., citizen curation systems). Over 80+ publications and active participation in conferences and media discussions highlight his interdisciplinary impact.

Kohei Nakajimaمشاهده پروفایل

دانشیار

• Soft Robotics
• Physical Reservoir Computing
• Physical Deep Learning
• +۵ مورد دیگر

Kohei Nakajima is an Associate Professor at the Department of Intelligent Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo. He holds concurrent positions at the Department of Creative Informatics and the Next Generation Artificial Intelligence Research Center (AI Center). As an Endowed Chair in Advanced Artificial Intelligence Education, he leads the Physical Intelligence Lab, which focuses on the intersection of soft robotics, nonlinear dynamics, and physical computing. His research interests center on Physical Reservoir Computing (PRC), a paradigm that exploits the natural dynamics of physical systems for computation, with applications in soft robotics, spintronics, and quantum machine learning. Nakajima's work demonstrates how physical systems can inherently process information without traditional digital computation, leveraging phenomena like chaos, bifurcations, and embodied intelligence. Nakajima's publications reveal a strong focus on understanding how physical systems can perform computational tasks. His recent work spans from biological applications (jellyfish cyborgs, ostrich-inspired robotics) to fundamental theoretical advances in reservoir computing. The research demonstrates how physical phenomena can be harnessed for information processing, with implications for energy-efficient computing and novel robotic control paradigms. As the organizer of the Reservoir Computing Seminar, Nakajima has built a vibrant research community exploring the nature of information processing across disciplines. His lab actively recruits graduate students and postdocs, indicating strong research momentum and institutional support for his work in physical intelligence.

Eva Erikssonمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Participatory Design
• Interaction Design
• +۷ مورد دیگر

Eva Eriksson is an Associate Professor at Aarhus University, affiliated with the School of Communication and Culture and the Department of Digital Design and Information Studies. Her work bridges design, technology, and social values, focusing on participatory and human-centered approaches. Her research interests center on Human-Computer Interaction (HCI) , Participatory Design , and Design for Sustainability . She explores how co-design methods can empower youth, support children with learning differences like dyscalculia, and integrate more-than-human perspectives—considering non-human actors such as nature and technology—in design processes. Her work emphasizes ethical, inclusive, and reflective design practices. The recent publications highlight a strong trend in co-design with youth , XR and AR for education , sustainable technology , and methodological innovation in design research . These works span case studies, scoping reviews, and conceptual provocations, often published in top-tier venues like CHI and Interacting with Computers . Honourable Mention Award at CHI 2020 Honorable Mention, Design Space, CHI 2021 Most Cited Paper of 2021, International Journal of Child-Computer Interaction Eva Eriksson leads and contributes to externally funded research projects such as COMPILE (focused on dyscalculia and AR) and MOVA (on more-than-human values in design education), supported by the Independent Research Fund Denmark and Erasmus+. She supervises student projects and teaches courses such as Co-design and Bachelor Project . She also serves on international PhD examination and evaluation panels, demonstrating her active role in the global academic community. She is a core member of the Center for Computational Thinking & Design (CCTD) , a multidisciplinary research center at Aarhus University that fosters innovation in design, education, and technology.

Emilia Mendesمشاهده پروفایل

استاد

• Software Engineering
• Empirical Software Engineering
• Human-Centric Software Engineering
• +۱۲ مورد دیگر

Emilia Mendes is a Full Professor in the Department of Electrical and Computer Engineering at Aarhus University . Her research focuses on Empirical Software Engineering , particularly human-centric approaches, evidence-based decision-making, and the application of machine learning and statistical techniques in software development. Current research themes: Human-Centric Software Engineering, Evidence-Based Research, Statistical/Machine-Learning Techniques, and Value-Based Software Engineering. Developed tools for team climate forecasting, capability measurement, and value-based decision-making. Research Trends: Her work bridges software engineering with psychology (personality traits, team dynamics), machine learning (effort estimation, dementia prognosis), and value-based frameworks for decision-making. She emphasizes industrial applications, including agile methodologies, cross-company predictions, and Bayesian network modeling. Scientific Impact & Awards: 10,018 citations, h-index 58. Ranked #32 in Empirical Software Engineering Scholars (Google Scholar). Ranked #20 in Top Computer Science Scientists in Sweden (2023). Top 2% scientist in the world (2019, 2020, 2022; only female in Sweden for SE in 2022. Nine best paper awards at international conferences. Editorial board member: Information and Software Technology , ACM Computing Surveys , former roles at IEEE Transactions on Software Engineering and others. Grants & Leadership: Awarded €11.921.603 in research grants. Held leadership roles as General Chair (EASE 2017), PC Co-Chair (EASE 2012, ESEM 2012), and active participant in 200+ academic events.

Arijit Khanمشاهده پروفایل

دانشیار

• Graph Neural Networks
• Blockchain
• Data Management
• +۵ مورد دیگر

Arijit Khan is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark. He leads the Data Engineering, Science and Systems group and is affiliated with the Technical Faculty of IT and Design. His research focuses on Graph Neural Networks , Blockchain , Data Management , and AI interpretability . He is the Principal Investigator (PI) of a major project on Data Management, Fundamental Algorithms, and Machine Learning for Emerging Problems in Large Networks (2022–2027). Research Interests : Graph Data Management & Machine Learning Blockchain Transaction Analysis Large Language Model + Knowledge Graph Synergies Healthcare AI (e.g., ICU glucose prediction) Explainable AI for Graph Neural Networks Research Trends : His publications emphasize neuro-symbolic systems , uncertain graph analysis , and AI-driven blockchain insights . Recent work bridges large language models with knowledge graphs and explores GPU performance optimization via shader code analysis. Awards & Grants : No explicit awards listed, but his active research grants include a 5-year project on large network analysis with interdisciplinary applications in life and health sciences. Funding emphasizes algorithmic innovation and data science integration. Labs/Teams : Head of the Data Engineering, Science and Systems research group, focusing on AI for societal impact ('AI for the People') and scalable graph data systems. Collaborations span blockchain analytics, healthcare informatics, and GPU architecture design.

Andreas Bjerre-Nielsenمشاهده پروفایل

دانشیار

• Educational Public Policy
• AI for Public Policy
• Social Networks
• +۶ مورد دیگر

Andreas Bjerre-Nielsen is an Associate Professor at the Department of Economics and Copenhagen Center for Social Data Science (SODAS) within the Faculty of Social Sciences at the University of Copenhagen. His work bridges economics and data science to analyze education-related behavior and policies. Research Focus: School choice, digital technology in education, predictive analytics for interventions, and social network effects. Methodology: Combines econometrics with machine learning techniques to evaluate policy impacts. Research Trends: Recent publications emphasize algorithmic fairness in college admissions, socioeconomic impacts of school boundary policies, and behavioral insights from large-scale datasets. His 2025 Scientific Reports study reveals nation-scale social network dynamics. Awards and Grants: Tietgen Prize (2021) for young social science researchers 2024: Independent Research Fund Denmark grant for 'Coded Clues' project 2023: Major grant for school choice research Collaborations: Works with Danish Ministry of Children and Education through UDDanKvant unit, and collaborates with multidisciplinary researchers including Sune Lehmann and David Dreyer Lassen.

Petar Popovskiمشاهده پروفایل

استاد

• Wireless Communication
• Internet of Things
• Ultra-Reliable Low Latency Communication
• +۱۲ مورد دیگر

Petar Popovski is a Professor at the Department of Electronic Systems within the Technical Faculty of IT and Design at Aalborg University, Denmark. His research focuses on next-generation wireless communication systems, with a strong emphasis on ultra-reliable low-latency communication (URLLC), Internet of Things (IoT), multiple access, and 6G technologies. He leads several high-impact research projects, including the Classique - Center for Classical Communication in the Quantum Era funded by the Danish National Research Foundation and WATER (Wireless Architectures for intelligent and Trusted connectivity in the posT-5G ERa) supported by Villum Fonden. His research interests span key areas in modern communication theory and systems, including random access , non-terrestrial networks , satellite communication , and machine learning for reliable communication . He is actively involved in advancing the integration of sensing and communication, digital twin technologies, and quantum-era classical communication frameworks. The recent publications highlight a strong trend toward deterministic and reliable access in wireless networks, integration of sensing and communication for industrial automation, and novel physical-layer techniques using reconfigurable intelligent surfaces. These works are published in top IEEE journals such as IEEE Transactions on Communications , IEEE Transactions on Haptics , and IEEE Transactions on Vehicular Technology . Award highlights include the Best Student Paper Award (2021) , recognizing his mentorship and collaborative research excellence. Prof. Popovski serves as a principal investigator (PI) and supervisor in multiple research projects, securing significant funding from national and international bodies such as the Danish National Research Foundation and the European Space Agency (ESA). He hosts visiting researchers regularly and contributes to scientific leadership through editorial roles and conference participation. He is a key figure in the Connectivity section at Aalborg University and leads cutting-edge research in future wireless systems, contributing to both theoretical foundations and practical implementations in smart infrastructure, space communication, and dependable 6G networks.

Charlotte Albrechtsenمشاهده پروفایل

مدرس

• Digital Media
• Participatory Research Methods
• Qualitative Data Analysis
• +۱۰ مورد دیگر

Charlotte Albrechtsen is an External Lecturer in the Department of Business & Management at the University of Southern Denmark, Faculty of Social Sciences. She is actively engaged in teaching, research, and editorial activities, contributing to interdisciplinary studies at the intersection of digital media, communication, and participatory research methods. Institution: University of Southern Denmark Department: Department of Business & Management (DBM) Academic Role: Lecturer Email: charal@sam.sdu.dk Her research interests center on innovative qualitative methodologies, including mobile ethnography, collaborative data analysis through gamified techniques, and the integration of generative AI in creative research practices. She explores how digital tools can enhance participatory research and democratize knowledge production. Recent publications reveal a strong trend toward blending humanities perspectives with digital technologies—such as drawing analogies between medieval monastic practices and modern prompt engineering, or using board games to involve stakeholders in data interpretation. This reflects a unique interdisciplinary approach that bridges communication theory, design, and AI literacy. Scientific recognition includes: Forbundet Kommunikation & Sprogs ph.d.-pris (2006) Forfatterlegat (2007) She has taught courses in strategic communication, research methodology, and market analysis, and has served as a peer reviewer for journals like CoDesign . Her current project, Balancing AI in EDU , investigates ethical and pedagogical implications of AI in higher education. While no formal advisees are listed, her supervisory role in teaching suggests mentorship experience. She does not appear to lead a formal lab but contributes to collaborative, participatory research networks.