جستجوی استاد راهنمای دانشگاهی

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.

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

Nicholas Dias is a postdoctoral researcher at the Department of Political Science, Aarhus University. His work focuses on public opinion, political psychology, and the dynamics of democratic systems. Research examines citizen competence, polarization, and misinformation Teaching includes seminars on American politics and data science Contact: niccdias@ps.au.dk Research Trends: Dias’s publications analyze how citizens engage with democracy, polarization’s impact on governance, and misinformation mitigation. His work challenges assumptions about voter rationality and explores the limits of correcting partisan misperceptions. Collaborations: Co-authored studies with scholars like Y. Lelkes and A. Sippitt, published in journals such as Journal of Politics , PNAS Nexus , and Political Quarterly .

• Political Science
• Public Opinion
• Political Psychology
• +۴ مورد دیگر

Desmond Elliott is an Associate Professor in the Natural Language Processing section at the Department of Computer Science, University of Copenhagen (UCPH). His research focuses on multimodal and multilingual models with specific emphasis on vision-language integration and tokenization-free NLP approaches. He teaches Bachelor and Master's level courses including Advanced Topics in Natural Language Processing (since 2019), Grundlæggende Data Science (since 2023), and previously Data Science (2021-2023). His research interests center on building and understanding multimodal and multilingual models , particularly exploring vision and language interactions through billion-parameter systems. Current work investigates cultural representation disparities in vision-language models, parameter-efficient captioning, and multimodal distributional semantics across diverse domains including food culture and medical imaging. His methodology emphasizes real-world applicability in non-English contexts and ethical considerations in multimodal systems. Elliott's recent publications (2025) demonstrate leadership in multimodal NLP, with significant contributions to vision-language pretraining, multilingual evaluation frameworks, and clinical NLP applications. His work spans theoretical advancements in model architectures and practical implementations addressing challenges in low-resource languages and domain adaptation. Best Long Paper Award at EMNLP 2021 Best Poster Award at COLING 2019 As an active educator, Elliott contributes to courses on Fair and Transparent Machine Learning and previously taught Information Retrieval. His research collaborations span international institutions with particular focus on European and non-English language contexts, reflecting UCPH's recognition as Europe's #1 institution for HCI research over the past decade.

• Multimodal Learning
• Multilingual NLP
• Vision-Language Models
• +۴ مورد دیگر

Jesper Rindom Jensen is an Associate Professor in the Department of Electronic Systems at Aalborg University, Denmark, under the Technical Faculty of IT and Design. He is the Head of the Audio Analysis Lab, a leading research group in audio signal processing, since 2023. His work bridges theoretical signal processing and practical applications in artificial intelligence and audio systems. Full Name: Jesper Rindom Jensen Institution: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Audio Analysis Lab Email: jrj@es.aau.dk Office: Fredrik Bajers Vej 7B, B5-206, 9220 Aalborg Øst, Denmark Education: M.Sc. in Electronic Systems, Aalborg University (cum laude, 2009) Ph.D. in Signal Processing, Aalborg University (2012) Research Interests: Jesper Rindom Jensen's research centers on audio signal processing, with a strong emphasis on artificial intelligence, speech enhancement, noise reduction, beamforming, and multichannel systems. His work applies to diverse domains including robot and drone audition, spatial audio, and active noise control. He develops novel filtering techniques, including variable span linear filters and harmonic beamformers, to improve speech quality and intelligibility in noisy and reverberant environments. Publication Trends: His recent publications (2023–2025) show a strong trend toward integrating deep learning with classical signal processing, particularly in direction-of-arrival estimation, underwater acoustics, and robust multichannel systems. There is a clear focus on real-world applications, including sound zone control, active noise control, and limited-data scenarios using knowledge distillation. His work consistently emphasizes robustness, efficiency, and practical deployment. Scientific Awards and Recognition: AAU Talent for emerging research leaders Recipient of a competitive postdoc grant from the Danish Independent Research Council Advising and Grants: Jesper has supervised multiple PhD and master’s students, including Nørholm, Karimian-Azari, Zhang, and Wang. He has led significant research projects such as 'Sound Processing for Robots and Drones' (2018–2020) and participated in others related to joint audio-visual tracking and speech enhancement. His research has been supported by national funding bodies, reflecting its innovation and impact. Labs and Teams: He is a founding and core member of the Audio Analysis Lab at Aalborg University, which focuses on cutting-edge audio signal processing and AI-driven solutions. The lab fosters interdisciplinary collaboration and has produced numerous publications, datasets, and real-world applications. Jensen’s leadership since 2023 underscores his pivotal role in shaping the lab’s research direction.

• Audio Signal Processing
• Artificial Intelligence
• Speech Enhancement
• +۱۲ مورد دیگر

Dorte Hammershøi is a Professor in the Department of Electronic Systems at The Technical Faculty of IT and Design, Aalborg University, Denmark. Her research focuses on acoustics, sound engineering, and hearing science with significant contributions to human hearing, ear canal acoustics, and audio technology applications. Her research interests include: Temporary Threshold Shift and frequency resolution in human hearing Ear canal acoustics and sound pressure level measurement Distortion Product Otoacoustic Emission (DPOAE) analysis Impulse response and acoustic impedance studies Hearing aid technology and rehabilitation methodologies Virtual reality audio interfaces and accessibility applications Professor Hammershøi's recent publications demonstrate a strong clinical-engineering interdisciplinary approach, bridging theoretical acoustics with practical hearing rehabilitation applications. Her work on hearing aid fitting methodologies, occupational noise exposure effects, and virtual reality audio interfaces shows consistent innovation in translating engineering principles to clinical practice. The research shows particular attention to individualized hearing solutions and accessibility technologies. Her scientific contributions have been recognized with: Dansk Lydpris 2020 (awarded November 17, 2021) Ambassadør for Aalborg (awarded September 15, 2004) Professor Hammershøi has supervised 5 PhD students and led numerous research projects including the ongoing "Audio Only VR for Blind Gamers" project (2024-2028) funded by the Independent Research Foundation of Denmark, and the completed "BEAR: Better Hearing Rehabilitation" project (2016-2022). Her research has attracted significant media attention with 110 press/media appearances discussing hearing damage prevention, tinnitus, and public health implications of noise exposure. She maintains active professional engagement through committee memberships (46 documented activities), international collaborations, and contributions to clinical practice guidelines. Her work continues to influence both academic research and practical applications in hearing science and audio engineering.

• Acoustics
• Hearing Science
• Audio Engineering
• +۵ مورد دیگر

Daniel Hershcovich is a Tenure Track Assistant Professor at the Department of Computer Science (Faculty of Science, University of Copenhagen) specializing in Natural Language Processing and Machine Learning . His research focuses on cross-cultural adaptation of language models, integrating human values into AI, and analyzing food-related cultural narratives for sustainable diets. Education: Ph.D. in Computational Neuroscience from Hebrew University of Jerusalem B.Sc. in Mathematics and Computer Science from Open University of Israel Recent publications highlight his work on multimodal models (haptic captioning, visual assistants for the blind), historical text analysis (Danish/Norwegian literature, euphemism detection), and cross-cultural NLP (recipe adaptation, cultural value alignment, climate awareness). His projects frequently combine AI ethics with domain-specific applications like food studies, historical linguistics, and accessibility research. Key collaborative networks include institutions in Denmark, Israel, and international partnerships through conferences like ACL, EMNLP, and workshops on cross-cultural NLP. The NLP section at DIKU serves as his primary affiliation for these efforts.

• Natural Language Processing
• Machine Learning
• Cultural Adaptation in NLP
• +۴ مورد دیگر

Sneha Das is an Assistant Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), specializing in Speech and Language Technology, Machine Learning, and Privacy-Preserving AI. Her research bridges technical innovation with applications in mental health and physiological signal analysis. Her work focuses on Speech Emotion Recognition , Distributed Speech Processing , and Explainable AI , with recent publications exploring model interpretability, speaker anonymization, and physiological data analysis for emotion detection. She actively supervises PhD students in projects involving AI for mental health and hydroacoustic modeling of fish behavior. Key Research Areas: Speech Emotion Recognition (SER) Privacy and Fairness in Speech Processing Transfer Learning with Physiological Time Series AI Applications in Health and Aquaculture Notable achievements include earning a DSc (Tech) degree for her thesis on robust distributed speech processing. She also contributes to educational activities, including teaching applied statistics and R programming to PhD students.

• Speech and Language Technology
• Machine Learning
• Data Privacy
• +۵ مورد دیگر

Isabelle Augenstein is a Professor at the University of Copenhagen, Department of Computer Science (DIKU), where she heads the Copenhagen Natural Language Understanding (CopeNLU) research group and the Natural Language Processing section. She is also a co-lead of the Danish Pioneer Centre for Artificial Intelligence, Denmark's largest research center initiated by the Danish Ministry of Higher Education and Science. In October 2022, she became Denmark's youngest ever female full professor. Dr. Augenstein earned her undergraduate degree in Computational Linguistics and Psychology from Heidelberg University, followed by a Master's in Computational Linguistics. She completed her PhD in Computer Science at the University of Sheffield under the supervision of Dr. Diana Maynard and Prof. Fabio Ciravegna. In 2021, she earned a Habilitation at the University of Copenhagen in Explainable Fact-checking. Professor Augenstein's primary research focuses on fair and accountable Natural Language Processing, with particular emphasis on explainability, factuality, and bias detection. Her work spans multiple subfields including automated fact-checking, stance detection, gender bias analysis, and cultural bias in language models. She has pioneered research in explainable fact-checking, developing methods that not only predict claim veracity but also provide meaningful explanations of the decision-making process. Her research group has produced numerous influential papers on measuring model fragility, quantifying gender biases, and developing robust fact-checking systems that account for distribution shifts. Her significant contributions have been recognized with several prestigious awards: ERC Starting Grant on 'Explainable and Robust Automatic Fact Checking' DFF Sapere Aude Research Leader fellowship on 'Learning to Explain Attitudes on Social Media' Karen Spärck Jones Award from the British Computing Society and Bloomberg Hartmann Diploma Prize from the Hartmann Foundation Member of the Royal Danish Academy of Sciences and Letters since 2024 Professor Augenstein has secured significant research funding including her ERC Starting Grant supporting five years of blue-sky research. She actively mentors PhD students and postdoctoral researchers through her 'ExplainYourself' project. She served as President of SIGDAT (which organizes the EMNLP conference series), having previously held leadership roles as Vice President and Vice President-Elect. She is a co-founder of Widening NLP (WiNLP), an initiative to increase diversity in the NLP community, and maintains the BIG Directory of underrepresented groups in NLP. She leads the Copenhagen Natural Language Understanding (CopeNLU) research group, which relocated to the historic Østervold Observatory in Copenhagen's Botanical Gardens in 2023. The group focuses on developing methods for explainable and robust natural language understanding, with applications in fact-checking, bias detection, and social media analysis. Professor Augenstein also co-leads the Speech and Language collaboratory at the Pioneer Centre for Artificial Intelligence, where her team investigates how language models can better serve diverse populations while maintaining accountability and transparency.

• Natural Language Processing
• Explainable AI
• Fact-Checking
• +۴ مورد دیگر

Karina Kosiara-Pedersen is an Associate Professor at the Department of Political Science, University of Copenhagen. She coordinates the Center for Voting and Parties (CVAP) and contributes to the Gender & Politics research group. Her work focuses on party membership, organizational development, candidate recruitment, and political harassment. Research keywords include political parties, democracy, electoral systems, and political violence Teaching courses in Danish and Comparative Politics Current research examines gender-based anger in politics (2024-2025), political harassment (DIPAS, 2022-2025), and candidate surveys across municipal/regional/parliamentary elections. She co-leads the Political Parties Database (PPDB) and studies online harassment. Her media contributions (1,193) often address Danish political trends, including recent analysis of electoral shifts and parliamentary dynamics. She serves on the Department’s Faculty board and has been study board chair since 2022.

• Political parties
• Party organizations
• Party membership
• +۱۳ مورد دیگر

Per Bækgaard is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), specializing in Cognitive Systems. He serves as Head of Study for Human-Centered Artificial Intelligence, leading research in human-computer interaction, user experience, eye tracking, and cognitive neuroscience. His work bridges AI and human cognition to create systems that enhance daily life and support meaningful tasks. PhD, MSc EE, Technical University of Denmark His research interests center on Human-Computer Interaction (HCI) , User Experience , and Human-Centered Artificial Intelligence , with strong emphasis on Eye Tracking , Cognitive Neuroscience , and Digital Media . He explores how digital systems can adapt to users’ cognitive states using physiological signals like pupil dilation and gaze patterns, aiming to improve learning, health, and decision-making. His work aligns with UN Sustainable Development Goals in health and education. The recent publications reflect a strong trend in integrating eye tracking and pupillometry with AI-driven adaptive systems , particularly in education and healthcare. Themes include generative AI in learning , trustworthy AI in supply chains , and digital micro-interventions for mental health . The interdisciplinary nature spans computer science, psychology, and biomedical engineering, showcasing a cohesive focus on human-centered technology evaluation. Scientific Awards: Best Paper Award, 26 Jun 2020 – for contributions to gaze interaction research Per Bækgaard actively supervises PhD students and leads multiple research projects, including those involving generative AI in education , digital phenotyping , and AI in nursing and mental health . He is the main supervisor for several PhD projects and a co-supervisor or examiner in others, demonstrating a strong commitment to academic mentoring. His grant involvement includes projects funded by DTU and collaborative research initiatives in digital health and AI. He is part of the Cognitive Systems group at DTU, contributing to interdisciplinary research in AI, neuroscience, and human factors. His team collaborates on projects involving real-time physiological monitoring, adaptive interfaces, and AI-mediated learning systems, positioning him at the forefront of human-centered AI research in Scandinavia.

• Human-Computer Interaction
• User Experience
• Human-Centered Artificial Intelligence
• +۷ مورد دیگر

Charlotte Fooks is a Research Assistant at the Centre for Industrial Electronics , Institute of Mechanical and Electrical Engineering, University of Southern Denmark. Her work focuses on biosignal analysis, vibroacoustic stimulation, and stress assessment. Research Output: 2 peer-reviewed publications (2024) investigating vibroacoustic therapy's effects on stress metrics using speech and physiological signals Key Tools: Electrocardiogram (ECG), electroencephalogram (EEG), Perceived Stress Scale, parasympathetic activity measurements Her research combines biomedical signal processing with human stress assessment to evaluate non-invasive wellness interventions. Recent studies analyze vibroacoustic sound massage through speech biosignals and quantify its impact on physiological stress markers. Collaborative work with Dr. Niebuhr demonstrates measurable improvements in stress parameters through vibroacoustic interventions, contributing to emerging physiological monitoring and stress management technologies.

• Biomedical Engineering
• Signal Processing
• Stress Assessment
• +۳ مورد دیگر

Peter Vuust is a Professor at the Center for Music in the Brain, Department of Clinical Medicine, Aarhus University. With over 397 publications and 22 ongoing or completed research projects, his work bridges neuroscience, music cognition, and clinical applications. His research spans multiple decades with significant publication output from 2000-2025, showing increasing productivity in recent years with 27 publications in 2024 and 19 in 2025. His research interests focus on music cognition and neuroscience, particularly examining how the brain processes musical elements like rhythm, harmony, and beauty. Vuust employs advanced neuroimaging techniques including fMRI, MEG, and EEG to investigate auditory processing, neural entrainment, and the relationship between music training and cognitive abilities. Key areas include mismatch negativity, auditory cortex function, brain networks, and functional connectivity during music perception. His work spans fundamental research on rhythm perception and musical beauty to clinical applications involving cochlear implants and music therapy. Vuust's recent publications (2023-2025) demonstrate a strong focus on the neural correlates of musical experience, with particular attention to rhythm perception, musical beauty, and the relationship between music training and sensory processing. His work often involves interdisciplinary collaborations and combines behavioral measures with neuroimaging to provide comprehensive insights into music cognition. Current research directions include studying rhythmic complexity, neural entrainment, music's therapeutic applications for sleep, and the development of music processing skills in cochlear implant users. Professor Vuust actively engages with the public through numerous presentations and media appearances, including recent talks at Roskilde Oplysningsforbund, Lægeforeningen, Folkekirkens Uddannelses- og Videnscenter, Djursland Jazzfestival, and HerningErMusik in 2024. His research is supported by various funding sources including Helsefonden (Danish Health Foundation), with multiple ongoing projects exploring musical rhythm, neural entrainment, developmental aspects of music processing, and music's therapeutic applications. At the Center for Music in the Brain, Vuust collaborates with researchers including Elvira Brattico, Simone Dalla Bella, Morten Kringelbach, and Bjorn Petersen. His interdisciplinary team spans neuroscience, musicology, and clinical medicine, working together to unravel the complex relationship between music and the brain through both basic and applied research.

• Music Cognition
• Neuroscience
• Brain Imaging
• +۷ مورد دیگر

Tina Høegh is an Associate Professor at the Department of Design, Media and Educational Science, Faculty of Humanities, University of Southern Denmark. Her research focuses on dialogic teaching, intercultural pedagogy, multimodal communication, and the digitalization of classrooms. She leads the InDi project funded by the Independent Research Fund Denmark and co-leads the DiaMu focus area at SDU. PhD and MA in Nordic Studies and Linguistics (University of Copenhagen) Active in Nordic collaborations like QUINT and EU-funded MiCREATE Specializes in second-order didactics and autoethnographic methods Her work bridges micro-level classroom dynamics with macro-level educational policy, emphasizing democratic participation through aesthetic expression. She has supervised Master’s and PhD students and participated in ministerial projects on interdisciplinary teaching. Recent Trends : Recent publications highlight sustainable digital pedagogy, literacy-as-events in techno-scholastic environments, and collaborative production processes. Themes include multimodal interaction, intercultural competence, and AI as a dialogic partner. Scientific Collaborations : Co-founder of the FiDU network on dialogic teaching Chair of the ARLE Special Interest Group on dialogic practices Active in Nordic writing seminars and cross-country educational research

• Pedagogy
• Dialogic Teaching
• Intercultural Pedagogy
• +۵ مورد دیگر

Daniel Spikol is an Associate Professor at the Department of Computer Science , University of Copenhagen , affiliated with the Center for Digital Education and Human-Centred Computing section. His research focuses on multimodal learning analytics, computational thinking, and physical computing technologies that enhance learning, play, and reflection. Keywords: Learning Analytics, Human-Computer Interaction, Computational Thinking His recent work examines: Collaborative task design impacts on knowledge construction AI trust dynamics in educational contexts across six countries Smart learning environment integration with MMLA Design frameworks for multimodal analytics systems Key publications (2023-2025) analyze: Cultural factors in AI adoption Collaborative learning metrics Speech analytics for language acquisition He leads research bridging ambient computing, social signal processing, and educational innovation through physical computing toolkits like Talkoo (2016) and mBox (2024).

• Multimodal Learning Analytics
• Human-Computer Interaction
• Computational Thinking
• +۳ مورد دیگر

Barbara Plank is a Professor and Chair for AI and Computational Linguistics at LMU Munich , where she leads the Munich AI and NLP (MaiNLP) Lab within the Center for Information and Language Processing (CIS) . She also serves as a Visiting Full Professor at the IT University of Copenhagen . Her research focuses on natural language processing under real-world constraints, including domain adaptation, continual learning, and multimodal learning. Current Projects: ERC Consolidator DIALECT Project KLIMA-MEMES Project Her recent work investigates annotation bias , self-consistency in language models , and trustworthy model evaluation . She has delivered keynotes at major conferences like ACL, EMNLP, and CLEF, emphasizing human-centric approaches to NLP. Scientific Awards: ACL 2024 Area Chair Award Barbara actively contributes to the academic community as VP-Elect for the Association for Computational Linguistics (ACL) and through teaching roles in MSc/BSc Computational Linguistics programs.

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۳ مورد دیگر