جستجوی استاد راهنمای دانشگاهی

• Natural Language Processing
• Machine Learning
• Artificial Intelligence Ethics
• +۳ مورد دیگر

Anders Søgaard is a Professor at the University of Copenhagen , affiliated with both the Department of Computer Science and the Department of Communication. His research bridges Natural Language Processing and Machine Learning with a focus on AI ethics , explainability , and human-AI interaction . Primary Affiliation: Department of Computer Science, University of Copenhagen Secondary Affiliation: Department of Communication, University of Copenhagen Email: soegaard@di.ku.dk, soegaard@hum.ku.dk Research Interests His work spans Natural Language Processing , Machine Learning , and AI ethics , with recent studies addressing: Trustworthiness in AI systems Explainable AI (XAI) frameworks Multilingual model fairness and alignment Human-AI collaboration in reasoning tasks Ethical implications of social robots Mental health analytics using ML Recent Publications His 2025 output highlights trends in: AI ethics (e.g., fairness metrics, trustworthy systems) Multilingual model analysis (knowledge retention, cross-lingual transfer) Human-centric AI (gaze data, cultural considerations) Applications in healthcare and social good

Konstantinos Kalogeropoulosمشاهده پروفایل

استادیار

• Proteomics
• Snake Venom Research
• Protein Structure Prediction
• +۳ مورد دیگر

Konstantinos Kalogeropoulos is an Assistant Professor at the Department of Biotechnology and Biomedicine, Technical University of Denmark (DTU), leading research at the Cell Diversity Lab. His work bridges proteomics, computational biology, and snake venom research. Current projects: "The Proteomic Landscape during Influenza Infection" (2022-2025) Supervisor for PhD projects on protease network rewiring in psoriasis and wound exudate degradomics Research interests include: Proteomic analysis of inflammatory diseases Snake venom toxin structure prediction Extracellular matrix biomechanics De novo peptide sequencing algorithms Computational modeling of protease networks Recent article trends demonstrate his work in • Database-free proteomics (InstaNovo/InstaNexus) • Snake venom pathophysiology (V-ToCs clustering) • Inflammatory disease biomarkers (psoriasis, impaired healing) • Extracellular matrix mechanics (fibronectin tension, gut inflammation) Advising: Supervises PhD students Polhaus, C. J. M. and Haack, A. M., focusing on protease networks and wound healing.

Claudia Wagnerمشاهده پروفایل

استاد

• Computational Social Science
• Algorithmic Fairness
• Digital Behavioral Data
• +۷ مورد دیگر

Claudia Wagner is a full professor for Applied Computational Social Sciences at RWTH Aachen University and the Scientific Director of the Computational Social Science department at GESIS—Leibniz Institute for the Social Sciences. She is also an External Faculty member at the Complexity Science Hub Vienna. Her work bridges computer science and the social sciences to study algorithmic systems and their societal impacts. Her research focuses on socio-technical phenomena such as inequality, sexism, and perception bias in algorithmically infused societies. She investigates methodological challenges in using digital behavioral data to study human behavior, attitudes, and group dynamics. Her interests span computational social science, algorithmic fairness, network science, and AI ethics. The analysis of her recent publications reveals a strong emphasis on bias, fairness, and methodological rigor in digital data analysis. Her work spans AI psychometrics, gender inequality in online platforms, and validation frameworks for digital traces. She frequently publishes in top-tier venues such as Nature , Science , and AAAI conferences. DOC-fFORTE fellowship from the Austrian Academy of Sciences Four best paper awards at international conferences (ICWSM, CSCW, WWW, AAAI) Associate Editor, EPJ Data Science Steering Committee Member, International AAAI Conference on Web and Social Media Board Member, International Society for Computational Social Science Claudia Wagner has led and co-led substantial research projects funded by national and international agencies. She mentors a diverse group of PhD students working on topics like algorithmic bias, data quality, and dehumanization. She has organized training events such as the CSS Methods Summer School and delivered keynotes globally on inequality and computational social science. She leads the Computational Social Science department at GESIS and collaborates with interdisciplinary teams at RWTH Aachen and the Complexity Science Hub. Her group develops tools for measuring algorithmic impacts and visualizing disparities in socio-technical systems, such as the 'Planets of Disparity' dashboard.

Andrea Burattinمشاهده پروفایل

دانشیار

• Process Mining
• Business Process Management
• Petri Nets
• +۶ مورد دیگر

Andrea Burattin is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark. His work bridges formal methods and practical process analysis, focusing on process mining, business process management, and hybrid modeling techniques. He actively contributes to research in healthcare process optimization, streaming data analysis, and system verification through Petri nets and CCS transformations. UN Sustainable Development Goals: Poverty eradication, environmental protection, and prosperity for all (via process optimization) Active projects: Immersive Process Mining (2024-2027), Usability and Understandability of Hybrid Process Models (2018-2021) His research explores large language model integration with process mining, proposing frameworks like Tiramisù for multi-faceted process visualization and PN2CCS for formal model translation. Recent work emphasizes real-time monitoring, conformance checking, and IoT-driven process analytics. Key trends in his publications include: 1) Streaming process mining pipelines (2022-2025); 2) LLM-plan generation frameworks (2024); 3) Formal verification techniques (Petri nets, CCS); 4) Healthcare process modeling (2019-2023); 5) Behavioral pattern analysis in process compliance. Scientific Awards Best Demo Award (2022, 2016) Best Process Mining Dissertation Award (2014) Best Workshop Paper (EDBA and PODS4H, 2023) As advisor, he supervises PhD projects on process mining and hybrid modeling. His editorial roles include Information Systems reviewer (2024-2025) and past editor for Engineering Applications of AI (2022-2023). Collaborations span Denmark, Italy, and the Netherlands.

Zhiru Sunمشاهده پروفایل

دانشیار

• Learning Analytics
• Digital Humanities
• AI in Education
• +۵ مورد دیگر

Zhiru Sun is an Associate Professor at the University of Southern Denmark, affiliated with the Department of Design, Media and Educational Science. Their research focuses on the intersection of education, humanities, and data science, with expertise in Learning Analytics (LA), Digital Humanities (DH), and AI applications in education and humanities. Sun holds a Ph.D. in Educational Technology from The Ohio State University (2011–2015), alongside advanced degrees in Applied Statistics and Cultural Foundations of Technology. Key research interests include student motivation and performance analysis, historical data mining in DH, and human-centered AI in education. They have received notable awards such as the Outstanding Proposal Award (2021) and the Loadman Outstanding Dissertation Award (2016). Sun leads projects like 'Empowering Humanities Education with Deep Learning' and 'Flipped Classroom Design for Self-Regulation.' Their work spans collaborative learning algorithms, flipped classroom efficacy, and generative AI policy analysis in education. Educations: Ph.D. in Educational Technology, M.Sc. in Applied Statistics, and M.Sc. in Cultural Foundations (all from The Ohio State University) Key Projects: FREI: The Danish Family Revolution, DH Visualization Tools Teaching: Courses include Digital Humanities, Data Science, and Web-mediated Communication Recent publications address learner empowerment in online environments, negotiation skills in collaborative games, and group formation algorithms for optimal learning outcomes.

David E. Gloriamمشاهده پروفایل

استاد

• G Protein-Coupled Receptors (GPCRs)
• Computational Drug Discovery
• Biostructural Research
• +۶ مورد دیگر

Professor David E. Gloriam is a leading expert in G protein-coupled receptors (GPCRs) at the University of Copenhagen , Department of Drug Design and Pharmacology. Recognized as a top 1% Clarivate Highly Cited Researcher, he leads GPCRdb, a major database with >50,000 annual users, and develops computational tools like GPCRgraphs for drug discovery. His innovation roles include Senior Scientific Expert at Kvantify A/S and applications in pharmaceutical industry tools with patent citations. Education: Ph.D. in Medicine (Uppsala University, 2006), M.Sc. in Pharmaceutical Sciences (Uppsala University, 2003) Leadership: Head of GPCRdb (2014–), EU COST Actions member (2014–17), and institutional leadership roles in Pharmaceutical Data Science unit and Research Leadership Forum Research Interests: His work spans computational modeling of GPCR dynamics, virtual screening methods for inaccessible receptors, pharmacogenomics (PGxDB platform), and biased signaling for safer drugs. He integrates structural biology, data science, and bioinformatics to advance pharmaceutical discovery. Awards: Clarivate Highly Cited Researcher (2022) IUPHAR Analytical Pharmacology Award (2023) Lars Arge Prize for Big Data (2021) UCPH Forward Talent Program (2019) ERC Starting Grant (2014) Teaching & Supervision: Teaches Molecular Pharmacology and AI in Drug Discovery , and supervises 3 current PhD students. He has mentored 13 PhDs and 14 Postdocs, with former members attaining tenured academic or industry roles.

• Human-Computer Interaction
• Virtual Reality
• Extended Reality
• +۴ مورد دیگر

Teresa Hirzle is a Tenure Track Assistant Professor at the Department of Computer Science , University of Copenhagen , specializing in Human-Centred Computing . Her research focuses on Human-Computer Interaction (HCI) , Virtual Reality (VR) , Extended Reality (XR) , and Gaze-Based Interaction . Research Interests: Designing interaction techniques for immersive environments Eye movement analysis for educational applications Addressing digital eye strain in interactive systems Evaluating user experience in VR/AR Recent Research Trends: Her recent publications examine AI representation in VR co-creation, VR sickness in locomotion, eye strain in gaze-driven systems, and hybrid applications of comics/AR. She also explores pedagogical implications of eye tracking in remote learning. Contact: Email: tehi@di.ku.dk Office: Sigurdsgade 41, 2200 København N.

Thomas Bjørnerمشاهده پروفایل

دانشیار

• Qualitative Research
• Mixed Methods
• User Experience
• +۵ مورد دیگر

Thomas Bjørner is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. He serves as Head of the Media Innovation & Game Research (Me-Ga) unit and co-founded the research network for qualitative methods (since 2007) with 40+ company collaborations. Specializes in qualitative/mixed methods for technology evaluation Teaches PhD courses in advanced qualitative methods EU expert evaluator for research grants His research focuses on gamified learning , VR for social communication , and technology acceptance studies , often addressing UN Sustainable Development Goals. Recent projects include: Audio-only VR for blind gamers Generative AI integration in education Plastic crisis awareness games Smart city implementation barriers Scientific Awards: Serious Game Competition Award (2022) International conference prizes (2020, 2018) With over 121 publications including two textbooks, his work emphasizes applied qualitative methods with improved validity in technology contexts, particularly for youth education and media research.

Abdulkadir Çelikkanatمشاهده پروفایل

استادیار

• Genome Representation Learning
• Graph Representation Learning
• Machine Learning
• +۵ مورد دیگر

Abdulkadir Çelikkanat is an Assistant Professor in the Department of Computer Science at Aalborg University, Denmark, where he is part of the DKW (Data Science and Knowledge) research group. His research focuses on genome representation learning, graph representation learning, and machine learning applications in bioinformatics and network science. Research Interests: His work lies at the intersection of artificial intelligence and biological data analysis, with a strong emphasis on scalable methods for genome and metagenome representation using k-mer profiles, as well as modeling dynamic and complex networks. He develops novel machine learning models to capture the structure and evolution of graphs over time. Recent Research Trends: His recent publications, appearing in top-tier venues like NeurIPS, AAAI, and AISTATS, demonstrate a consistent focus on improving scalability and effectiveness in representation learning. Key themes include revisiting traditional k-mer methods for modern deep learning, modeling citation dynamics, and developing continuous-time node embedding techniques. His work bridges theoretical advances with practical applications in genomics and network analysis. Scientific Awards: Best Paper Award, TGL Workshop @ NeurIPS 2023 Top Reviewer, LoG 2024 Conference Advising and Grants: While current advisees are not listed, he is actively leading research projects as evidenced by his recent publications and project organization (e.g., Nordic ProbAI summer school). His work is supported through institutional affiliations and likely competitive research funding, given the high-impact venues of his publications. Labs and Teams: He is affiliated with the DKW group at Aalborg University. Previously, he was part of the Inria OPIS team and the Centre for Visual Computing during his Ph.D., and worked in the Section for Cognitive Systems at DTU Compute as a postdoctoral researcher.

Jakob Eg Larsenمشاهده پروفایل

دانشیار

• Human Computer Interaction (HCI)
• Personal Informatics
• Quantified Self
• +۳ مورد دیگر

Jakob Eg Larsen is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Applied Mathematics and Computer Science (DTU Compute) within the Cognitive Systems Section. He leads the Mobile Informatics and Personal Data Laboratory (MILAB). His research focuses on Human-Computer Interaction (HCI), Personal Informatics, Quantified Self, and Information Visualization, with applications in wearable technology, mental health, and healthcare. He teaches courses in Digital Media Engineering, including user experience, mobile application prototyping, and personal informatics. Education: PhD (2005) and MSc in Computer Science (1999) from the University of Copenhagen, with additional studies in cognitive psychology. Research emphasizes wearable devices for mental health interventions (e.g., PTSD treatment), physical activity tracking in pregnancy, and personalized hearing aid systems. Over 98 publications and 12 supervised PhD projects highlight his contributions to HCI, mHealth, and data-driven healthcare solutions. Labs/Teams: MILAB focuses on mobile informatics and personal data interaction. Collaborations span interdisciplinary fields like audiology, clinical psychology, and public health.

Stefan Iversenمشاهده پروفایل

دانشیار

• Narrative Theory
• Rhetoric
• Digital Media
• +۱۷ مورد دیگر

Stefan Iversen is Associate Professor at the School of Communication and Culture, Aarhus University, where he also serves as Director of the PhD programme for Art, Literature and Cultural Studies. His academic work bridges literary studies, rhetoric, and digital media, focusing on the evolving role of narratives in contemporary society. His research centers on narrative theory, rhetorical analysis, and the cultural implications of digital media. Key areas include fictionality , metanoic reflexivity , visual and multimodal rhetoric , political discourse , and cultural memory . He investigates how narratives shape identity, public debate, and democratic processes, especially in digital environments involving memes, AI-generated content, and campaign rhetoric. The trends across his recent publications reveal a sustained engagement with narrative disruption in politics, quantified storytelling on social media, and the theoretical foundations of fictionality. His work integrates literary theory with communication studies and digital humanities, reflecting an interdisciplinary approach to modern narrative forms. Aarhus University PhD Prize for 2008 He has supervised over 80 master’s theses and currently advises three PhD students in rhetorical studies. He teaches in the Rhetoric, Scandinavian Studies, and Humanistic Conflict Studies programs, and leads the international Summer Course in Narrative Studies. He is also a member of the national examination corps for Danish and Rhetoric. Stefan Iversen is actively involved in major research projects including the Center for Fictionality Studies , Humanistiske Konfliktstudier , and Globalisering og Kulturel Identitet , which reflect his commitment to interdisciplinary humanistic inquiry into contemporary societal challenges.

Arijit Khanمشاهده پروفایل

دانشیار

• Graph Neural Networks
• Blockchain
• Data Management
• +۵ مورد دیگر

Arijit Khan is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark. He leads the Data Engineering, Science and Systems group and is affiliated with the Technical Faculty of IT and Design. His research focuses on Graph Neural Networks , Blockchain , Data Management , and AI interpretability . He is the Principal Investigator (PI) of a major project on Data Management, Fundamental Algorithms, and Machine Learning for Emerging Problems in Large Networks (2022–2027). Research Interests : Graph Data Management & Machine Learning Blockchain Transaction Analysis Large Language Model + Knowledge Graph Synergies Healthcare AI (e.g., ICU glucose prediction) Explainable AI for Graph Neural Networks Research Trends : His publications emphasize neuro-symbolic systems , uncertain graph analysis , and AI-driven blockchain insights . Recent work bridges large language models with knowledge graphs and explores GPU performance optimization via shader code analysis. Awards & Grants : No explicit awards listed, but his active research grants include a 5-year project on large network analysis with interdisciplinary applications in life and health sciences. Funding emphasizes algorithmic innovation and data science integration. Labs/Teams : Head of the Data Engineering, Science and Systems research group, focusing on AI for societal impact ('AI for the People') and scalable graph data systems. Collaborations span blockchain analytics, healthcare informatics, and GPU architecture design.

Jeppe Revall Frisvadمشاهده پروفایل

دانشیار

• Computer Graphics
• Digital Image Synthesis
• Realistic Rendering
• +۷ مورد دیگر

Jeppe Revall Frisvad is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), within the Visual Computing group. His work bridges computer graphics, material science, and applied optics, focusing on realistic rendering and material appearance modeling. Ph.D. in Computer Graphics, DTU Informatics (2008) M.Sc. in Engineering (Applied Mathematics), DTU (2004) Education in University Teaching, LearningLab DTU (2008–2009) His research centers on computing material appearance from physical and chemical properties, developing faster and more accurate physically based rendering methods. Key areas include light scattering, bidirectional reflectance distribution functions (BRDF), anisotropy, and translucency modeling. Applications span computer games, movies, digital prototyping, architectural visualization, and training simulators. His recent publications (2024–2025) reflect a strong trend in digitizing material appearance, especially for 3D printing and food science, using spectrophotometry and optical validation. The work combines computer graphics with interdisciplinary applications in food structure and biological imaging, emphasizing measurement, modeling, and simulation. Scientific Awards: Research travel prize from AEG Elektronfonden (2006) IGDA scholarship for GDCE 2005 DTU Ph.D. scholarship (2004) He actively supervises Ph.D. students and leads multiple research projects, including those on organ-on-chip imaging, cheese quality analysis, and optical modeling of teeth. He collaborates across disciplines and institutions, with external research stays at UC San Diego and the University of Otago. He is involved in projects integrating AI with 3D imaging and material digitization. Jeppe is a key member of the Visual Computing research environment at DTU, contributing to both fundamental rendering algorithms and practical applications in industry and science.

Schahram Dustdarمشاهده پروفایل

استاد

• Distributed Systems
• Cloud Computing
• Services Computing
• +۵ مورد دیگر

Schahram Dustdar is a Full Professor of Computer Science and head of the Distributed Systems Group at TU Wien (Vienna University of Technology), Austria. He has held significant international academic positions, including Honorary Professor at the University of Groningen (2004–2010) and Visiting Professor at the University of Seville (Dec 2016–Jan 2017) and UC Berkeley (Jan–Jun 2017). His research interests lie at the intersection of distributed computing, cloud services, and intelligent data systems. He actively contributes to advancing the fields of services computing, cloud infrastructure, web technologies, and data-driven financial modeling. His work emphasizes scalable, robust, and knowledge-aware systems, particularly in financial data visualization and transaction network analysis. The most recent publications highlight his focus on modeling financial transaction networks using constraint satisfaction and developing visualization frameworks that incorporate incremental domain knowledge. These works reflect a strong trend toward integrating formal methods with interactive data systems for enterprise and financial applications. ACM Distinguished Scientist (2009) IBM Faculty Award (2012) IEEE Fellow (2016) Elected Member of Academia Europaea Schahram Dustdar has supervised multiple research projects and leads a vibrant research group at TU Wien. He has been involved in editorial leadership as Editor-in-Chief of Computing (Springer) and Associate Editor for top-tier journals such as IEEE Transactions on Cloud Computing, IEEE Transactions on Services Computing, ACM Transactions on the Web, and ACM Transactions on Internet Technology. His editorial roles and international visiting positions indicate extensive collaboration and grant-related activities, though specific grants are not detailed in the text. He leads the Distributed Systems Group at TU Wien, a research team focused on building next-generation distributed computing platforms, cloud services, and intelligent data processing systems with real-world applications in finance, enterprise systems, and large-scale data analytics.

• Multiple Sclerosis
• Neurology
• Neuropathic Pain
• +۷ مورد دیگر

Henrik Boye Jensen is a Clinical Associate Professor at the Department of Regional Health Research, IRS - Sygehus Lillebælt, Forskningsenhed for Neurologi (Kolding), affiliated with the University of Southern Denmark. His work bridges clinical neurology and research, with a strong focus on multiple sclerosis, stroke, and neurorehabilitation. Institution: University of Southern Denmark Department: Department of Regional Health Research Research Unit: Research Unit for Neurology, Kolding Academic Rank: Clinical Associate Professor His research interests center on multiple sclerosis , particularly disease progression, pharmacological treatments, and the role of exercise in neuroprotection. He also investigates stroke rehabilitation and diagnostic challenges in neurological conditions such as Lyme neuroborreliosis. His work frequently employs advanced methodologies including randomized controlled trials , cohort studies , and neuroimaging (MRI) . The 15 most recent articles reflect a strong trend in clinical neuroscience , with emphasis on MS phenotypes , pharmacological interventions , exercise as therapy , and diagnostic accuracy . His publications span high-impact journals in neurology and rehabilitation, demonstrating consistent scholarly output. Scientific Awards: No specific awards listed in the provided text. Henrik Boye Jensen has been actively involved in advising and research projects. He has contributed to at least three supervised works, including a Ph.D. thesis, and is a working partner in the RoboRehab project on stroke rehabilitation. He has participated in multiple collaborative research initiatives and has delivered presentations in both academic and public settings. He is also involved in public discourse through media contributions on neurological health issues. Labs and Teams: He is associated with the Research Unit for Neurology in Kolding and collaborates extensively within the Region of Southern Denmark and with national and international research groups, particularly in MS and stroke research.