جست‌وجوی استاد و پژوهشگر

Dario Parigiمشاهده پروفایل

دانشیار

• Structural Engineering
• Sustainable Construction
• Timber Reuse
• +۵ مورد دیگر

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.

Stefanie Zollmannمشاهده پروفایل

دانشیار

• Visual Computing
• Augmented Reality
• Virtual Reality
• +۳ مورد دیگر

Stefanie Zollmann is an Associate Professor at the Department of Computer Science, Aarhus University. Her primary research focuses on Visual Computing, Augmented Reality, and Virtual Reality, with applications in immersive education and sports technology. She has contributed to advancements in 3D modeling, scene reconstruction, and hybrid XR systems. Her work spans technical innovations in virtual environments, including semantic-controlled rendering, panorama inpainting, and mobile sports coaching systems. She has also contributed to conference organization, serving as a Program Chair for IEEE VR 2024. Zollmann's recent publications address challenges in user localization for AR, immersive teaching via 360° storytelling, and hybrid sports spectator experiences. Her research emphasizes practical applications in education and sports, leveraging both hardware and software advancements. Collaborations include projects on situated sports coaching, mobile capture systems, and tabletop XR interfaces. While no awards are listed, her active participation in top-tier conferences underscores her scholarly impact.

Andres Masegosaمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Networks
• Data Streaming
• +۴ مورد دیگر

Andres Masegosa is an Associate Professor at the Department of Computer Science, Aalborg University (AAU), within The Technical Faculty of IT and Design. He is actively involved in the DarkScience project (2022–present), focusing on metagenomic binning and microbial dark matter analysis. His research interests span Bayesian networks, machine learning, probabilistic graphical models, and educational methodologies in computer science instruction. Key research contributions include advancements in PAC-Bayes theory, genome representation learning, and cold posterior effects in Bayesian models. He has published extensively in top venues like Advances in Neural Information Processing Systems and Transactions on Machine Learning Research. His work often bridges theoretical contributions with practical applications in genomics and education. Masegosa leads the development of tools like InferPy for probabilistic modeling and has contributed to open-source projects such as the AMIDST toolbox. His educational research explores learning styles and active learning strategies, emphasizing live coding and programming exercises. Collaborations include interdisciplinary projects with microbiologists and data scientists, reflecting his expertise in computational methods for complex biological systems. His research portfolio demonstrates a strong focus on scalable probabilistic methods and their real-world applications.

Anne Marie Svaneمشاهده پروفایل

دانشیار

• Topological Data Analysis
• Probability Theory
• Mathematical Statistics
• +۳ مورد دیگر

Anne Marie Svane is an Associate Professor at the Department of Mathematical Sciences, Aalborg University, specializing in topological data analysis, stochastic geometry, and probability theory. Her research bridges theoretical mathematics with applied statistics, focusing on geometric functionals and computational methods. Education: PhD in Mathematics from Aarhus University. Her recent work explores cobordism obstructions, Gibbs processes, and applications in climate science and medical research. Key contributions include: Advancing kernel persistence methods for topological data analysis. Developing central limit theorems for spatial point processes. Modeling moisture dynamics in building physics with climate data. Investigating the interplay between digital algorithms and geometric structures. She collaborates on interdisciplinary projects like AI-Aalborg Intelligence and contributes to educational initiatives such as Girls' Day in Science.

Hao Liمشاهده پروفایل

پژوهشگر ارشد

• Topology Optimization
• Mechanical Engineering
• Thermal Systems
• +۲ مورد دیگر

Hao Li is a MSCA Postdoc Fellow and Visiting Scholar at LIP6 , affiliated with the University of Southern Denmark in the Department of Mechanical Engineering . His research focuses on advanced computational methods for topology optimization in thermal, fluid, and structural engineering systems. Education: Not explicitly stated in the provided text. Current Projects: Leading EU-funded research on heat exchanger design using multiscale models and machine learning. Dr. Li's work spans multiscale topology optimization, level-set methods, and fluid-structure interaction, with applications in microchannel cooling, compliant mechanisms, and biodegradable composites. His recent publications highlight advancements in 3D conjugate heat transfer, adaptive meshing, and eigenfrequency maximization. The trends in his research output (2017–2025) emphasize thermal-fluid systems , high-resolution structural optimization , and manufacturable composite designs . Notable subfields include triply periodic minimal surfaces for cooling channels, nonlinear buckling analysis, and phasor-based dehomogenization techniques. Teaching & Supervision: Currently supervising projects on topology optimization frameworks for heat sinks and high heat flux cooling. His past projects (2018–2023) include research on piezoelectric transducers and thermal-fluid system design. Labs & Collaborations: Collaborates with institutions in Japan and France, focusing on experimental validation and industrial applications. His network includes partnerships with researchers in structural mechanics, computational fluid dynamics, and additive manufacturing.

Peter Vistisenمشاهده پروفایل

دانشیار

• User-Centered Innovation
• Design Thinking
• Digital Innovation
• +۱۲ مورد دیگر

Peter Vistisen is an Associate Professor at the Department of Communication and Psychology, Faculty of Social Sciences and Humanities, Aalborg University, Denmark. His interdisciplinary work bridges information technology and the liberal arts, with a focus on user-centered innovation, digital media, and design thinking. He is affiliated with InDiMedia (Centre for Interactive Digital Media & Experience Design) and involved in the MASSHINE research initiative. His research interests include: User-centered innovation and design thinking Digital innovation and strategic design Animation and sketching as tools in the innovation process Metaverse and experience technologies AI for the People and ethical digital design Interactive digital media in everyday life His recent publications reflect a strong trend toward interdisciplinary research combining digital media, health communication, sustainability, and cultural storytelling. Key themes include the use of animation in health and climate communication, XR onboarding systems, museum metaverses, and the domestication of digital tools in everyday life. His work often involves collaborative, user-driven design and explores how emerging technologies can be made accessible and meaningful. Scientific awards include: Årets Underviser (Teacher of the Year), 2020 Årets Brøl: Best App/Mobile Website, 2014 MÆRKK Prize: Best Master’s Thesis, 2011 He actively supervises students and leads research projects in digital innovation, public engagement, and experience design. His grants and projects often involve cross-sector collaboration with healthcare, cultural institutions, and public organizations. He is involved in multiple research centers and initiatives, including InDiMedia and MASSHINE, and frequently contributes to academic conferences, workshops, and public media discussions on digital culture and design. Notable research teams and labs: InDiMedia (Centre for Interactive Digital Media & Experience Design) MASSHINE Collaborative projects with healthcare and cultural sectors

• Probabilistic Graphical Models
• Machine Learning
• Deep Generative Models
• +۷ مورد دیگر

Thomas Dyhre Nielsen is a Professor (MSO) in the Department of Computer Science at Aalborg University . He is a member of the Distributed, Embedded and Intelligent Systems (DEIS) research group and contributes to the Artificial Intelligence and Machine Learning team at the university. His primary research interests lie in the theoretical and applied aspects of probabilistic graphical models , machine learning , and deep generative models . His work spans from foundational methods for learning and inference to the development of frameworks for solving complex decision problems. He is the co-author of the authoritative textbook Bayesian Networks and Decision Graphs . His recent research output reveals a strong trend towards interdisciplinary applications. His 15 most recent publications demonstrate significant work in bioinformatics , using graph neural networks and variational autoencoders for metagenomic binning, and in urban infrastructure , applying reinforcement learning and probabilistic models to optimize stormwater and wastewater management systems. He also has impactful research in healthcare , developing Bayesian network models for clinical risk prediction. Senior area editor for the International Journal of Approximate Reasoning . Principal or Co-Investigator on research projects such as the AMIDST project (developing a Java toolbox for scalable probabilistic machine learning) and PGM 2020 (organizing the International Conference on Probabilistic Graphical Models). Actively supervising research, as evidenced by a current opening for a PostDoc position in probabilistic machine learning. Professor Nielsen leads a research lab focused on probabilistic machine learning, which is part of the larger DEIS and AI/ML teams at Aalborg University. His group develops and applies advanced models to real-world problems in environmental science, healthcare, and intelligent systems.

Heidi Hautoppمشاهده پروفایل

دانشیار

• Visual Methods
• Design Approaches
• Hybrid Learning Formats
• +۵ مورد دیگر

Heidi Hautopp is an Associate Professor at the Department of Culture and Learning, Faculty of Humanities and Social Sciences, Aalborg University, Copenhagen. Her work integrates visual methods and design approaches in higher education and organizational contexts, with a focus on hybrid teaching formats through the Nordic Visual Studies and Art Education (NoVA) master's program. PhD from Aalborg University (2018-2022) on graphic facilitation Teaches IT, learning and organizational change (ILOO), Learning and change processes (LFP), and Communication and digital media programs Co-founder of the Danish Play Think Tank promoting creative approaches in education Her research examines how visual tools like graphic facilitation and video prototyping can drive educational innovation. Recent work explores AI image generation in design and hybrid PBL models for arts education. Publications span both empirical studies and methodological frameworks. Principal investigator in projects like Emergency AI and Sustainable Development Lab Active in conferences on networked learning and arts-based research Collaborates across disciplines including organizational development and sustainability

Kristian G. Olesenمشاهده پروفایل

دانشیار

• Bayesian Networks
• Artificial Intelligence in Medicine
• Medical Decision Making
• +۳ مورد دیگر

Kristian G. Olesen is an Associate Professor in the Department of Computer Science at Aalborg University, affiliated with The Technical Faculty of IT and Design. His work focuses on probabilistic graphical models, medical decision support systems, and Bayesian network applications in healthcare. Research Interests : Olesen specializes in Bayesian networks and their applications in medicine, including temporal reasoning for diagnoses (e.g., Lyme disease), home care delivery optimization, and emergency department patient flow prediction. His methodologies emphasize online updating algorithms and modularization of complex tasks. Professional Activities : He serves on the board of Hugin Expert A/S since 1989 and Folkeuniversitetet i Aalborg from 2018–2022. His projects include collaborations on medical decision support systems and normative systems with Hewlett Packard (1998–2003). Media Engagement : Olesen has been featured in media discussions on AI ethics (e.g., robot regulation in 2016) and institutional achievements, including the recognition of Aalborg University’s computer science institute as world-class in 2017.

Anders Nymark Christensenمشاهده پروفایل

دانشیار

• Image Analysis
• Computer Vision
• Medical Imaging
• +۷ مورد دیگر

Anders Nymark Christensen is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing. His work bridges computer vision, medical imaging, and materials science, with a strong focus on explainable AI in clinical applications and structural analysis of complex materials. Institution: Technical University of Denmark (DTU) School: Department of Applied Mathematics and Computer Science Department: Visual Computing Role: Associate Professor Christensen’s research interests include image analysis, computer vision, explainable AI, ultrasound imaging, fetal medicine, and fiber orientation in composites. He applies advanced computational techniques to solve real-world problems in healthcare and materials engineering, particularly through structure tensor analysis and deep learning. His recent publications highlight a strong trend in developing AI tools for clinical decision support in fetal medicine, structural analysis of food and composite materials, and ultrasound imaging. These works span journals such as Scientific Reports , Food Structure , and IEEE Access , reflecting interdisciplinary innovation. Clinical validation of explainable AI for fetal growth scans Characterization of anisotropy in mozzarella cheese Determining fetal orientations from ultrasound video Structure tensor analysis in composites He supervises several PhD students in projects related to AI in skin lesion analysis, cancer detection, and ultrasound imaging. His collaborative network includes key researchers at DTU such as Anders Bjorholm Dahl, Vedrana Andersen Dahl, and Mads Nielsen. He has been involved in significant research grants and is active in both medical and engineering domains, contributing to open datasets and reproducible research. Christensen leads and contributes to numerous active projects, including: Decision Support AI for Skin Lesions (2024–2027) Fighting Cancer with Generative AI (2024–2027) SONAI: Explainable AI in the Clinic (2022–2026) Deep learning for identifying biomarkers in medical images (2022–2025) His work supports UN Sustainable Development Goals related to health, innovation, and responsible consumption, particularly through advancements in medical diagnostics and sustainable materials.

Donya Sheikh Khanمشاهده پروفایل

پژوهشگر

• Indoor Air Quality
• Energy Conservation
• Occupant Feedback Systems
• +۷ مورد دیگر

Donya Sheikh Khan is a postdoctoral researcher at the Technical University of Denmark (DTU), Department of Civil and Mechanical Engineering, specializing in Energy and Services. Her research focuses on improving building performance and occupant comfort through innovative technologies such as IoT-based data acquisition and occupant voting systems. Education: Master of Science in Architectural Engineering, Aarhus University (2010–2016) Ph.D. in Building Science, Technical University of Denmark (2018–2021) Her research interests lie at the intersection of sustainable building design, indoor environmental quality, and human-building interaction. She explores how real-time occupant feedback and sensor networks can enhance thermal comfort, indoor air quality, and energy efficiency in office environments. Her work heavily involves field studies, user interface design, and data-driven building optimization. The most recent publications reflect a consistent trend in occupant-centric building control, emphasizing IoT integration, spatial sensor distribution, and user satisfaction through interactive feedback systems. These studies are primarily applied in office buildings and contribute to sustainable urban development and energy conservation. Scientific Awards: BEST RESEARCH-IN-PROGRESS PAPER AWARD - ECIS 2019 She has been involved in significant research projects, including an Industrial Ph.D. project on IoT-based data acquisition for high-performing buildings, supervised by experts at DTU. Her external engagements include presenting at international conferences, organizing workshops, and contributing to public discourse on urban air quality. She also served as a visiting researcher at Carnegie Mellon University, indicating strong international collaboration. Labs and Research Teams: She is affiliated with the CONSTRUCT research group at DTU (http://www.construct.dtu.dk), which focuses on sustainable construction and building services engineering.

Søren Wengel Mogensenمشاهده پروفایل

دانشیار

• Causal Inference
• Stochastic Processes
• Survival Analysis
• +۳ مورد دیگر

Søren Wengel Mogensen is an Associate Professor at the Department of Finance, Copenhagen Business School, Denmark. His research focuses on developing advanced statistical and machine learning methodologies for complex systems analysis. Research Interests: Dr. Mogensen's work spans causal inference, stochastic processes, survival analysis, and time-series modeling. Key themes include: Causal discovery algorithms for industrial and biological systems Graphical representations of dependencies in high-dimensional data Time-varying mediation in survival contexts Bayesian networks for cascade modeling Publication Trends: His recent articles (2021-2025) demonstrate a strong emphasis on theoretical-statistical innovation with applications in healthcare, industrial monitoring, and computational finance. Dominant methodologies include kernel-based independence tests, continuous-time Bayesian networks, and constrained stochastic process modeling.

Vedrana Andersen Dahlمشاهده پروفایل

دانشیار

• Geometry Processing
• Image Analysis
• Computer Vision
• +۳ مورد دیگر

Vedrana Andersen Dahl is an Associate Professor at the Technical University of Denmark (DTU), Department of Applied Mathematics and Computer Science. Her research focuses on image analysis and geometry processing, including geometric texture analysis, deformable models, and tomographic data processing. She holds a PhD in Image Analysis and Computer Graphics from DTU (2007–2011), an MSc in IT from the IT University of Copenhagen (2005–2007), and a Diploma in Mathematics and Physics from the University of Zagreb (1992–1999). PhD: Technical University of Denmark (2007–2011) MSc: IT University of Copenhagen (2005–2007) Diploma: University of Zagreb (1992–1999) Her research interests span geometric texture analysis, deformable models, OCT data processing, and medical imaging applications. She has contributed to projects such as the Villum Experiment Grant (2022) and collaborates internationally on topics like placental tomography and fibrous composite analysis. Dahl supervises multiple PhD students in areas like medical image segmentation and X-ray imaging techniques. She has authored over 100 publications, with recent work focusing on 3D tomography, medical imaging, and machine learning applications. Her datasets, including BugNIST and STXAE, are widely used in academic and industrial research. Dahl also serves on review committees at institutions like the University of Copenhagen and University College Copenhagen.

Christoph Seidlمشاهده پروفایل

دانشیار

• Software Engineering
• Virtual Reality
• Software Visualization
• +۵ مورد دیگر

Christoph Seidl is an Associate Professor in the Department of Software Engineering at the IT University of Copenhagen. His research focuses on software visualization, software archaeology, and the application of virtual reality in software engineering tasks. He leads the Immersive Software Archaeology project, exploring collaborative systems and legacy system analysis in virtual environments. Key research areas include software product lines, feature modeling, and model-driven development. Seidl has received awards such as the SoSyM Best Reviewer Award (2018) and SPLC'19 Distinguished Reviewer Award (2019). His work emphasizes innovative tools for software exploration, including immersive 3D visualization and collaborative note-taking systems in VR. He has published extensively on topics like variability management, configuration testing, and domain-specific languages. Research trends in his articles highlight advancements in using VR for software archaeology, collaborative software exploration, and methodologies for managing software evolution. His projects address challenges in legacy system understanding, feature model synthesis, and automated testing for configurable systems. Seidl collaborates internationally, with projects funded by the Independent Research Fund Denmark. His contributions span academic publications, datasets (e.g., VaMoS 2022 artifacts), and tool development for software product line engineering.

• Data Science
• Machine Learning
• Forensic Science
• +۳ مورد دیگر

Therese Graversen is an Associate Professor of Data Science and Head of the BSc in Data Science Programme at the IT University of Copenhagen. Her research focuses on forensic science , DNA analysis , and computing education . She leads two major research projects funded by the Independent Research Fund Denmark: Statistical and Computational Aspects of Forensic Identification using DNA (2019–2020) A Unified Statistical Framework for Complex Forensic DNA Evidence (2022–2027) Her work bridges Bayesian networks , graphical models , and educational strategies , with notable contributions to improving gender representation in computing education. Recent collaborations include predictive maintenance in pharmaceutical industries and analysis of high-profile criminal cases via advanced DNA methodologies. Media engagements highlight her role as an expert in forensic DNA advancements.