جست‌وجوی استاد و پژوهشگر

Kai Zhaoمشاهده پروفایل

پژوهشگر ارشد

• Time Series Analysis
• Machine Learning
• Data Mining
• +۳ مورد دیگر

Kai Zhao is a Research Fellow in the Department of Computer Science at the Technical Faculty of IT and Design, Aalborg University, Denmark, specializing in time-series analytics and machine learning applications. Research Interests: Time Series Analysis Machine Learning Data Mining Contrastive Learning Graph Neural Networks Anomaly Detection His recent publications (2023-2025) demonstrate a cohesive focus on graph-based and contrastive learning techniques for time-series challenges, particularly addressing few-shot scenarios, multivariate forecasting, and anomaly detection in IoT contexts. Methodological innovations include dynamic graph modeling and generative contrastive frameworks. Scientific Awards: No awards mentioned in available documentation. As Principal Investigator, he led the project 'Time Series Analyse with Few-shot Learning' (2022-2023), advancing few-shot learning applications for time-series analysis. His collaborative network spans multiple institutions, evidenced by co-authorships with researchers from Aalborg University and international partners. His research integrates theoretical frameworks with practical implementations, showing strong emphasis on robustness and adaptability in real-world time-series applications.

• Second Language Acquisition
• Foreign Language Pedagogy
• Input Processing
• +۹ مورد دیگر

Teresa Cadierno is a Full Professor of Second Language Acquisition at the Department of Language and Communication , University of Southern Denmark. Her academic journey includes a Ph.D. in Second Language Acquisition and Teacher Education from the University of Illinois at Urbana-Champaign (1992), with prior degrees from the University of Georgia (1988) and the University of Oviedo (1986). She has held faculty positions at the University of Southern Denmark since 1992 and previously at Aarhus University (1993-1996). Education Ph.D., Second Language Acquisition and Teacher Education, University of Illinois at Urbana-Champaign (1992) M.A., Spanish Applied Linguistics, University of Georgia (1988) B.A., English Philology, University of Oviedo (1986) Her research focuses on Second Language Acquisition from a usage-based/cognitive linguistics perspective, particularly examining how adult learners acquire grammatical structures, process input, and express motion/placement events. Recent studies explore the role of age in English language learning in Danish primary schools, cross-linguistic influence on spatial cognition, and mobile-assisted vocabulary acquisition. Key publications include edited volumes like Linguistic Relativity in SLA (2010) and Usage-Based Perspectives on Second Language Learning (2015). Her work frequently appears in Language Learning , The Modern Language Journal , and Annual Review of Cognitive Linguistics . Scientific Awards ACTFL-MLJ Paul Pimsleur Award (1996) Fyns Stiftstidendes Research Prize (2001) She supervises Ph.D. students on topics ranging from motion event verbalization to bilingual cognition and technology-enhanced language learning. Active in project leadership, she directs the Center for Language Learning and the Second Language Research Center (SELC), securing funding from the Danish Council for Independent Research, Marie Curie ITN, and Velux Foundation.

Anne Kathrine Frandsenمشاهده پروفایل

پژوهشگر

• Universal Design
• Architecture and Physical Planning
• Healing Architecture
• +۷ مورد دیگر

Anne Kathrine Frandsen serves as Deputy Head of Department for Government Services, Head of Section, and Senior Researcher at Aalborg University's Department of Construction, Urban and Environmental Engineering within the Faculty of Engineering and Science. She leads the Section for City, Housing and Property and the research group for Universal Design, focusing on creating inclusive environments through architectural research. Education: PhD in Architecture, Drawing and Building from Royal Danish Academy – Architecture, Design, Conservation (1999-2005, graduated December 19, 2005) Architect degree from Royal Danish Academy – Architecture, Design, Conservation (1986-1994, graduated June 30, 1994) Dr. Frandsen's research spans universal design, healing architecture, visual environments, home environments, and lighting conditions. Her work bridges theoretical frameworks with practical applications to create accessible spaces for diverse populations, particularly focusing on elderly care, visual impairment considerations, and inclusive housing solutions. She examines how spatial design affects well-being, accessibility, and everyday living experiences. Her recent publications demonstrate a strong trajectory toward interdisciplinary approaches to universal design, with increasing focus on dementia care environments, sensory fieldwork methodologies, and lighting conditions for visually impaired populations. The research shows evolution from theoretical frameworks toward practical implementation tools for architects and policymakers. Dr. Frandsen leads multiple significant research projects including 'The need for the elderly to remain in their own homes' (2024-2026), 'The role of light when vision changes' (2023-2027, funded by The Velux Foundation), and 'New process tool: Integrating universal design knowledge into Landsbyggefonden's design process' (2024-2026). These projects demonstrate her commitment to translating research into practical design tools and policy recommendations. She actively supervises PhD students and contributes to academic discourse through conference presentations, peer reviewing, and editorial work. Her research group for Universal Design serves as a hub for interdisciplinary collaboration between architects, healthcare professionals, policymakers, and end-users to develop evidence-based design solutions.

• Machine Learning
• Medical Image Analysis
• Computer Vision
• +۲ مورد دیگر

Nicklas Boserup serves as an Instructor at the Department of Computer Science (DIKU) at the University of Copenhagen, located at Universitetsparken 1 in Copenhagen Ø. His academic appointment places him within the institution's research and teaching structure, contributing to computer science education and research activities. Boserup's research interests center on machine learning applications in medical imaging, with particular focus on self-supervised learning techniques for histopathology image analysis. His work bridges computer vision and healthcare applications, developing algorithms that can process and segment medical images without requiring extensive labeled training data. This research direction addresses critical challenges in digital pathology where annotation by medical experts is time-consuming and costly. Analysis of Boserup's publication record shows a consistent focus on contrastive learning approaches for medical image segmentation, with his 2022-2023 work establishing foundational techniques in patch-based contrastive learning for histopathology. His 2024 publication represents an expansion into parameter inference methods using differentiable diffusion models, indicating a broadening research scope into statistical computing and probabilistic modeling. The trajectory suggests increasing sophistication in handling complex medical imaging data through advanced machine learning techniques. Boserup maintains an active research profile with publications appearing in both preprint repositories and conference proceedings, demonstrating engagement with the academic community. His email contact (nibos@di.ku.dk) provides a direct channel for academic collaboration and professional communication within the university framework.

• Medical Imaging
• Radiology
• Artificial Intelligence in Healthcare
• +۵ مورد دیگر

Jonathan Frederik Carlsen serves as a Clinical Associate Professor at the Department of Clinical Medicine within the Faculty of Health and Medical Sciences at the University of Copenhagen. His academic work is centered in the Radiology section, with research conducted at facilities located at Blegdamsvej 9 in Copenhagen Ø and Blegdamsvej 3 in Copenhagen N. With 37 documented research outputs, Carlsen maintains an active research profile with significant contributions to medical imaging and radiology. Dr. Carlsen's research interests span multiple critical areas in modern medical imaging, with particular emphasis on the integration of artificial intelligence into clinical radiology practice. His work explores innovative applications of imaging technology across various medical specialties including oncology, neurology, and women's health. He investigates both technical aspects of imaging modalities and practical implementation challenges in diverse healthcare settings worldwide. His research demonstrates a strong commitment to improving diagnostic accuracy, treatment planning, and clinical decision-making through advanced imaging techniques. Analysis of Carlsen's recent publications reveals a clear trajectory toward AI-assisted medical imaging with particular focus on tumor delineation, stroke assessment, and diagnostic workflows. His work bridges technical innovation with clinical applicability, examining how AI tools can be adapted to different healthcare contexts globally. The publications show consistent collaboration with interdisciplinary teams, suggesting an integrative approach to medical imaging research that connects technical development with practical clinical implementation. With numerous publications appearing in high-impact journals including Diagnostics, Neuro-Oncology Advances, and Journal of Medical Screening, Carlsen's research has garnered significant attention in the medical imaging community. His work on AI applications in radiology has accumulated multiple citations and substantial readership across academic platforms, indicating growing influence in his field. While specific details about his mentorship activities aren't explicitly provided in the available information, Carlsen's extensive collaborative research network suggests active engagement with students and junior researchers. His work appears to be conducted within the radiology research environment at the University of Copenhagen, involving interdisciplinary teams comprising clinicians, researchers, and technologists working at the intersection of medical imaging and artificial intelligence.

Hua Luمشاهده پروفایل

استاد

• Computer Science
• Data Mining
• Data Science
• +۴ مورد دیگر

Hua Lu is a Professor in the Department of People and Technology Programming, Logic and Intelligent Systems at Roskilde University in Denmark. His research focuses on computer science with specialties in database systems, data mining, spatial data processing, and AI/ML applications for databases. He leads projects on AI-powered spatial databases and data-driven systems. His research interests span multiple domains including data science fundamentals, IoT data streams, location-based services, and database optimization techniques. Recent publications demonstrate strong focus on spatial-temporal data processing, machine learning integration with databases, and practical applications of data science. Professor Lu has received multiple scientific awards including Best Paper nominations and runner-up awards at premier conferences, recognizing his contributions to database and mobile computing research.

Peter Kjær Willendrupمشاهده پروفایل

پژوهشگر

• Neutron & X-ray scattering
• Computational Physics
• Computer Science
• +۳ مورد دیگر

Peter Kjær Willendrup serves as a Senior Research Engineer and Special Consultant at the Department of Physics at the Technical University of Denmark (DTU), where he has been employed since January 2012. He is also seconded to the European Spallation Source (ESS) Data Management and Software Center (DMSC), initially at 33% capacity from June 2014 to January 2023, and at 100% capacity since April 2023. His primary role involves leading major computational projects that support neutron and X-ray scattering research infrastructure. Willendrup's research spans multiple disciplines including neutron & X-ray scattering, computational physics, computer science, data analysis, project management, and software development. His work focuses on creating simulation tools for neutron scattering instrumentation, with particular emphasis on applications for the European Spallation Source in Lund, Sweden. He has made significant contributions to computational methods for neutron scattering experiments and instrument design. His publication record shows a strong trend toward neutron instrumentation development for the ESS facility, with increasing focus on simulation techniques, data analysis methods, and computational approaches to optimize neutron scattering experiments. Recent work demonstrates growing integration of machine learning techniques with traditional simulation methods, particularly for assisting users with model selection in neutron scattering experiments. Willendrup leads two major software projects: McStas (since 2002), which is world-leading in simulation of instrumentation for neutron scattering and virtual neutron scattering experiments, and McXtrace, its X-ray equivalent. These projects involve collaboration with multiple international institutions including DTU, ESS, NBI, ILL, and PSI. His educational background includes an M.Sc. in Physics and a B.Sc. in Mathematics from the University of Copenhagen (1992-2000). Prior to joining DTU, he worked as a research assistant at Rigshospitalet's Neurobiology Research Unit (2000-2002) and briefly as a physics teacher at Skt. Annæ Gymnasium (1998-1999). He is multilingual, speaking Danish, English, Swedish, German, and French fluently.

• Data Management
• Location-Based Services
• Trajectory Data
• +۷ مورد دیگر

Christian S. Jensen is a Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His primary research focuses on data management, spatiotemporal systems, and AI-driven solutions for mobility and cyber-physical systems. He leads projects like DiCyPS (Data-Intensive Cyber-Physical Systems) and MALOT (Managing Mobility Data Quality for Location of Things). He has published over 700 papers, with recent work emphasizing time series forecasting, trajectory analysis, and edge computing. Notable contributions include frameworks like Memory Guided Transformers and TEAM for traffic prediction. His work has been recognized with awards including the IEEE TCDE Impact Award (2019) and the Order of Dannebrog (2016). Jensen actively collaborates internationally, holding roles in organizations like the Max Planck Institute and the Villum Foundation. His research bridges theory and practice, addressing real-world challenges in smart cities, energy systems, and autonomous driving.

• Computability Theory
• Rewriting
• Lambda Calculus
• +۳ مورد دیگر

Jakob Grue Simonsen is a Professor and Department Chair at the Department of Computer Science (DIKU), University of Copenhagen. He holds a Dr. Scient., PhD, and MBA. His research focuses on the mathematics of computation, including computability theory, term rewriting, lambda calculus, complexity hierarchies, and symbolic dynamics, with applications in information retrieval and human-computer interaction. His primary research explores infinite computational processes and their finite representations, alongside practical work in neural hashing, fact-checking systems, and quantum language models. Previously, he contributed to constructive mathematics and biocomputing. An analysis of his 15 most recent publications (2015–2022) reveals strong emphasis on: Theoretical computability and game-theoretic models Neural networks for NLP (BERT, semantic hashing) Fact verification and explainable AI methodologies Efficient retrieval algorithms and recommendation systems Awards: RTA 2004 Best Paper Award CHI '13 Honorable Mention CHI '14 Honorable Mention

• Linguistic Dynamics
• Language Change
• German as a Foreign Language
• +۴ مورد دیگر

Lars Behnke serves as a Teaching Associate Professor at the Department of English, Germanic and Romance Studies (Engerom) within the Faculty of Humanities at the University of Copenhagen. His academic base is at Emil Holms Kanal 6, Copenhagen S. His professional focus spans both theoretical linguistics and practical German language instruction across all proficiency levels. His research centers on linguistic dynamics, particularly language change over time and space, and adaptations during language acquisition. With initial training in Slavic languages (Polish and Russian), he maintains a contrastive perspective—especially regarding Danish-German linguistic relationships—in his German language teaching methodology. His pedagogical philosophy emphasizes functional, communicative approaches to demystify German's perceived difficulty for learners. Analysis of his recent publications reveals concentrated exploration of language contact phenomena in European border zones (particularly German-Polish interfaces), morphosyntactic innovations, and academic literacy frameworks. His work bridges corpus linguistics with practical language teaching, examining tensions between linguistic authenticity and learnability in German-as-foreign-language materials. Current projects address multilingual communicative competence and language policy implementation within Danish higher education. Professional development includes significant involvement in the NCFF-project 'Academic Literacy i et brobygningsperspektiv' and co-organization of conferences like 'Danish and German as European neighbour languages' (2021). His teaching methodology integrates linguistic theory with practical application, focusing on enabling learner competence through accessible communicative strategies.

• Phonetics
• English Pronunciation
• Intelligibility of Accented Speech
• +۵ مورد دیگر

Christian Jensen serves as Associate Professor in the Department of English, Germanic and Romance Studies at the University of Copenhagen's Faculty of Humanities, focusing on phonetics and English-medium instruction (EMI) in higher education. His research examines intelligibility of accented speech and pronunciation's impact on perceived academic competence, with significant contributions to understanding Danish-English phonetic interactions. His educational background includes an MA in English and Phonetics and a PhD. Jensen's primary research areas encompass: English pronunciation (contrastive phonetics and phonology) Teaching and acquisition of pronunciation Speech prosody (stress/accent) EMI in European higher education Speech technology applications for language learning Analysis of his publications from 2012-2024 reveals consistent evolution in EMI research, shifting from foundational studies on vowel perception to contemporary investigations of cognitive load in accented speech comprehension and student-lecturer dynamics. His work increasingly integrates technological approaches while maintaining empirical rigor in measuring intelligibility and academic outcomes. Jensen actively contributes to academic discourse through editorial roles for journals including Nordic Journal of English Studies and Journal of English for Academic Purposes , and serves on review committees for conferences such as the International Symposium on Applied Phonetics. His departmental profile indicates involvement in developing web-based pronunciation training tools and participation in university-level EMI initiatives, though specific grant details remain unlisted in available materials.

• Cognitive Linguistics
• Functional Linguistics
• Usage-Based Grammar
• +۱۱ مورد دیگر

Johan Pedersen is an Associate Professor of Spanish Linguistics at the Department of English, Germanic and Romance Studies , University of Copenhagen . He is also the Chairman of the Kirsten Schottlænder’s Foundation board , which funds research in Spanish, Catalan, and Portuguese language and culture, and serves as Editor of the peer-reviewed journal Revue Romane (John Benjamins, Amsterdam) for Spanish linguistics. Education : MA in Spanish language and culture, University of Copenhagen (1992) Minor in Economics, University of Copenhagen (1993) Graduate Diploma in International Business, HD1, CBS (1995) Ph.D. in Spanish linguistics, University of Copenhagen (2000) Research interests span cognitive and functional linguistics, usage-based approaches to grammar, contrastive linguistics, and language typology. His work focuses on clause structure organization, motion event expressions, Spanish reflexive/impersonal constructions, and the interplay between research, teaching, and learning. He is a member of the research platform Variation and Change in Language and co-directs projects like Cognitive modeling and meaning construction across languages (granted by the Spanish Ministry of Economy and Competitiveness). Key trends in recent publications include analyses of parasynthetic constructions in Spanish, comparative studies of Danish and Spanish verb prefixes, and construction grammar applications to typological differences in motion event framing. His work often integrates corpus linguistics, cognitive modeling, and functional grammar frameworks. Supervision and grants include mentoring PhD candidates such as Alexandra Donoso (motion events, Spanish-Swedish) and Henriette Baleau (causative alternations in Spanish). He has led or co-led projects like the Cogmod grant (Spanish Ministry) and Construction Grammar meets Typology (Marie Curie grant).

• Medical Imaging
• Radiology
• AI in Diagnostic Imaging
• +۴ مورد دیگر

Michael Brun Andersen serves as a Clinical Associate Professor in the Department of Clinical Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences. His work is centered at the Radiology division (Blegdamsvej 3, Copenhagen), with active research output extending into 2025. His institutional email is michael.brun.andersen@regionh.dk and professional profile hosted via University of Copenhagen's domain (ikm.ku.dk). His research spans advanced medical imaging applications with emphasis on AI-driven diagnostic enhancement , oncology imaging protocols , and quantitative analysis of CT/MRI artifacts . Key focus areas include photon-counting CT optimization for prostate cancer radiotherapy, motion artifact mitigation in stroke MRI, and pulmonary nodule surveillance systems. Recent work demonstrates integration of reinforcement learning for pancreatic duct identification and validation of handheld ultrasound in emergency settings. Analysis of his 2024-2025 publications reveals strong collaborative networks across European radiology and oncology research groups. His work frequently addresses clinical implementation challenges of AI in diagnostics, spectrum bias in deep learning models, and functional imaging biomarkers for immunotherapy monitoring. Notable contributions include feasibility studies on DCE-CT parameters in lung cancer therapy and investigations into incidental finding management protocols. While no formal awards or student advisement details are documented in the provided materials, his research demonstrates consistent peer-reviewed output in high-impact journals including Acta Oncologica , European Radiology , and Cancer Imaging . His work shows significant attention from clinical communities with multiple publications referenced in news outlets and Mendeley readership.

Michael Bachmann Nielsenمشاهده پروفایل

استاد بالینی

• Radiology
• Medical Imaging
• Artificial Intelligence Applications
• +۳ مورد دیگر

Michael Bachmann Nielsen, DMSc, PhD, serves as a Clinical Professor in the Department of Clinical Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences, maintaining dual affiliations with the Radiology department and Capital Region of Denmark (Region Hovedstaden) at Blegdamsvej addresses in Copenhagen. His active clinical-academic role bridges medical practice and research innovation. His research program focuses on: AI-driven optimization of medical imaging workflows Advanced ultrasound techniques including super-resolution vascular imaging Clinical applications in neuroimaging, oncology, and pediatric diagnostics Machine learning for radiology report analysis and protocol adaptation Recent publications demonstrate significant contributions to MRI protocol refinement, tumor volume delineation, and contrast-free microvascular imaging. His work consistently appears in high-impact journals like European Journal of Radiology and Scientific Reports, emphasizing practical clinical translation of imaging technologies through cross-disciplinary collaboration. Nielsen's extensive publication record (291 outputs) reflects leadership in adapting artificial intelligence to radiology practice, with particular emphasis on workflow efficiency and diagnostic accuracy across diverse clinical scenarios.

• Radiology
• Medical Imaging
• Dual-Energy CT
• +۴ مورد دیگر

Peter Sommer Ulriksen serves as a Clinical Associate Professor in the Department of Clinical Medicine at the University of Copenhagen, specializing in Radiology within the hospital system of the Capital Region of Denmark (Region Hovedstaden) at Blegdamsvej 3, 2200 Copenhagen N. His research focuses on advanced CT imaging techniques, particularly dual-energy and spectral CT, with applications in pulmonary embolism diagnosis, bowel ischemia detection, and AI-assisted quantification. He pioneers iodine density mapping and deep learning reconstruction methods to enhance diagnostic precision in acute care settings. Analysis of his 2021-2025 publications reveals a cohesive trajectory in optimizing CT protocols for emergency radiology, emphasizing quantitative biomarkers and multi-center clinical validation. His work consistently bridges engineering innovation with clinical implementation across pulmonary and abdominal imaging domains.