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Marcell Richard FeketeView profile

Research Fellow

• Multilinguality
• Language variation and typology
• Parameter-efficient fine-tuning methods
• +2 more

Marcell Richard Fekete is a Research Fellow at Aalborg University Copenhagen's Department of Computer Science within The Technical Faculty of IT and Design. Funded by the Carlsberg Foundation, his work focuses on multilingual modeling for resource-poor languages under Professor Johannes Bjerva's supervision. Education MA in Human Language Technology from Vrije Universiteit Amsterdam (2022) BA in Linguistics from University of Cambridge (2018) His research explores multilinguality, language typology, parameter-efficient fine-tuning methods, and computational linguistics interpretability. He investigates how language models represent linguistic knowledge and compares human-AI language understanding paradigms. Recent publications focus on adapter modules for cross-lingual transfer, phonetic similarity in toponym matching, and creole language benchmarks. His work demonstrates strong connections to machine translation, language modeling, and computational linguistics subfields. Active in academic dissemination, he has presented at major conferences like ACL and NAACL, participated in workshops, and engaged in international collaborations including a guest researcher position at Hungary's Research Centre for Linguistics.

• Programming Languages
• Reversible Computation
• Quantum Computing
• +7 more

Robin Kaarsgaard Sales is an Assistant Professor on the tenure track in the Department of Mathematics and Computer Science at the University of Southern Denmark, Faculty of Science and Engineering. His research focuses on the theoretical foundations of programming languages, with an emphasis on reversible computation, quantum programming, and categorical semantics. His research interests span Programming Languages , Reversible Computation , Quantum Computing , Categorical Semantics , Functional Programming , and Formal Methods . He investigates how invertibility and reversibility can be integrated into programming models, particularly in the context of quantum computation, using tools from category theory and mathematical logic. His recent publications, appearing in high-impact venues such as POPL and ICFP, demonstrate a consistent focus on compositional models of reversible and quantum computation. Key themes include invertible functional programming, quantum semantics via groupoids and morphisms, and program transformations for tail recursion in reversible settings. These works reflect a deep integration of theoretical computer science with mathematical structures. Robin was a participant in the research project Landauer Meets von Neumann: Reversibility in Categorical Quantum Semantics (2020–2022), funded by the Danish Research Council, which underscores his active role in advancing foundational aspects of quantum computing. He has collaborated extensively with prominent researchers including Jacques Carette, Chris Heunen, and Amr Sabry. His work has been featured in public media, including TV2 News and regional press, highlighting both his research impact and community engagement. He is also referenced on Wikipedia and has a presence on academic platforms such as ORCID, Scopus, and Mendeley. He is affiliated with a research group active in programming language theory and quantum computation, contributing to a growing international network in reversible and quantum computing. His ongoing work continues to explore the mathematical underpinnings of computation, aiming to bridge theory with practical language design.

Ali BasiratView profile

Associate Professor

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +5 more

Ali Basirat is an Associate Professor in the Department of Nordic Studies and Linguistics at the Faculty of Humanities, University of Copenhagen, affiliated with the Center for Language Technology (CST). His research focuses on data-driven approaches to language technology, particularly explainable natural language processing and morphosyntactic analysis, with emphasis on universal patterns across languages and efficient language processing tools. His academic qualifications include: PhD in Computational Linguistics from Uppsala University (awarded 2018) Certificate in Higher Education Pedagogy from Linköping University (awarded 2022) Dr. Basirat's research centers on mathematical modeling of natural languages, with core interests in universal language models, representation learning, dependency syntax, and explainable NLP. He investigates data-driven syntax, word embeddings, grammatical gender patterns across languages, and adaptation of large language models for environmental studies and sustainable development goals. His work bridges theoretical linguistics with practical NLP applications. Analysis of his 2020-2025 publications reveals three dominant trends: (1) Advancements in multilingual dependency parsing through linguistic typology and syntactic nuclei exploration; (2) Investigation of grammatical gender representation in word embeddings and language models; (3) Application of NLP techniques to climate conceptual history and environmental studies. His research increasingly addresses efficiency challenges in large language model adaptation while maintaining cross-lingual performance. No major scientific awards are currently documented in his public profile. Dr. Basirat supervises master's theses in natural language processing and computational linguistics, focusing on machine learning, language modeling, syntactic parsing, and knowledge graphs. He teaches graduate courses including Scientific Programming and Representation Learning for Natural Language Processing (RL4NLP) at the University of Copenhagen's IT & Cognition and Computer Science programs. He is a core member of the Center for Language Technology (CST) and actively collaborates with the Nordic Language Processing Laboratory (NLPL). His research network extends through membership in the Association for Computational Linguistics (ACL), facilitating international collaborations across European institutions.

Line Burholt KristensenView profile

Associate Professor

• Psycholinguistics
• Experimental linguistics
• Neurolinguistics
• +9 more

Line Burholt Kristensen is an Associate Professor in the Department of Nordic Studies and Linguistics at the University of Copenhagen's Faculty of Humanities. She leads the research group "Broken Grammar & Beyond," financed by the Independent Research Fund Denmark, and serves as Principal Investigator for the Steno Diabetes Center Sjælland-funded project "Vulnerability and related notions - an investigation of language to and about individuals with diabetes" with co-PI Christina Fogtmann Fosgerau. Her educational background includes an MA in linguistics, PhD, and completion of the Teaching and Learning in Higher Education Programme at the University of Copenhagen (2013-2014). Her academic career spans positions as Associate Professor (2018-present), Postdoc at the ProGram research group (2013-2017), External lecturer (2012-2013), and PhD student (2009-2012). Kristensen's research integrates psycholinguistics, neurolinguistics, and experimental methodologies to investigate grammatical processing. Her primary focus examines how native speakers process texts with anomalous learner syntax, particularly verb placement errors in Danish as a second language. She employs eye-tracking technology to measure reading times and comprehension, comparing grammatical anomalies in native versus non-native Danish writing. Her work on information structure and sentence context builds on her 2013 PhD thesis "Context, you need," which investigated how these elements interact during sentence processing. Her recent publications reveal a strong trajectory in second language acquisition research, with particular emphasis on verb-second constructions in Danish, preposition usage, and error detection mechanisms. These studies combine corpus linguistic approaches with experimental methods, demonstrating how language users react to grammatical anomalies both cognitively and neurologically. Her work increasingly bridges theoretical linguistics with practical applications for language teaching. As an educator, Kristensen teaches at BA and MA levels in Linguistics and has previously instructed courses in Audiologopedics, Danish, and IT & Cognition. She actively supervises student projects in experimental linguistics and corpus linguistics, encouraging research on language processing and acquisition. Her grant portfolio includes substantial funding from the Independent Research Fund Denmark and Steno Diabetes Center Sjælland for interdisciplinary projects examining language in both educational and medical contexts. She directs the "Broken Grammar & Beyond" research group, which employs a multidisciplinary approach combining psycho- and neurolinguistic experiments with grammar research. The team investigates the neural underpinnings of language processing using neuroimaging techniques while analyzing naturally occurring grammatical anomalies in both native and non-native Danish writing. This work has significant implications for understanding language acquisition, processing limitations, and the cognitive architecture of grammar.

Jakob Lykke AndersenView profile

Associate Professor

• Algorithms
• Graph Transformation
• Chemical Reaction Networks
• +7 more

Jakob Lykke Andersen is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he conducts research in algorithms with applications in cheminformatics and complex systems. He also holds a former external appointment as a Research Fellow at the Tokyo Institute of Technology (2015–2017). Research Interests: His work lies at the intersection of computer science and theoretical chemistry, focusing on algorithmic methods for analyzing chemical reaction networks. He employs hypergraphs, mixed-integer linear programming, and probabilistic models to study metabolic pathways, reaction databases, and prebiotic systems. His research emphasizes computational efficiency, formal modeling, and software implementation. Publication Trends: His recent publications (2019–2025) show a consistent focus on graph-based modeling of chemical systems, rule extraction from reaction databases, thermodynamic feasibility, and stochastic analysis. These works appear in high-impact journals in cheminformatics, bioinformatics, and complex systems, reflecting strong interdisciplinary collaboration. Scientific Contributions: While no specific awards are listed, his sustained research output and leadership in funded projects highlight significant contributions to algorithmic cheminformatics. Grants and Projects: He is actively involved in two major ongoing research projects: (1) Software Infrastructures for Teaching at Scale (funded by Innovation Fund Denmark, 2022–2025), and (2) DIREC (Danish Research Center for Digital Economy, 2020–2025), indicating active engagement in both educational technology and core computational research. Advising and Outreach: While no students are listed, he participates in academic advising through project supervision. He contributes to public discourse through media appearances on topics such as mathematics in health (e.g., intestinal system modeling in obesity) and educational well-being. Labs and Teams: He collaborates with interdisciplinary teams, including researchers from bioinformatics, chemistry, and computer science, particularly through projects involving Merkle, Flamm, Fagerberg, and Stadler. His work is associated with algorithmic cheminformatics and software framework development groups at SDU.

Martin SchoeberlView profile

Professor

• Real-Time Systems
• Embedded Systems
• Multicore Processing
• +3 more

Professor Martin Schoeberl is affiliated with the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on real-time systems, worst-case execution time analysis, and embedded systems engineering. He is actively involved in projects such as Rigoletto, aiming to develop high-performance automotive processors using RISC-V architecture. Research Interests: Schoeberl's work spans time-predictable processors, network-on-chip architectures, and hardware-software co-design for cyber-physical systems. He explores methodologies to ensure deterministic behavior in multicore environments and develops tools for WCET analysis. His contributions include advancements in compiler optimizations for neural networks and temporal semantics in embedded systems. Advising & Grants: Schoeberl supervises PhD students such as E. Khodadad (on rigorous design of time-predictable systems) and A. Cerioli (on compiler optimizations for neural networks). He leads or participates in funded projects including Rigoletto (2025-2028) and Multi-Core Architecture for L1 Deterministic Processing (2022-2025). These projects aim to enhance real-time capabilities in embedded systems and automotive computing platforms. Labs & Teams: As part of the Embedded Systems Engineering group at DTU, Schoeberl collaborates on hardware generators using Chisel and designs reactor-oriented architectures for cyber-physical systems. His work integrates reconfigurable logic and synchronous models to create efficient, time-predictable solutions.

Kim JørgensenView profile

Assistant Professor

• Mental Health
• Recovery-Oriented Care
• Critical Discourse Analysis
• +4 more

Kim Jørgensen is an Assistant Professor (20% part-time) in the Department of People and Technology at Roskilde University, Denmark, affiliated with the Health and Society Research Group. His work centers on mental health systems, recovery-oriented practices, and cross-sectoral collaboration between psychiatric hospitals and municipal services. His research employs critical discourse analysis to examine mental health policy framing, user involvement mechanisms, and professional implementation challenges. Key themes include the fragmentation of care transitions, discourse constructions of recovery, and power dynamics in interorganizational collaboration. He investigates how healthcare professionals navigate recovery-oriented models within existing structural constraints, with particular focus on Danish mental healthcare reforms. Recent publications (2024-2025) demonstrate methodological diversity through scoping reviews, qualitative studies, and critical discourse analyses. Dominant trends include cross-sectoral collaboration challenges (38% of recent works), recovery-oriented practice implementation (29%), and user involvement frameworks (22%), with increasing attention to children of mentally ill parents and digital self-harm. Dr. Jørgensen actively contributes to 9 research projects including the active 2024-2027 study 'Recovery-oriented care in mental health centres for users with severe mental difficulties' and serves as co-supervisor for PhD research on online self-harming behavior. His editorial work includes Nordisk Sygeplejeforskning (2025) and International Journal of Environmental Research and Public Health (2023-2024). He collaborates with interdisciplinary teams across mental health centers and municipalities, presenting findings at Nordic nursing conferences on recovery-oriented network meetings and professional experiences with cross-sectoral collaboration.

Morten RhigerView profile

Associate Professor

• Computer Science
• Programming Languages
• Semantics of Programming Languages
• +10 more

Morten Rhiger is an Associate Professor in the Department of People and Technology at Roskilde University, Denmark, specializing in programming language theory and implementation with expertise in semantics, type systems, and compiler design. His research portfolio centers on: Programming Languages : Core design principles and theoretical foundations Semantics : Formal denotational and operational frameworks Type Systems : Safety mechanisms and correctness verification Compilers : Optimization techniques and runtime systems Program Generation : Staged computation and automatic code synthesis Multi-stage Languages : Runtime code generation and partial evaluation Publication trends reveal sustained contributions from foundational work (2009-2012) on pattern combinators and staged computation to recent innovations in type-based uncurrying (2024), with significant interdisciplinary work on energy-transparent systems (2016). His research consistently bridges theoretical rigor with practical implementation challenges. Rhiger actively contributes to major research initiatives including ENTRA (2012-2015) for energy transparency, NUSA (2011-2013) for model checking, and recent energy-certification projects (2020-2022), demonstrating sustained focus on program analysis and energy-aware computing. He maintains strong community engagement through organizing the Copenhagen Programming Languages Workshop and participating in key conferences including the Symposium on Implementation and Application of Functional Languages.

• Programming Languages
• Quantum Computing
• Reversible Computing
• +3 more

Robin Kaarsgaard is an Assistant Professor (Tenure-track) specializing in Programming Languages, Quantum Computing, and Reversible Computing. His work bridges theoretical computer science with practical programming language design, focusing on foundational aspects of quantum algorithms, invertible computation, and algebraic structures. Research interests include quantum programming languages, reversible computing models, category theory applications in computer science, and formal semantics of programming constructs. He has contributed to frameworks like Jeopardy, an invertible functional language, and explored quantum computing's computational limits through mathematical abstractions. Key projects include the Landauer Meets von Neumann initiative (2020–2022), investigating reversibility in quantum semantics. His work has been featured in media discussions about academic life in Svendborg, Denmark. Publications span 28 peer-reviewed outputs in venues like ACM Proceedings and Lecture Notes in Computer Science, with recent focus on compositional approaches to quantum programming and invertible recursion mechanisms.

Danny Bøgsted PoulsenView profile

Associate Professor

• Formal Methods
• Model Checking
• Cyber-Physical Systems
• +3 more

Danny Bøgsted Poulsen is an Associate Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on formal methods, model checking, and cyber-physical systems with applications in security analysis and programming languages. He contributes to projects like BEO-COVID (2020–2020) and IDEA4CPS (2011–2015), which explore decision support tools and foundational cyber-physical systems. His academic background includes advanced work in formal verification and statistical model checking. Key research interests include: Formal methods for string constraints and SMT solvers Statistical analysis of security-critical systems Modelling protocols like DTLS and attack-defense scenarios Applications of formal methods in education and public health Recent work highlights include developing SMTQuery for benchmark analysis, statistical evaluation of bit-flip vulnerabilities, and leveraging large language models for educational feedback. His research outputs span over 36 publications across journals and conferences, with active contributions to UPPAAL tool development and open datasets for reproducibility. Poulsen collaborates internationally on projects involving formal verification of embedded systems and cybersecurity protocols. His work bridges theoretical computer science with practical applications in safety-critical systems.

Jørgen VilladsenView profile

Associate Professor

• Logic
• Artificial Intelligence
• Multi-Agent Systems
• +5 more

Roles and Affiliations: Jørgen Villadsen is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Applied Mathematics and Computer Science and the Algorithms, Logic and Graphs Section. He serves as Head of Study and focuses on formal logic, multi-agent systems, and computer science education. Education: MSc in Computer Science and Engineering (1989, DTU) and PhD in Computer Science (1995, DTU). Research Interests: Villadsen’s work centers on logic and its applications in computer science and artificial intelligence, including formal methods, multi-agent systems, type theory, and non-classical logics. He emphasizes the development of proof assistants like Isabelle and tools for teaching logic and formal reasoning. Recent Research Trends: His publications from 2020–2017 highlight contributions to logic education, automated reasoning, and multi-agent system design. Key areas include Isabelle-based proof systems, hybrid logic formalization, and competitive agent development in programming contests. Scientific Contributions: He has led teams in the Multi-Agent Programming Contest, published extensively in journals like Annals of Mathematics and Artificial Intelligence , and contributed to open-source tools like NaDeA and SPA. Grants and Projects: Involved in projects such as CONTROL (constraint-based language processing) and HyLoMOL (hybrid logic integration). Supervised numerous MSc and PhD students in multi-agent systems and formal methods. Labs/Teams: Active in the Multi-Agent Systems Lab, leading development of agents for competitions and educational tools. Collaborates internationally on logic, AI, and formal verification.

• Programming Languages
• Formal Logic
• Software Verification
• +5 more

Jesper Bengtson is a Lecturer in Theoretical Computer Science specializing in Programming Logic and Semantics at the IT University of Copenhagen. His research primarily focuses on formal methods for programming languages, with particular expertise in session types, separation logic, and proof assistants. Dr. Bengtson's research interests center around programming language theory and formal verification. His work explores how to mathematically verify software correctness through logical frameworks. He specializes in session types for communication protocols, separation logic for reasoning about concurrent programs, and developing tools for interactive theorem proving. His research bridges theoretical computer science with practical applications in software verification. His publication record shows consistent contributions to programming language theory over the past decade, with a clear trend toward applying formal methods to concurrent and distributed systems. Recent work demonstrates increasing focus on mechanized verification of session type systems and integration of session types with separation logic for concurrent program verification. Dr. Bengtson has been involved in several significant research projects including MECHANIST (MECHANIsation of Session typEs, 2021-2025), ToMeSo (Tools and Methods for Scalable Software Verifications, 2009-2013), and a general-purpose framework for software verification (2013-2017). These projects were funded by major Danish research foundations including Danmarks Frie Forskningsfond and Independent Research Foundation of Denmark. His work has been featured in media outlets, including a 2015 article titled 'Danish researcher wants to eradicate software errors' and a 2021 piece about 'Natural or woke? Big shooter introduces controversial soldier,' indicating public engagement with his research.

• Programming Languages
• Type Systems
• Theoretical Computer Science
• +5 more

Hans Hüttel is a Part-time Lecturer and Guest Researcher in the Department of Computer Science at the University of Copenhagen's Faculty of Science, specializing in Programming Languages and Theory of Computation within the Programming Languages and Theory of Computation research group. His research focuses on: Type systems for programming languages Process calculi and concurrency theory Formal semantics of programming languages Static analysis techniques Theoretical foundations of programming languages Data flow and alias analysis Hüttel's scholarly work demonstrates sustained contributions to programming language theory with publications spanning from 2022 to 2025. His research trajectory shows both theoretical depth in process calculi and practical applications in modern programming languages. The 2025 publication on program synthesis indicates adaptation of his expertise to emerging AI-assisted programming paradigms while maintaining rigorous theoretical foundations. His publications appear in reputable venues including Communications of the ACM, Information and Computation, and Electronic Proceedings in Theoretical Computer Science, reflecting both theoretical significance and practical relevance in programming language design and implementation. Hüttel maintains active collaborations with researchers across multiple institutions as evidenced by his co-authored publications with colleagues including Lybech, Bendixen, Bojesen, Lund, Jensen, Paulsen, Teule, and Saioc. His work receives attention across academic platforms with readership on Mendeley and mentions on social media platforms including X and Bluesky.

Hamid BekamiriView profile

Assistant Professor

• Technology Mapping
• Science Mapping
• Applied Machine Learning
• +3 more

Hamid Bekamiri is an Assistant Professor in Innovation and Industrial Dynamics at Aalborg University Business School. He holds a PhD in Information Technology Management and specializes in applied machine learning and digital transformation. His research bridges computer engineering with social sciences, focusing on technology mapping methodologies. His research interests center on developing computational tools for science and technology mapping, with expertise in NLP, deep learning, and big data analytics. Recent work explores semantic similarity models for patent analysis and knowledge landscape visualization. Publications demonstrate consistent focus on machine learning applications in technology management. Recent articles show progression from banking security algorithms to advanced patent classification systems using transformer architectures. Professional technical skills include: 7+ years in Python/R programming AWS and Slurm-based cloud computing NoSQL/SQL database management High-dimensional data processing

• Semantic Web
• Formal Methods
• Digital Twins
• +3 more

Eduard Kamburjan is an Assistant Professor in the Department of Software Engineering at the IT University of Copenhagen. His research focuses on integrating Semantic Web technologies with formal methods to develop and analyze data-heavy computational systems, particularly Digital Twins. He is the creator of the SMOL language for knowledge graph integration and Crowbar, a deductive verification system for Active Objects. His current work explores novel approaches to modularity in program verification, emphasizing contracts for distributed and hybrid systems. In 2024, he contributed to a publication on probabilistic dynamic logic proof systems. Eduard's research is affiliated with the Software Quality Research (SQUARE) group. His ORCID profile (0000-0002-0996-2543) and contact details, including his office in Copenhagen (Denmark), are publicly accessible.