جست‌وجوی استاد و پژوهشگر

Søren Overgaardمشاهده پروفایل

دانشیار

• Philosophy of Mind
• Phenomenology
• Metaphilosophy
• +۳ مورد دیگر

Søren Overgaard is an Associate Professor at the Department of Communication , Faculty of Humanities , University of Copenhagen, and a core member of the Center for Subjectivity Research . His work bridges phenomenology , philosophy of mind , and metaphilosophy , with a focus on perceptual experience, intersubjectivity, and metaphilosophical methodology. Areas of Specialization : Philosophy of Mind (Perception, Social Cognition), Phenomenology, Metaphilosophy, Wittgenstein Studies Education : PhD in Philosophy (2002, University of Aarhus), MA in Philosophy (1998), BA in Philosophy (1996) Research Interests center on perceptual experience , including disjunctivism, naive realism, and the phenomenology of hallucination/illusion. He integrates Husserl’s phenomenology , Merleau-Ponty’s embodiment theories , and Wittgenstein’s ordinary language philosophy to address questions about consciousness, social cognition, and the nature of philosophical methodology. Recent Publications include peer-reviewed articles on perceptual occlusion, backlighting, and the vertical-horizontal illusion in journals like Synthese , Mind , and Erkenntnis , as well as chapters in edited volumes on empathy, enactivism, and phenomenological approaches to psychopathology. His authored books include En verden af indtryk (2023) and An Introduction to Metaphilosophy (2013), translated into Korean and Turkish. Scientific Awards : 2020: Einar Hansen’s Research Foundation Prize for Outstanding Humanistic Research (SEK 150,000) Grants include a 2024-26 6,183,000 DKK grant from the Independent Research Fund Denmark for Mapping Perceptual Presence , and prior grants from the Danish National Research Foundation, Research Councils UK, Carlsberg Foundation, and others. Leadership and Service roles: Deputy Head of Department for Research (2024–), Director of the MA Programme in Cognition and Communication (2020–2022), President of the Nordic Society for Phenomenology (2017–2023), and editorial roles for journals and book series like Routledge Research in Phenomenology .

Henrik Schønau Fogمشاهده پروفایل

دانشیار

• Media Research
• Adaptive Interactive Storytelling
• Computer Games
• +۹ مورد دیگر

Henrik Schønau Fog is an Associate Professor and Deputy Head of Department at Aalborg University's Department of Architecture, Design and Media Technology, part of The Technical Faculty of IT and Design. His research focuses on interactive storytelling, game design, and educational technology, with a particular emphasis on adaptive narratives, player engagement, and serious games. He leads initiatives such as the Center for Applied Game Research (CEAGAR) and the SMILE Lab, exploring real-time filmmaking, virtual reality, and gamification in education. His work bridges theory and practice, addressing challenges in interactive media, climate awareness through games, and improving learning outcomes via purposive game development. Key projects include AGAVE (AI-Driven Game Adaptation for Virtual Environments) and ViZARTS (Visualization and Adaptive Real-Time Storytelling). Fog has authored over 60 publications, with notable contributions in adaptive narratives, emotional response analysis, and educational game frameworks. He has received prestigious awards, including Best Paper recognitions at HCI in Games and Interactive Storytelling conferences. His teaching portfolio emphasizes problem-based learning and hybrid educational models, fostering technical and collaborative skills through game development courses. Fog collaborates internationally, engaging with institutions like Arizona State University and contributing to media innovations showcased in film, virtual reality, and interactive installations. His research also extends to measuring workplace well-being via wearable technology and enhancing museum experiences through immersive VR interfaces.

• Combustion
• Microscale Systems
• Laser Diagnostics
• +۴ مورد دیگر

Christopher Cadou is a Professor and Director of Undergraduate Studies in the Department of Aerospace Engineering at the University of Maryland. He holds a B.S. in Mechanical Engineering and B.A. in History from Cornell University, and M.S. and Ph.D. in Mechanical Engineering from UCLA. His research focuses on combustion at micro and conventional scales, laser diagnostics, compact power systems, and fuel cells. He has led interdisciplinary projects in micro-gas turbine engines, microfluidics, and energy innovation. Professional affiliations include the American Society of Mechanical Engineers (ASME), American Institute of Aeronautics and Astronautics (AIAA), and The Combustion Institute. He has reviewed for journals like Combustion and Flame, and government agencies such as the National Science Foundation. His work includes pioneering infrared diagnostics for micro-combustors and developing analytical models for heat transfer in mini/microchannels. He has organized conferences including the 2009 AIAA Joint Propulsion Conference. His contributions span technical reports on microturbomachinery and scramjet inlet flows, and collaborations with industry through initiatives like the Maryland Energy Innovation Institute.

Daniel S. Hainمشاهده پروفایل

دانشیار

• Data Science
• Network Analysis
• Machine Learning
• +۷ مورد دیگر

Professor Daniel S. Hain is an Associate Professor at Aalborg University Business School, part of Aalborg University's Faculty of Social Sciences and Humanities. He is affiliated with the IKE Research Group (AI for the People) and the MASSHINE Cluster for Research on Innovation and Development. His research focuses on innovation dynamics, artificial intelligence, network analysis, and technology forecasting. Hain has been actively involved in strategic initiatives such as the Danish Industry Foundation's AI Denmark program and the Generative Ethnographic AI (GE-AI) seed project, demonstrating his commitment to advancing AI applications in societal contexts. His work bridges academic research with practical industry challenges, particularly in areas like patent analytics (e.g., Patentsberta model), renewable energy innovation, and global venture capital patterns in developing economies. Hain has received the OECD IPSDM “Big Data Analytics” Challenge award (2018) for collaborative research on inventive activity visualization. He contributes to policy discussions on AI governance, the privatization of research talent, and regional green technology development. Key projects include the Danish Research Unit for Industrial Dynamics (DRUID) since 1995, exploring innovation systems, and the EIS project on energy innovation competitiveness. Hain’s recent focus on generative AI ethics and SME predictive analytics reflects his dual expertise in technical methodologies and socio-economic impacts.

Anna Rogersمشاهده پروفایل

دانشیار

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Anna Rogers is an Associate Professor of Data Science at the IT-University of Copenhagen , affiliated with the NLPnorth research group. Her work focuses on Natural Language Processing (NLP) , Artificial Intelligence , and Large Language Models (LLMs) , with a particular emphasis on ethical data use, peer review innovation, and transformer model analysis. She leads projects addressing AI transparency, medical QA hallucinations, and generative AI applications. Her research explores topics including: LLM behavior and evaluation Data governance in NLP Peer review systems optimization Transformer model robustness Medical AI applications Key Projects : PlagAIrism : Tracking LLM training data origins Pioneer Centre for AI : Pre-registered replication studies TinyGPT : Efficient NLP models AIInterviewer : Large-scale qualitative data collection Publications span ACL , EMNLP , and specialized NLP workshops, addressing topics from BERT analysis to AI content farms.

Markus Strohmaierمشاهده پروفایل

استاد

• Computational Social Science
• Data Science
• Machine Learning
• +۷ مورد دیگر

Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences. University of Mannheim – Chair for Data Science in the Economic and Social Sciences GESIS – Scientific Coordinator for Digital Behavioral Data Complexity Science Hub Vienna – External Faculty Former Professor at RWTH Aachen University and University of Koblenz-Landau Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology His research focuses on computational social science , algorithmic fairness , network science , and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies. The recent articles reflect a strong trend in studying inequality in algorithmic systems , governance in decentralized organizations (DAOs) , and psychological profiling of AI . His work spans high-impact journals like Nature and Scientific Reports , emphasizing fairness, transparency, and societal impact of data-driven technologies. Notable scientific contributions include: Editor-in-Chief of EPJ Data Science (2018–2022) Founding co-chair of the Computational Social Science section of the German Informatics Society He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure. His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity , which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.

Ginés Carreto Picónمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Signal Processing
• Artificial Intelligence of Things
• +۳ مورد دیگر

Ginés Carreto Picón serves as a Research Fellow within the Department of Electrical and Computer Engineering at Aarhus University, Denmark, specializing in the Signal Processing and Machine Learning research group. His work focuses on developing computationally efficient AI solutions for resource-constrained environments. His research expertise spans machine learning, signal processing, and artificial intelligence of things (AIoT), with emphasis on creating high-performance sequence processing models through continual learning frameworks, dimensionality reduction, and low-rank approximation techniques. These approaches significantly reduce energy consumption while maintaining model accuracy for edge deployment. His publication on visual fingerprinting for sequential data demonstrates his focus on interpretable pattern recognition methods. Current work centers on the 2024-2027 PhD project developing lightweight AI architectures specifically optimized for IoT devices, aiming to expand feasible AI applications in constrained computational environments. He actively contributes to the Signal Processing and Machine Learning laboratory's research ecosystem, advancing methodologies for practical implementation of efficient AI systems in real-world edge computing scenarios.

Leon Derczynskiمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Misinformation Detection
• +۳ مورد دیگر

Leon Derczynski is an Associate Professor of Computer Science at the IT University of Copenhagen , with a dual role as Principal Research Scientist/LLMSEC at NVIDIA . He leads the Strømberg NLP research group and coordinates NLP South at ITU, while also being affiliated with the Machine Learning group. Specializes in Natural Language Processing , Machine Learning , and LLM security Focus on Misinformation detection , Clinical text mining , and Danish language technology Research grants include Verif-AI (2.9M DKK), ClinRead (544K DKK), and LITHME (EU COST action, €11K). He has coordinated major projects like COMRADES and PHEME , and contributed to uComp and TrendMiner . Scientific recognition includes the University of Sheffield Exceptional Contribution Award (twice), WEBIST Best Student Paper award , and FP7 funding . His technical work includes the garak.ai LLM vulnerability scanner and generalised-brown clustering library. Actively supervises students and maintains numerous GitHub repositories (86 public projects) related to NLP, machine learning, and computational linguistics. He has delivered keynotes and guest lectures , including at Innopolis University (Russia) and PET (Danish Security and Intelligence Service).

• Science and Technology Studies
• Digital Methods
• Generative AI for Social Research
• +۵ مورد دیگر

Anders Kristian Munk is a Professor at DTU Management, Technical University of Denmark, based in the Department of Technology, Management and Economics within the Division for Technology and Business Studies. His research focuses on the critical intersection of technology and society through Science and Technology Studies (STS) and advanced digital methodologies. His primary research domains include: Generative AI integration in social research Digital methods development (notably data sprints) Controversy mapping of sociotechnical issues Computational ethnography and network analysis Critical examination of data imaginaries Urban studies through computational visual methods Recent publications (2023-2025) demonstrate a strategic pivot toward generative AI applications, with significant contributions in developing AI-native research frameworks like synthetic interlocutors and irreductionist mapping. His work uniquely bridges STS theory with practical tool development, exemplified by Gephisto for critical network analysis. Key application areas span public health (e.g., inflammatory bowel disease trend analysis in Africa), cultural industries (film audience analytics), and urban studies (pandemic place attachments). Prof. Munk co-developed the data sprint methodology for collaborative controversy mapping and has contributed to major projects including Climaps and EMAPS. His interdisciplinary approach combines social science rigor with computational innovation through partnerships across computer science, design, and domain-specific fields. Current work emphasizes ethical AI integration and methodological adaptation for complex sociotechnical challenges.

Mohammad Naser Sabet Jahromiمشاهده پروفایل

استادیار

• Explainable Artificial Intelligence
• Biometrics
• Machine Learning
• +۴ مورد دیگر

Mohammad Naser Sabet Jahromi is an Assistant Professor at the Department of Architecture, Design and Media Technology, Aalborg University, Denmark. He is affiliated with the Visual Analysis and Perception Centre for AI Ethics, Law and Policy. His research focuses on explainable AI (XAI), biometrics, machine learning, and ethical AI applications in legal and medical domains. He actively participates in interdisciplinary projects like REPAI: Responsible AI for Value Creation (2023-2027), which explores AI ethics, computational discourse analysis, and value-driven AI systems. His educational background is not explicitly detailed in the provided text, but his research trajectory indicates strong expertise in computer science and AI systems. Key research interests include interpretable machine learning models, privacy-preserving biometric systems, and AI applications in asylum adjudication and educational assessment. Recent work emphasizes developing XAI frameworks like SIDU-TXT for NLP, verifying machine unlearning mechanisms, and automating large-classroom assessments. His projects bridge technical AI advancements with societal implications through collaborations with legal and ethical scholars. Notable contributions include datasets evaluating XAI methods in medicine and methodologies for transparent AI decision-making. He has participated in conferences such as ICPR 2024 and JURISIN 2023, showcasing interdisciplinary research impact.

Sylvia von Wallpachمشاهده پروفایل

استاد

• Brand Co-creation
• Interpretative Consumer Research
• Luxury Branding
• +۳ مورد دیگر

Sylvia von Wallpach is Professor with Special Responsibilities at Copenhagen Business School's Department of Marketing. Her research focuses on brands as social processual phenomena, multi-stakeholder brand co-creation, and qualitative method development. She serves as Associate Editor for Marketing at the European Management Journal and organizes the EMAC Climber Community. Her research on luxury experiences, brand identity, and consumer behavior has received international recognition including the Social Science Space Impact Award. Dr. von Wallpach teaches courses on Applied Strategic Brand Management and New Frontiers in Branding, employing blended and online formats. She holds Senior Fellowship of the Higher Education Academy and supervises Master's theses and doctoral candidates in brand-related research areas.

Andreas Birkbakمشاهده پروفایل

دانشیار

• Digital Publics
• Environmental Humanities
• Journalism and Democracy
• +۳ مورد دیگر

Andreas Birkbak is an Associate Professor at Roskilde University (RUC), specializing in digital publics, environmental humanities, and science studies. Previously, he worked at Aalborg University (AAU), where he co-founded TANTlab, a research group combining ethnographic and digital methods. He holds a Ph.D. in Science & Technology Studies from AAU, an MSc in Sociology from the University of Copenhagen, and additional training in Internet Studies from the University of Oxford. His research focuses on how publics are formed in high-tech and digitized societies, with a particular emphasis on democratic practices and digital methodologies. Key projects include studies of algorithmic governance, social media controversies, and participatory data design. He has published widely on topics like Facebook's algorithmic influence, crisis communication, and democratic situations. Notable awards include the Freeman Award (2024), Teacher of the Year (2020), and the Ziman Award (2020). Birkbak actively contributes to media commentary on digital democracy and advises initiatives such as the AdvanCing a Democratic Digital Culture Project. His teaching focuses on techno-anthropology and journalism education. Current research activities include evaluating national documentation practices (EvaluNation project), exploring AI development ethics, and analyzing social media dynamics in political campaigns. He co-leads the Digital Media Lab at RUC, producing reports on topics like the 2024 European Parliament election campaigns on Facebook.

Michael Hockenhullمشاهده پروفایل

استادیار

• Science and Technology Studies (STS)
• Ethnography
• Data Visualization
• +۹ مورد دیگر

Michael Hockenhull is an Assistant Professor at the IT University of Copenhagen (ITU), affiliated with the Department of Technologies in Practice. His work focuses on interdisciplinary research at the intersection of Science and Technology Studies (STS), Digital Humanities, and political economy. He explores topics such as data infrastructure governance, speculative design, and the societal implications of digitalization through ethnographic and visual analytic methods. He has contributed to two major research projects: SSH and Sustainable Business (2021–2023, Carlsberg Foundation) and Data as Relation (2016–2021, Velux Foundation), both emphasizing digitalization, corporate sustainability, and sociotechnical systems. His recent publications (2020–2024) reflect a growing interest in climate technology advocacy, feminist digital methodologies, and critical analyses of Denmark’s tech sector. Michael frequently engages with public discourse through media contributions and organized events like Folkemødet 2024 workshop. His research emphasizes opening 'black boxes' of digital systems to foster accountability and ethical innovation.

Rikke Gadeمشاهده پروفایل

دانشیار

• Computer Vision
• Image Processing
• Robot Vision
• +۵ مورد دیگر

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.

Amélie Desvars-Larriveمشاهده پروفایل

دانشیار

• Infectious Disease Epidemiology
• Zoonotic Diseases
• Emerging Infectious Diseases
• +۱۲ مورد دیگر

Amélie Desvars-Larrive is an Associate Professor in Infection Epidemiology at the University of Veterinary Medicine Vienna and a Faculty Member at the Complexity Science Hub (CSH) in Vienna, Austria. Her work bridges veterinary medicine, public health, and data science, with a strong emphasis on the One Health approach to understanding zoonotic and emerging infectious diseases. She holds a Doctor of Veterinary Medicine from the National Veterinary School of Toulouse, France, with a specialization in tropical diseases and epidemiology, and earned her PhD in epidemiology from the University of Saint-Denis, La Réunion, in 2013. Her professional journey includes eight years as a field epidemiologist and veterinary research engineer in the Indian Ocean region, focusing on livestock and wildlife diseases. She completed postdoctoral research at Umeå University, Sweden, on tularemia modeling, followed by work at the University of Veterinary Medicine Vienna on urban brown rats and their role in zoonotic disease transmission and antimicrobial resistance. Her research interests include infectious disease epidemiology, zoonotic diseases, veterinary public health, disease modeling, antimicrobial resistance, and the application of data science to animal and human health. She has led and contributed to major open data initiatives, such as the SARS-ANI dataset on SARS-CoV-2 in animals and the CSH’s global dataset on governmental pandemic responses. The most recent articles highlight a strong trend in One Health research, integrating veterinary, environmental, and public health data. Key themes include zoonotic pathogen surveillance (e.g., Leptospira, SARS-CoV-2, E. coli), network modeling of animal trade, biosecurity assessments, and policy analysis of national One Health strategies. The work spans diverse systems—from urban rats in Vienna to dairy cows in Rwanda—demonstrating a global and interdisciplinary approach to disease prevention. Scientific Awards and Recognition: Her work on national One Health strategic plans was featured as an Editors' monthly favorite on the Cell Press Sustainability Hub. Her research on SARS-CoV-2 in animals has been widely covered in international media, including the San Francisco Chronicle and Kurier. She co-developed the CSH’s COVID-19 Control Strategies List (CCCSL), one of the largest datasets of governmental pandemic interventions. Advising and Grants: While specific advisees are not listed, she collaborates extensively with multidisciplinary teams across institutions. She has secured funding for data-driven projects in One Health, including those supported by the Complexity Science Hub. Her work on SARS-ANI and zoonotic web visualization reflects strong grant-supported research initiatives. She actively mentors early-career researchers, as seen from her involvement in the CSH PostDoc Program. Labs and Research Teams: She is a key member of the Health Across Species research group at the Complexity Science Hub, which focuses on zoonotic disease dynamics. She also leads research within the Unit of Conservation Medicine and the Institute of Animal Hygiene and Veterinary Public Health at the University of Veterinary Medicine Vienna. Her team employs data science, network analysis, and field epidemiology to study urban wildlife, livestock, and pathogen transmission.