جست‌وجوی استاد و پژوهشگر

Juan Manuel Rodriguezمشاهده پروفایل

استادیار

• Recommender Systems
• Web Services
• Deep Learning
• +۳ مورد دیگر

Juan Manuel Rodriguez is an Assistant Professor in the Department of Computer Science at Aalborg University, Denmark. His affiliation is within The Technical Faculty of IT and Design, specializing in Data, Knowledge, and Web Engineering. Dr. Rodriguez holds a PhD in Computer Science and has a strong focus on research areas including Recommender Systems, Web Services, Deep Learning, and Social Media Analysis. His work often intersects with applications in information retrieval, healthcare systems, and crisis management. His research explores topics such as misinformation detection, transformer-based news recommendation, and clinical data analysis using knowledge graphs. He has contributed to projects like HEREDITARY (2024–2027), which integrates heterogeneous data for gut-brain research. Rodriguez has also engaged in media collaborations, including work highlighted in 'Udforsker Mars: Studerende fra Aalborg samarbejder med NASA' (June 2024). Key technical interests include leveraging neural networks for user behavior modeling, optimizing retrieval systems, and addressing ethical challenges in AI. His recent publications (2020–2025) span domains from pandemic mental health tracking to parking availability prediction, reflecting a multidisciplinary approach to computational challenges.

Hans Hüttelمشاهده پروفایل

دانشیار

• Process Calculi
• Type Systems
• Programming Languages
• +۴ مورد دیگر

Hans Hüttel is an Associate Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design. His research focuses on theoretical foundations of computer science with emphasis on programming languages and formal methods. His research interests span process calculi, type systems, concurrency theory, program synthesis, and security protocols. The fingerprint analysis of his work shows strong emphasis on Type Systems (100%), Process Algebra (27%), Cryptographic Protocols (22%), and Branching Time (18%). His recent work demonstrates a growing interest in the intersection of formal methods with emerging technologies like large language models. Hüttel's publication trend shows consistent output with 97 research outputs including 56 articles in proceedings, 17 journal articles, and 9 conference articles in journals. His most recent work (2024-2025) focuses on type systems for programming languages, program synthesis with LLMs, and functional array programming. Scientific Awards: CONCUR Test-of-Time Award (Sept 2020) Hüttel has participated in multiple research projects including TREsPASS (Technology-supported Risk Estimation by Predictive Assessment of Socio-technical Security), BETTY (Behavioural Types for Reliable Large-Scale Software Systems), and educational initiatives like PBL Exchange. He has 35 media appearances where he discusses topics ranging from AI ethics to university education reform. He leads research within the Distributed, Embedded and Intelligent Systems group and has been active in educational development through problem-based learning (PBL) initiatives at Aalborg University.

Galadrielle Humblot-Renauxمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۴ مورد دیگر

Galadrielle Humblot-Renaux is a Research Fellow at Aalborg University's Technical Faculty of IT and Design, affiliated with the Department of Architecture, Design and Media Technology and the Section for Media Technology in Aalborg, Denmark. Her work focuses on AI-driven solutions for computer vision, robotics, and uncertainty quantification in machine learning systems. Key Research Areas Out-of-Distribution Detection and Robustness Testing 3D Semantic Segmentation and Point Cloud Processing Uncertainty Quantification in Renewable Energy Systems Human-Robot Interaction and Speaker Identification Marine Ecology Image Analysis via Multi-Annotator Datasets Scientific Contributions She has created two influential datasets: JAMBO (2024) for underwater benthic habitat classification and Why Talk to People When You Can Talk to Robots? (2021) for far-field speaker identification challenges. Her publications across 2018-2025 demonstrate interdisciplinary expertise bridging AI theory with practical applications in robotics, automotive systems, and ecological monitoring.

Dalin Zhangمشاهده پروفایل

دانشیار

• EEG-based Emotion Recognition
• Time Series Forecasting
• Graph Neural Networks
• +۴ مورد دیگر

Dalin Zhang is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark. He holds a position within the Technical Faculty of IT and Design. His research focuses on machine learning, sensor data analysis, and their applications in healthcare, smart cities, and human-computer interaction. Key areas include EEG-based emotion recognition, time series forecasting, and graph neural networks. He leads the PREDICTION-ENABLED DYNAMIC SCHEDULING OF HOUSEHOLD ELECTRICITY USAGE project (2023–2024), demonstrating expertise in energy systems optimization. His work bridges theoretical advancements with practical applications, such as developing lightweight models for real-time traffic flow prediction and creating benchmarks for emotion recognition systems like LibEER. Research interests span: EEG signal processing for emotion and intention recognition Efficient time series analysis and forecasting Graph neural networks and adversarial defense mechanisms Data privacy in wearable sensor systems Recent publications highlight innovations like Pure-GNN (graph neural networks against adversarial attacks), LightCast (traffic forecasting), and Self-Supervised EEG Representation Learning. He advises two PhD students but their names are not listed in the provided texts. His work often emphasizes computational efficiency and real-world deployment across healthcare, smart infrastructure, and consumer electronics.

Sean S. Downeyمشاهده پروفایل

دانشیار

• Complex Adaptive Systems
• Socioecological Sustainability
• Indigenous Knowledge Systems
• +۷ مورد دیگر

Sean S. Downey is an Associate Professor in the Department of Anthropology at The Ohio State University, affiliated with the College of Arts and Sciences. He is also associated with the Sustainability Institute and the Translational Data Analytics Institute at OSU, where he contributes to interdisciplinary research on complex socioecological systems. He is currently leading the development of a new Bachelor of Science in Computational Social Science. His research focuses on applying complex adaptive systems theory to understand how Indigenous customary practices—particularly in swidden agriculture—contribute to long-term socioecological sustainability. His work integrates field experiments, agent-based modeling, and remote sensing to study human-environment interactions in regions such as the Toledo District of Belize and historical Neolithic Europe. Dr. Downey's recent publications highlight a strong trend in using computational and experimental methods to analyze sustainability in traditional agricultural systems. His studies combine anthropology with data science, focusing on topics like public goods games in Maya communities, drone-based ecosystem monitoring, and early warning signals of societal collapse. This interdisciplinary approach bridges environmental science, social theory, and complexity science. Scientific Awards: National Science Foundation CAREER Award Sean Downey has secured competitive external funding, including the prestigious NSF CAREER award, supporting his work on Q’eqchi’ Maya social norms and tropical forest dynamics. He actively collaborates with leading scholars such as J. Stephen Lansing and Stefan Thurner, contributing to high-impact research on cultural evolution, language transmission, and sustainable land use. While formal advisees are not listed, his leadership in curriculum development and research suggests a strong mentoring role. He is involved in advanced modeling initiatives and is building academic infrastructure through the new Computational Social Science program, reflecting a commitment to translational, data-driven anthropology.

Vito D. P. Servedioمشاهده پروفایل

پژوهشگر

• Innovation dynamics
• Opinion dynamics
• Economic complexity
• +۷ مورد دیگر

Vito D. P. Servedio is a senior researcher at the Complexity Science Hub in Vienna, specializing in complex systems analysis applied across diverse domains including human dynamics, innovation, economic complexity, and railway systems. With a background in physics, he has developed expertise in ab initio calculations for electronic properties of materials and agent-based modeling of social and technological systems. His research interests span conceptual and practical applications, with significant contributions to innovation dynamics, opinion dynamics, and complex network analysis. His interdisciplinary approach applies complex systems methodologies to unconventional areas such as chess, blockchain technology, and music analysis. He has led major projects including the Kouzan group which secured a US patent for a blockchain-based device recording information flow in working groups, and developed macroscopic railway simulations for the Austrian railway system. His recent work focuses on the Science of Science, studying global migration patterns of researchers and identifying patterns in scientific capacity building. His publication record demonstrates a clear trend toward increasingly interdisciplinary work, with recent papers bridging network science, transportation systems, cultural dynamics, and scientific evolution. His research consistently applies quantitative methods to complex social and technological phenomena, revealing underlying patterns in seemingly disparate domains. US patent for a blockchain-based device recording information flow in working groups Vito leads multiple research projects including Train Operating Forecasting (TOF I and II) focused on optimizing Austrian railway systems, the Kouzan project on blockchain applications for knowledge transfer, and the CSH PostDoc Program aimed at strengthening scientific expertise in digitalization and data science. His work frequently involves collaboration with institutions including Sony CSL Paris and Austrian railways (ÖBB). He has also contributed to significant visualizations such as tools for optimizing train traffic in Austria and models for analyzing district collapse risk in healthcare systems.

Johannes Bjerring Bjervaمشاهده پروفایل

استاد

• Natural Language Processing (NLP)
• Computational Linguistics
• Large Language Models (LLMs)
• +۳ مورد دیگر

Johannes Bjerring Bjerva is a Professor at Aalborg University specializing in Language Technology. He leads the Sapere Aude-funded project Building TRUST in Text , which focuses on detecting adversarial manipulation of large language models (LLMs) to ensure their reliability and trustworthiness across languages. Educated at Stockholm University (PhD in NLP) and Hamar Cathedral School Research interests: Computational Linguistics, AI Security, Multilingual NLP, Linguistic Signal Analysis Recipient of Sapere Aude: DFF-Research Leaders 2025 grant and DFF-Forskningsleder-bevillingen His project addresses critical challenges in identifying poisoned LLM outputs through subtle linguistic fingerprints, with societal implications for healthcare, education, and finance. He collaborates with Stockholm University and NVIDIA to develop scalable detection methods. Scientific Awards: Sapere Aude: DFF-Research Leaders 2025 grant DFF-Forskningsleder-bevillingen Johannes advises two PhD students and a postdoc within his research group, emphasizing interdisciplinary approaches to secure AI systems. His work balances foundational research with practical applications to make LLMs safer for global use.

• Rehabilitation Robotics
• Assistive Technologies
• Tongue-Computer Interfaces
• +۱۵ مورد دیگر

Lotte NS Andreasen Struijk is a Professor and Center Director at the Department of Medicine and Health Technology, Faculty of Health Sciences, Aalborg University. She leads the Center for Rehabilitation Robotics and the Neurorehabilitation Robotics and Engineering research group, and she heads both the Rehabilitation Engineering and Robotics Laboratory and the Biorobotics Laboratory. Her work is dedicated to advancing rehabilitation technologies for individuals with severe disabilities. Education: PhD in Biomedical Engineering and Science, Aalborg University (2002) University Pedagogics for Assistant Professors, Aalborg University (2001–2004) Her research focuses on developing innovative assistive technologies, particularly tongue-based interfaces (e.g., iTongue), exoskeletons, and robotic rehabilitation systems. These technologies aim to restore independence for people with spinal cord injuries and neuromuscular disorders. Key areas include brain-computer interfaces, human-robot interaction, and the clinical evaluation of assistive devices. Her work significantly contributes to the UN Sustainable Development Goals, especially in health and innovation. Her recent publications highlight advancements in intelligent exoskeletons, EEG-based tongue movement classification, and real-world usability of assistive robotic arms. These works reflect a strong trend toward user-centered, clinically validated, and interdisciplinary solutions in rehabilitation robotics. Scientific Awards: Vanførefondens Forskerpris (2019) Clinica Award (2013) Honorary Professor, Amity University (2022) Nominated full member of Sigma Xi (2023) Nominated IEEE EMBS Geographical Representative for Europe (2024) She has supervised 9 PhD students as main supervisor and 5 as co-supervisor. She has secured major research grants, including from the Independent Research Fund Denmark and the Louis-Hansen Foundation, supporting projects like EXOTIC and intelligent hybrid exoskeletons. She is also actively involved in academic leadership, serving on the Academic Council of the Faculty of Medicine and the AAU Parallel Language Advisory Group. She leads the Rehabilitation Engineering and Robotics Laboratory (https://rerob.aau.dk/) and the Biorobotics Laboratory, where interdisciplinary teams develop and test next-generation assistive technologies. Her work bridges engineering, clinical practice, and user needs, ensuring translational impact.

Emad Jacob Marounمشاهده پروفایل

پژوهشگر ارشد

• Worst-Case Execution Time Analysis
• Real-Time Systems
• Embedded Systems
• +۳ مورد دیگر

Emad Jacob Maroun is a Research Fellow at the Department of Applied Mathematics and Computer Science within the College of Engineering at the Technical University of Denmark (DTU). His work centers on time-predictable computing with emphasis on Worst-Case Execution Time (WCET) analysis for safety-critical embedded systems. His research interests span Worst-Case Execution Time Analysis , Real-Time Systems , Embedded Systems Engineering , Instruction Set Architectures , and Time-Predictable Computing . Maroun focuses on creating deterministic execution environments through techniques like single-path code generation, tagged architectures, and hardware-software co-design for predictable timing behavior. Analysis of his recent publications reveals a strong trend toward solving WCET challenges in heterogeneous environments. His work bridges compiler design, hardware architecture, and real-time theory—particularly in Developing the Platin multi-target analysis framework Advancing Lingua Franca for real-time applications Designing internally-tagged instruction sets for safety Optimizing caching for mixed-criticality 5G systems His research directly addresses the timing predictability gap in modern complex hardware. Maroun actively contributes to the WCET research community through conference organization and tool development, though no formal scientific awards are currently documented. His collaborative work shows strong ties with the DTU Embedded Systems Engineering group and international researchers in real-time systems. While no formal students or major grants are mentioned in available records, his publications indicate leadership in multi-institutional projects like the Platin toolchain development. Maroun operates within DTU's Embedded Systems Engineering research environment, focusing on creating practical WCET solutions for industrial applications in safety-critical domains including telecommunications infrastructure and real-time control systems.

• WebAssembly
• Formal Verification
• Memory Models
• +۳ مورد دیگر

Jean Pichon-Pharabod is a Tenure Track Assistant Professor in the Department of Computer Science at Aarhus University, Denmark, with an office at Åbogade 34 in Aarhus N. His research spans formal verification, programming languages, and computer architecture, focusing on foundational work for secure and reliable systems. His primary research interests include the formal verification of WebAssembly, relaxed memory models for architectures like Arm, and security invariants for virtualized environments. He develops mechanized proofs using frameworks like Iris and Coq to establish robust safety properties for compilers, hypervisors, and low-level systems. His work bridges hardware semantics with programming language theory to address concurrency challenges in modern architectures. Analysis of his 2021-2025 publications reveals a consistent focus on verified compilation (CertiCoq-Wasm), axiomatic semantics for relaxed architectures (AxSL logic), and memory-safe WebAssembly verification (Iris-MSWasm). His research demonstrates strong international collaboration, particularly with Lars Birkedal at Aarhus University, and targets high-impact venues like PACMPL and CPP. Key trends include mechanized separation logics for virtual machines (VMSL) and formal elucidation of hardware-software interfaces for security-critical systems.

• Natural Language Processing
• Machine Learning
• Data Science
• +۷ مورد دیگر

Natalie Schluter is a Lecturer in Theoretical Computer Science at the IT University of Copenhagen , affiliated with NLPnorth and Machine Learning Algorithms. Her research focuses on Natural Language Processing (NLP) , Machine Learning , and Data Science , with specific contributions to automatic summarization, cross-lingual inference, and dependency parsing. She has secured multiple research grants and actively engages in public discourse on gender equality in academia. Principal Investigator (PI) for projects like GOOGLELOWNLP (2020–2025) and Danish Language Inclusion (2019–2021). Key research areas: Danish language technology, neural networks, and syntactic modeling. Email: nael@itu.dk Her publications highlight trends in machine translation , graph-based parsing , and low-resource NLP , often leveraging deep neural networks. She has contributed to 18 publications and participated in organizing events like the Women in Data Science (WiDS) Copenhagen conference. Media contributions include advocacy for gender equality in IT and NLP.

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +۳ مورد دیگر

Zhan Su serves as a Guest Researcher within the Programming Languages and Theory of Computation group at the Department of Computer Science, Faculty of Science, University of Copenhagen. His research bridges theoretical computer science with practical applications in artificial intelligence and privacy. Education: Ph.D. in Computer Science, University of Copenhagen, 2024 (Thesis: Information Propagation in Modular Language Modeling and Web Tracking) Research Interests: Dr. Su's work centers on quantum-inspired neural architectures for natural language processing and information retrieval systems. He pioneers density matrix representations for semantic modeling and investigates conversational search mechanisms enhanced by large language models. His research extends to privacy vulnerabilities in educational technology, examining web tracking evolution across digital learning platforms. The integration of quantum computing principles with classical machine learning frameworks represents a distinctive thread throughout his publications. Publication Trends: Analysis of Dr. Su's 8 publications (2023-2025) reveals three dominant research trajectories: (1) Quantum-AI hybrid systems (40% of output), featuring entanglement-embedded networks and density matrix word representations; (2) Conversational information retrieval (38%), with innovations in history-aware dense retrieval and query alignment; (3) Privacy/security applications (22%), particularly in online education ecosystems. His 2025 works demonstrate increasing sophistication in quantum-classical model fusion, while 2024 outputs show substantial conference presence at ACL, CIKM, and WWW venues. Advising and Grants: No advisory roles or grant funding details are documented in the available materials. Current research appears conducted within collaborative frameworks at the University of Copenhagen. Labs and Teams: Dr. Su operates within the Programming Languages and Theory of Computation research environment at DIKU (Department of Computer Science), engaging with interdisciplinary teams focused on language modeling, quantum computing applications, and web security analysis. His collaborations span institutions including the University of Copenhagen's Department of Computer Science and external partners in natural language processing research.

• Middle Eastern Studies
• Arabic Literature
• Syrian Cultural Studies
• +۳ مورد دیگر

June Dahy serves as a Teaching Associate Professor in the Department of Cross-Cultural and Regional Studies at the University of Copenhagen, specializing in Syrian cultural production and Arabic language instruction. Her academic profile demonstrates sustained engagement with Middle Eastern sociopolitical dynamics through both scholarly research and public advocacy. Her educational foundation includes a mag.art. (Master of Arts) in Semitic Philology, establishing her expertise in Arabic linguistic traditions. This academic background directly informs her dual focus on literary translation and critical analysis of Syrian cultural expression under authoritarian regimes. Research interests center on Syrian literary diaspora in Denmark, political resistance through theater, and refugee protection frameworks. Her work bridges Arabic literature, political science, and human rights advocacy, with particular emphasis on documenting systemic violence in Syria and challenging forced repatriation policies. Translations of seminal works like Samar Yazbek's 'Du Må Ikke Dø' demonstrate her commitment to amplifying Syrian voices. Publication trends from 2009-2023 reveal evolving scholarly focus: early work examined historical figures (Saladin, Ibn Khaldun), shifting toward contemporary Syrian cultural resistance (Maghout's theater) and urgent policy interventions (2021 refugee advocacy). This trajectory reflects increasing urgency in addressing Syria's humanitarian crisis through interdisciplinary scholarship. No scientific awards were documented in the source materials. Professional activities include editorial work on the ToRS yearbook series and public intellectual contributions through Danish media outlets. Her academic leadership manifests through curriculum development in Arabic language instruction and public scholarship challenging Denmark's refugee policies. Current work focuses on Syrian cultural survival mechanisms amid displacement, with emerging research on digital surveillance risks for returning refugees.

Robin Engelhardtمشاهده پروفایل

دانشیار

• Computational Social Science
• Social Cognition
• Complex Systems
• +۵ مورد دیگر

Robin Engelhardt serves as a Teaching Associate Professor in the Section for Consumption, Bioethics and Governance at the University of Copenhagen's Department of Food and Resource Economics (Faculty of Science). His interdisciplinary career bridges mathematical biology, social cognition, and science communication, with recent work focusing on computational modeling of social phenomena and educational game design. Academic Background: PhD in Complex Systems, Niels Bohr Institute (1995-1998) MSc in Theoretical Biology, University of Copenhagen (1992-1994) BA in Comparative European Literature, University of Copenhagen Teaching and Learning in Higher Education Programme (2014-2015) Engelhardt's research examines computational social science through complex systems theory, with emphasis on social cognition, online experiment design, and game mechanics. His work integrates philosophy of science with practical applications in collective decision-making, language evolution, and polarization dynamics. Recent projects analyze recursive belief reasoning in coordination games and wisdom-of-crowds phenomena in digital environments. Publication trends (2016-2022) reveal consistent interdisciplinary output spanning game theory, social media analysis, and science education. His articles demonstrate methodological innovation in modeling social cognition while addressing real-world challenges like research ethics and institutional science teaching. Key contributions include frameworks for interdisciplinary course design and computational investigations of shared knowledge limitations. Research Funding & External Roles: Engelhardt has secured grants from The Carlsberg Foundation, Trygfonden, Knud Højgaards Fond, The Danish Ministry of Children and Education, and European Union programs (e-Ten, IST). He maintains active science communication through Danish media outlets including Dagbladet Information and Ingeniøren, and has served as external lecturer at Aalborg University (2014-2016). His professional activities include judging FDB’s Green Idea Prize and developing publicly funded educational games through a personal consultancy.

• Neuropsychology
• Phenomenological Psychology
• Face Blindness
• +۳ مورد دیگر

Erling Nørkær is a Research Assistant in the Department of Psychology at the University of Copenhagen's Faculty of Social Sciences. He is currently conducting his PhD research under the supervision of Randi Starrfelt and Tone Roald, with office hours available Wednesdays 13:00-15:00. His research focuses on: Neuropsychology and face recognition disorders Phenomenological investigation of Developmental Prosopagnosia (DP) Qualitative methods for understanding face perception experiences Validation of assessment tools for prosopagnosia Nørkær's work bridges cognitive psychology and clinical neuropsychology through phenomenological approaches that examine the subjective experience of face blindness. His research moves beyond traditional cognitive models to explore how individuals with DP perceive, imagine and remember faces through in-depth interviews. His recent publications (2023-2025) demonstrate a concentrated focus on developmental prosopagnosia, with significant contributions including a comprehensive scoping review of the field, validation of the Danish Prosopagnosia Index, and investigations into the lived experience of face blindness. His work frequently appears in high-impact journals like Cortex and Journal of Vision. Nørkær collaborates extensively with leading researchers in the field, particularly with his supervisors Randi Starrfelt and Tone Roald, as well as Christian Gerlach. His research methodology combines qualitative phenomenological approaches with quantitative analysis to provide a holistic understanding of face recognition disorders.