Find Academic Supervisors

• Human-Computer Interaction
• Virtual Reality
• Body-Based User Interfaces
• +3 more

Joanna Bergström is an Associate Professor in the Department of Computer Science within the Faculty of Science at the University of Copenhagen. Her research focuses on human-centered computing, specifically in human-computer interaction (HCI), virtual reality (VR), and body-based user interfaces. Based at Sigurdsgade 41 in Copenhagen, she maintains an active research profile with 41 publications and significant international collaborations. Her primary research interests include virtual reality systems , haptic feedback mechanisms , interaction techniques , and perceptual studies . She investigates experimental methods in HCI, human perception, motor skills, and statistical modeling. Current projects explore tendon vibration for movement illusions in VR, ultrasound-based chemical stimulants for skin haptics, and doorway effects on memory in virtual environments. Analysis of her 15 most recent publications (2023-2025) reveals strong emphasis on VR locomotion techniques , haptic perception , and cognitive aspects of virtual environments . Key trends include multimodal feedback systems (combining tactile and chemical stimulation), real-world application of VR for medical training, and rigorous experimental validation of interaction paradigms. Her work frequently appears in top venues like CHI and IEEE Transactions on Haptics. Bergström maintains active research networks across multiple countries, with significant external collaborations reflected in her publication record. Her work has been referenced by 12 news outlets and garnered attention on social media platforms including X (7 users) and Bluesky (3 users), while accumulating 23 Mendeley readers for her 2025 DIRA paper.

Peter DalsgaardView profile

Professor

• Human-Computer Interaction
• Design
• Creativity Support Tools
• +5 more

Peter Dalsgaard is a Professor at Aarhus University's School of Communication and Culture, specifically within the Department of Digital Design and Information Studies. He maintains three additional institutional affiliations and serves as a leading researcher in human-computer interaction and digital design. His work bridges theoretical frameworks like pragmatism with practical applications in creativity support tools, media architecture, and participatory design methodologies. His research centers on how digital tools shape creative processes across professional domains. Key interests include idea capture and management in design workflows, the impact of AI on collaborative creativity, and the temporal dynamics of idea evolution. Recent work examines cross-domain practices among graphic designers, musicians, and other creative professionals, revealing how tool constraints influence creative outcomes. He integrates philosophical perspectives like more-than-human theory to address ethical dimensions in HCI. Analysis of his 15 most recent publications (2023-2025) shows a decisive shift toward AI-human collaboration in creativity, with 60% of recent work exploring AI's dual role as enabler and constraint. His studies increasingly employ longitudinal methods to track idea development, while maintaining strong foundations in participatory design and media architecture. The research spans practical applications in public libraries and design sprints, balancing technical innovation with critical theoretical inquiry. Dalsgaard has secured significant funding for major projects including CoCreate (2017-2021) on collaborative creativity tools, PLACED (2017-2020) for dynamic library services, Creative Tools (2017-2020), and CIBIS (2014-2018) on blended interaction spaces. These initiatives demonstrate sustained focus on translating theoretical insights into deployable systems for real-world creative environments.

• Medical Image Analysis
• Image Segmentation
• Image Registration
• +3 more

Jens Petersen is an Associate Professor at the Department of Computer Science , University of Copenhagen, specializing in medical image analysis. He works within the Image Analysis, Computational Modelling, and Geometry research section. Education: B.Sc. (2005), M.Sc. (2010) in Computer Science from University of Copenhagen; Ph.D. (2014) in Medical Image Analysis from University of Copenhagen with visiting researcher experience at University College London. Research Interests: Focus on medical image analysis techniques for segmentation and statistical analysis of tubular/branching structures like airways and carotid arteries. Key methodologies involve graph cuts, optimal surface methods, and computational modeling. Current research includes AI-guided tumor delineation, longitudinal image synthesis, and physics-based deformable registration. Publications Trends: Recent work spans AI applications in oncology, computational methods for cardiovascular imaging, and algorithm development for radiation therapy. Collaborations include international institutions and cross-disciplinary teams in machine learning and medical imaging.

Ivan Adriyanov NikolovView profile

Assistant Professor

• Computer Graphics
• Computer Vision
• Augmented Reality
• +6 more

Ivan Adriyanov Nikolov is an Assistant Professor at the Department of Architecture, Design and Media Technology within Aalborg University's Technical Faculty of IT and Design. He specializes in Computer Graphics, Computer Vision, and Augmented Reality, with a focus on 3D reconstruction techniques like Structure-from-Motion (SfM). His work bridges academic research and industrial applications, particularly in wind turbine blade inspection and educational technology. His educational background includes contributions to computer science education through innovative teaching methods. He has led projects like 'Drone Application for Pioneering Reporting in Wind Turbine Blade Inspection' (2017–2019) and 'Leading Edge Roughness - Wind Turbine Blades' (2015–2019), advancing drone-based inspection and 3D modeling for wind energy sectors. Research interests include synthetic data generation, environmental monitoring datasets (e.g., BrackishMOT, DigiWeather), and improving VR/AR user experiences. He has developed tools for dynamic lighting in pixel art games and multimodal guardian systems in VR. His datasets, such as Sewer Defect Point Clouds and Wind Turbine Blade SfM Reconstructions, are publicly available for academic use. He actively contributes to educational innovation, such as flipped classroom strategies to boost programming class engagement. His interdisciplinary approach spans computer graphics, AI-driven NPC interactions, and collaborative mixed-reality games for trust-building. Labs/Teams: Member of the Computer Graphics Group and Visual Analysis and Perception team at Aalborg University. Collaborates with industry partners on drone technology and environmental surveillance systems.

Elizabete MunzlingerView profile

Research Fellow

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +5 more

Elizabete Munzlinger is a Research Fellow (industrial PhD) at the IT University of Copenhagen specializing in Data Science, concurrently employed as an Industrial PhD candidate at GN Audio A/S (Jabra) since October 2023. Her work bridges academic research and industry applications in human-computer interaction and AI-driven interface design. Education: Master of Science in Computer Science and Electronic Engineering, Aeronautics Institute of Technology (ITA), completed May 2008. Thesis: "Multimodal and Multi-User Extensions of Graphical and Voice Interfaces based on Speech Technologies and Interactions Models." Bachelor in Computer Science, Universidade do Oeste de Santa Catarina (UNOESC), completed July 2005. Thesis: "The Use of Computers in the Domotic to Help Disabled People." Research Focus: Munzlinger pioneers cross-cultural interaction systems through multimodal interfaces, specializing in hand gesture recognition for virtual/hybrid meetings. Her work integrates machine learning with cultural anthropology to develop universally accessible communication tools, emphasizing accessibility for diverse user populations and voice interface optimization. Research Trends: Recent publications demonstrate a strategic shift toward globally applicable gesture vocabularies addressing cultural diversity in virtual collaboration. Her work synthesizes taxonomy classification, semantic similarity analysis, and foundation models to overcome cross-cultural communication barriers in distributed teams, with strong emphasis on practical Edge AI deployment. Scientific Recognition: Best Poster Extended Abstract Award (July 4, 2024) for gesture-based HCI research at international conference Grant Leadership: Principal Investigator for the Innovation Fund Denmark project "HAND: Identifying Universal Communal Hand Gestures for Virtual and Hybrid Meeting Interaction" (2023-2026; 36 months). This €1.2M initiative develops standardized gesture systems for global virtual collaboration, focusing on cultural adaptation and real-time implementation. Professional Engagement: Active contributor to CVPR 2024 tutorial on Edge AI deployment, demonstrating expertise in translating theoretical AI models into production-ready systems. International collaborations span Denmark, USA, and Brazil through the HAND project consortium.

• Human-Computer Interaction
• Virtual Reality
• Body-Based User Interfaces
• +5 more

Joanna Emilia Bergström serves as an Associate Professor in the Department of Computer Science at the University of Copenhagen, specializing within the Human-Centred Computing research section. Her academic work focuses on advancing human-computer interaction through innovative research in virtual reality and body-based user interfaces, where she applies rigorous experimental methods, investigates human perception and motor skills, and develops statistical models for interaction techniques. Dr. Bergström holds a D.Sc. (technology) degree, establishing her technical expertise in the field. Her educational background has prepared her for interdisciplinary research that bridges computer science with cognitive psychology and sensory science. Her primary research interests encompass human-computer interaction with particular emphasis on virtual reality systems and embodied interaction techniques. Bergström's work investigates how humans perceive and interact with digital environments, examining the intersection of cognitive psychology, motor control, and interface design. She employs experimental methodologies to study sensory illusions, haptic feedback systems, and the cognitive aspects of virtual environments. Her research often explores how virtual reality can create compelling illusions of presence and movement, with applications ranging from consumer VR to specialized training environments. This work has significant implications for designing more intuitive and effective virtual interfaces that align with human perceptual and motor capabilities. Analysis of her recent publication record (2024-2025) reveals a strong thematic focus on virtual reality interaction techniques, particularly examining presence phenomena, selection methods, haptic feedback mechanisms, and the cognitive aspects of virtual navigation. Her research demonstrates consistent interdisciplinary collaboration, as evidenced by co-authorship with researchers across different institutions and disciplines. The work spans theoretical contributions to HCI models and practical applications for consumer VR technologies, showing how academic research translates into real-world implementations. Bergström's publications appear in top-tier venues including CHI and IEEE Transactions on Haptics, indicating recognition within the international HCI community. Dr. Bergström actively collaborates with industry partners and academic institutions globally, as reflected in her international research projects and publications. Her work has gained significant attention beyond academia, with mentions in 12 news outlets and engagement across social media platforms including X (formerly Twitter), Facebook, and Bluesky. This broader impact demonstrates the relevance of her research to both technical communities and the general public. She is embedded within the Human-Centred Computing section at the University of Copenhagen's Department of Computer Science, contributing to both research and teaching activities. Her work connects with other research areas within the department including machine learning, image analysis, and software development, creating opportunities for cross-disciplinary innovation in human-centered technologies.

• Computer Graphics
• Physics Based Animation
• Computer Vision
• +1 more

Knud Henriksen serves as a Part-time Lecturer at the Department of Computer Science (DIKU), University of Copenhagen, within the Image Analysis, Computational Modelling and Geometry research section. His academic profile integrates teaching and research in computer graphics, physics-based animation, and computer vision, contributing to DIKU's expertise in visual computing methodologies. His educational background comprises: Elektroingeniør (Electrical Engineering) Cand. Scient (Master of Science) Ph.D. Henriksen's research focuses on Computer Graphics, Physics-Based Animation, Computer Vision, and Mathematics, with current investigations into inverse kinematics using bone representations and quaternions. His work emphasizes improving computational efficiency and realism in character animation through mathematical modeling and geometric algorithms. Analysis of his 30 publications (2002-2008) reveals consistent innovation in animation algorithms, particularly in inverse kinematics, physics simulation, and spline-based modeling. These contributions bridge theoretical computer graphics with practical applications in gaming and virtual reality, demonstrating robust solutions for 3D interaction and character rigging. No scientific awards are documented in the available information. Henriksen has supervised graduate projects including a 2008 thesis on quaternion-based inverse kinematics. While specific grant details are absent, his research aligns with DIKU's interdisciplinary approach. He operates within the Image Analysis, Computational Modelling and Geometry section, which collaborates extensively with industry on visual computing challenges.

Jon SporringView profile

Professor

• Computer Science
• Mathematical Image Processing
• Medical Image Analysis
• +6 more

Jon Sporring is a Professor at the Department of Computer Science, University of Copenhagen, specializing in theoretical and applied image processing, stochastic geometry, and biomedical imaging. He leads research in mathematical and medical image analysis, computer graphics, and pattern recognition. Education: Ph.D. in Computer Science (1998), Master in Computer Science (1995), both from University of Copenhagen Affiliations: Pioneer AI section, Applied Geometry Lab, and Faculty of Science External Roles: Visiting professor at McGill University (2012-13), co-founder of DigiCorpus Aps (2012-16) His research integrates scale-space theory, statistical shape analysis, and advanced imaging techniques for applications in medical diagnostics, materials science, and neuroscience. Recent work focuses on 3D reconstruction, persistent homology for bias correction, and AI-driven biomedical analysis. Jon teaches computer science at all academic levels, currently offering courses in bioimaging, signal processing, and deep learning. He emphasizes collaborative projects with external partners and has held administrative roles including Vice-Chair for Research at DIKU. His 15 most recent publications reflect expertise in medical imaging, 3D modeling, and AI applications, with subfields spanning neurodegenerative disease analysis, mitochondrial ultrastructure, and multi-scale image processing. Articles demonstrate interdisciplinary impact across medicine, biology, and materials science.

Rikke GadeView profile

Associate Professor

• Computer Vision
• Image Processing
• Robot Vision
• +5 more

Rikke Gade is an Associate Professor at the Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design at Aalborg University. Her research focuses on Visual Analysis and Perception, AI for the People, and Mobility and Tracking Technologies. She has established herself as a leading researcher in computer vision applications across multiple domains including sports analytics, animal welfare, and human-computer interaction. Dr. Gade earned her PhD in Computer Vision from Aalborg University in 2015 with her dissertation "Taking the Temperature of Sports Arenas - Automatic Analysis of People." Prior to this, she completed her M.Sc. in Informatics with specialization in Vision, Graphics and Interactive Systems in 2011, and her B.Sc. in Electronic and Electrical Engineering in 2009. Her research interests span Computer Vision, Image Processing, Robot Vision, and Thermal Imaging with applications in diverse fields. She has pioneered work in using thermal imaging for sports analytics, developing systems for tracking athletes and analyzing movement patterns in sports arenas. More recently, her research has expanded into AI applications for animal welfare, particularly developing computer vision systems for detecting pain and stress in horses through facial expression analysis. Dr. Gade's publications reveal a clear progression from foundational work in thermal imaging and sports analytics toward more complex applications in healthcare, animal welfare, and smart building systems. Her most recent work shows increasing focus on ethical AI applications that serve societal needs, as evidenced by projects like "AI for the People" and research on equine pain detection. Best Paper Award at Conference CISBAT 2021 (Lausanne, Switzerland) Dr. Gade actively supervises PhD students, including Alves, J.M. on equine affective state assessment. She has secured significant research funding, including a major grant from the Independent Research Fund Denmark for developing AI systems to detect pain in horses. Her collaborative approach is evident in her involvement in multiple interdisciplinary projects spanning computer science, veterinary medicine, and building science. She leads the Visual Analysis and Perception research group at Aalborg University, focusing on practical applications of computer vision technologies. Her team works closely with industry partners on real-world implementations, particularly in sports analytics and animal welfare applications. Current projects include developing AI systems for road damage detection in collaboration with Faxe Kommune and creating advanced tracking systems for sports performance analysis.

Henning PohlView profile

Assistant Professor

• Virtual Reality
• Augmented Reality
• Human-Computer Interaction
• +4 more

Henning Pohl is a Tenure Track Assistant Professor in the Department of Computer Science at Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on Human-Centered Computing, emphasizing Virtual Reality (VR), Augmented Reality (AR), and subtle/casual interaction techniques. He explores how technology can be integrated into everyday life through wearable devices and contextual computing. Key research interests include body-based AR interfaces, mobile interaction design, and the ethical implications of AI-generated advice. Notable projects include developing tools like Hafnia Hands for VR research and investigating user perceptions of AI limitations. His work bridges HCI with practical applications in mental health support, collaborative platforms like OpenStreetMap, and playful AR environments. Recent publications highlight advancements in AR feedback during conversations, LLM denial mechanisms, and fear-inducing game design. His articles reflect a commitment to understanding human-technology relationships across psychological, social, and technical dimensions. Labs/Teams: Human-Centered Computing group at Aalborg University Advising: No formal student advisees listed in available texts.

Manfred JaegerView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Bayesian Networks
• +5 more

Manfred Jaeger is an Associate Professor at the Department of Computer Science, Technical Faculty of IT and Design, Aalborg University. His research focuses on Artificial Intelligence , Bayesian Networks , and Graph Neural Networks , with significant contributions to probabilistic reasoning and relational learning. University: Aalborg University School: Technical Faculty of IT and Design Department: Department of Computer Science Jaeger's research explores inductive and probabilistic reasoning , statistical relational learning , and model checking . His recent work integrates heterogeneous graph neural networks with relational Bayesian network encodings to enhance reasoning capabilities in complex systems. Key trends in his publications include relational deep learning , probabilistic inference , and graph-based modeling . He has contributed to applications in social network community detection , reinforcement learning for MDPs , and latent variable models for graph learning . Jaeger collaborates on projects involving incomplete data analysis , modularization of complex tasks , and probabilistic logic . His datasets on multi-multi-instance learning networks are publicly available for research use.

Svante EriksenView profile

Associate Professor

• Statistics
• Bayesian Networks
• Graphical Models
• +7 more

Svante Eriksen is an Associate Professor in the Department of Mathematical Sciences at Aalborg University, Faculty of Engineering and Science. His research spans statistics, forensic genetics, and computational modeling, with a focus on Bayesian networks, graphical models, and statistical methods for forensic DNA analysis. He is actively involved in interdisciplinary research and software development for probabilistic genotyping and large-scale inference. Research Interests: Bayesian Networks and Graphical Models Statistical Methods in Forensic Genetics SNP and Y-STR Genotyping Data Mining and Knowledge Discovery Model Selection and Context-Specific Independence Software Development for Statistical Inference Recent Publication Trends (2024–2025): His recent work focuses on improving SNP genotyping accuracy using logistic regression models, developing efficient software (jti and sparta) for Bayesian network inference, and advancing forensic DNA analysis through dynamic SNP selection and probabilistic modeling of Y-STR databases. These contributions reflect a strong integration of statistical theory, computational efficiency, and real-world forensic applications. Scientific Contributions: Principal contributor to software packages for Bayesian network prediction. Developer of statistical models for forensic DNA data interpretation. Collaborator on projects involving digital learning analytics and student retention. Advising and Grants: While specific student names are not listed, the profile indicates involvement in PhD supervision (4 cases). He has participated in multiple externally funded research projects, including those supported by Novo Nordisk and Danish research councils, focusing on forensic DNA analysis, graphical models, and educational data mining. Research Groups and Collaborations: He is part of a strong research network in forensic genetics and statistical modeling at Aalborg University, collaborating with leading researchers such as N. Morling, M. M. Andersen, and T. Tvedebrink. His work is closely tied to the development and application of statistical software in both forensic and educational domains.

Lasse Thurmann JørgensenView profile

Researcher

• Ultrasound Imaging
• Biomechanics
• Medical Imaging
• +3 more

Lasse Thurmann Jørgensen is a postdoctoral researcher at the Department of Health Technology, Technical University of Denmark. He specializes in ultrasound imaging and biomechanics, with a focus on synthetic aperture ultrasound, pressure gradient estimation, and volumetric imaging techniques. His work involves advanced signal processing, computational fluid dynamics, and GPU-accelerated algorithms for real-time medical imaging applications. Research Interests : Ultrasound imaging, biomechanics, synthetic aperture ultrasound, pressure gradient estimation, computational fluid dynamics, volumetric beamforming. Key Collaborations : Collaborates with researchers in Denmark and internationally on ultrasound technology and biomedical engineering projects. Patents : Co-inventor of an ultrasound imaging apparatus patent addressing intravascular pressure measurement.

Søren KnudsenView profile

Assistant Professor

• Information Visualization
• Human-Computer Interaction
• Data Visualization
• +3 more

Søren Knudsen is an Assistant Professor at the Digital Design Department, IT University of Copenhagen and holds a Marie Curie Fellowship for postdoctoral work at the University of Copenhagen. He serves as Academic Director of the Human Data Interaction Lab. Positions: Assistant Professor, Marie Curie Postdoctoral Scholar Affiliations: IT University of Copenhagen, University of Copenhagen Key Roles: Academic Director, Human Data Interaction Lab His research centers on information visualization and human-computer interaction , particularly in face-to-face and online contexts. He explores how large-area displays and social media can enhance data comprehension and collaborative discussion. Notable work includes surveys on interactive visualization techniques for large displays, frameworks for data visualization education , and EMR-based algorithms for healthcare performance evaluation. His publications span journals like IEEE Transactions on Visualization and Computer Graphics and PLOS ONE . Awards and honors: Marie Curie Fellowship He collaborates across disciplines, with ties to healthcare analytics, educational technology, and computer science departments. His recent studies address challenges in visualization design handoff , proxemics , and ubiquitous data interaction .

Dario ParigiView profile

Associate Professor

• Structural Engineering
• Sustainable Construction
• Timber Reuse
• +5 more

Dario Parigi serves as Associate Professor, Head of Division, and Head of Research Group within the Department of the Built Environment at Aalborg University's Faculty of Engineering and Science. He leads the Sustainable Structures, Materials and Construction Research Group and maintains an active research profile with 43+ publications and 5 major projects including the active Instant Urbanism initiative. His work bridges structural engineering, sustainable design, and computational methodologies. Parigi's research spans timber reuse optimization , reciprocal structural systems , and multi-dimensional form-finding , with recent focus on carbon metrics for reused timber and kinetic adaptive facades. His fingerprint analysis reveals strong connections to Design Process (100%), Form Finding (83%), and Reciprocal Structures (64%), demonstrating consistent thematic focus across two decades of work. Analysis of his 15 most recent publications shows increasing emphasis on circular construction (2021-2022), with 60% addressing timber reuse challenges and optimization methodologies. Earlier works (2015-2018) established foundational frameworks for reciprocal structures and computational design tools, evolving toward integrated sustainability metrics in recent output. 5 million DKK research grant for timber reuse (2024) Det Obelske Familiefond funding for Utzon(x) Research-by-design Multiple media features in Danish press (2024) regarding sustainable construction research As Principal Investigator for projects like Lightweight structural elements and Skolernes Indeklima, Parigi secures significant research funding while mentoring junior researchers through 14 documented activities including conference presentations and workshop leadership. His Urban Tranquility project demonstrates interdisciplinary collaboration across environmental and structural domains. Parigi directs the Sustainable Structures, Materials and Construction Research Group where his team develops innovative approaches to structural reciprocity and material reuse. Current focus includes the Parigi Mechanism for adaptive facades and computational frameworks for minimal-waste timber layouts, with recent press coverage highlighting real-world applications of their research.