Narongrit Unwerawattana is a Researcher at the Department of Mathematics and Computer Science, University of Southern Denmark, affiliated with the Artificial Intelligence, Cybersecurity and Programming Languages VIP group and the Digital Democracy Centre. His work focuses on microservices, distributed computing, and software engineering. Research Interests He specializes in microservices architecture, testing frameworks, and programming languages, with secondary interests in cybersecurity and service-oriented systems. His research contributes to advancing coordination models and technical support for multiple services. Scientific Awards Best Artifact Award (2023) Projects Currently participating in the "Cybersecurity and Business Continuity" project (2023–2026), collaborating with researchers on mental models and cybersecurity challenges for small and medium enterprises.
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.
Ashutosh Dhar Dwivedi is an Assistant Professor in the Cybersecurity Group at Aalborg University, Copenhagen, Denmark. He specializes in blockchain security, applied cryptography, post-quantum cryptography, and advanced cybersecurity. His interdisciplinary research spans cryptography, IoT security, and AI-driven security analytics. Education: PhD in Cryptography, with postdoctoral research at institutions including the University of Waterloo, Technical University of Denmark, and the Polish Academy of Sciences. His pedagogical focus includes professional upskilling in cyber defense and post-quantum resilience. Research interests include post-quantum cryptographic protocols, privacy-preserving blockchain systems, and machine learning for security. His work has yielded over 50 peer-reviewed papers, including contributions to high-impact journals and conferences. Notable achievements: 2023 and 2024 Stanford University Top 2% Scientist ranking. Contributions: Editorial roles in international journals, program committees for premier conferences, and leadership in academic-industry collaborations like the Quantum Communication Infrastructure (QCI) consortium. Active in developing quantum-secure systems for national and industrial infrastructure.
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.
Sandra Greiner is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where she conducts research in artificial intelligence, cybersecurity, and programming languages. Her work is centered on improving the reliability and adaptability of control software in cyber-physical production systems through advanced software engineering techniques. Her research interests include software variability modeling , design by contract , and the application of generative AI in automating software development tasks. She focuses on ensuring high reliability in software-intensive systems, particularly in industrial automation contexts. Her work bridges theoretical computer science with practical software engineering challenges. The recent publications highlight a strong trend in leveraging AI for software contract generation, enhancing feature tracing with reliable knowledge, and managing variability in complex production systems. Her research contributes to model-driven engineering, software product lines, and intelligent software assistance, with a consistent emphasis on empirical validation through case studies. Sandra actively collaborates with researchers across Europe, particularly in Austria and Germany, contributing to top-tier conferences such as SPLC, MODELS, and GPCE. Her work has been published in high-impact journals and conference proceedings, reflecting active engagement in the global software engineering community. She is affiliated with the IMADA research center at SDU, as evidenced by her institutional email. No formal awards or fellowships are mentioned in the provided data. Sandra advises no publicly listed students, and there is no indication of lab leadership or team management in the text. However, her collaborative publications suggest participation in research teams focused on software product lines and AI-driven software engineering.
Kurt Jensen is a Professor at the Department of Computer Science, Aarhus University, Denmark. His academic career spans decades, focusing on formal modeling, concurrency, and software specification techniques. Research interests: Coloured Petri Nets, modeling and validation of distributed systems, simulation tools, and formal methods. Affiliation: Aarhus University, Department of Computer Science (School of Engineering not explicitly mentioned). His publications, including the seminal book series Coloured Petri Nets , emphasize theoretical computer science and practical applications in concurrent systems. Key contributions include the Invariant Method for Petri Net analysis and tools for system validation.
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.
Tobias Todsen serves as a Clinical Associate Professor in the Department of Clinical Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences. His primary research integrates technical innovation with clinical science to advance diagnostics and minimally invasive treatments, particularly in head and neck ultrasound applications. He directs the Surgical Ultrasound Research Group in Copenhagen (SURGiC), an interdisciplinary team of medical doctors and engineers, and holds leadership roles as Coordinating Associate Professor for the Technical University Hospital of Greater Copenhagen (TUH) and President of the Danish Society of Diagnostic Ultrasound (DSDU). Dr. Todsen's research interests span ultrasound technology, artificial intelligence in medical diagnostics, head and neck surgery, virtual reality applications, and global health outreach. His work focuses on developing innovative solutions for clinical problems, including AI-assisted ultrasound diagnostics, 3D imaging for surgical guidance, and regenerative therapies for cancer survivors. He has pioneered educational initiatives such as the Copenhagen International Head & Neck Ultrasound Course, which has trained over 200 physicians from 30+ countries, and developed the 'Data in Medicine' course introducing AI applications to medical students. Analysis of his recent publications reveals a strong trend toward human-AI collaboration in medical diagnostics, particularly in ultrasound applications for thyroid and head/neck conditions. His research increasingly incorporates large language models for medical assessment while maintaining rigorous clinical validation through multicenter trials. The work demonstrates significant translational impact, with several innovations progressing to patent applications and commercialization through his spinout company 3Sonic. Dr. Todsen has secured over 4 million Euros in competitive research funding and led multicenter clinical trials involving more than 30,000 participants. His educational contributions include technology-enhanced learning materials with over 300,000 views, including a WHO clinical guide. As course director for medical education programs, he has successfully implemented curriculum innovations for 296 medical students in the 'Data in Medicine' course. He directs the Surgical Ultrasound Research Group (SURGiC), which operates at the intersection of clinical practice and engineering innovation. The group has developed multiple patented technologies and established the spinout company 3Sonic to commercialize their diagnostic solutions. Dr. Todsen also maintains active clinical practice through Copenhagen University Hospital (Region H), where his email affiliation indicates his operational base for translational research.
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.
Lars Kæraa Lücke serves as a Lecturer in the Department of Computer Science at the University of Copenhagen, Denmark, with his office located at Universitetsparken 1, 2100 København Ø. His research spans core computer science disciplines, emphasizing both theoretical and applied domains: Computer Science Algorithms Programming Languages Software Engineering Data Science Machine Learning Professional engagement includes maintaining an active institutional web presence at https://diku.dk/ and direct correspondence via lkl@di.ku.dk.
Fanar Haddad is an Assistant Professor (Tenure Track) at the University of Copenhagen's Department of Cross-Cultural and Regional Studies, within the Faculty of Humanities. His research focuses on Iraqi politics, sectarianism, and post-2003 state formation. He contributes to HUM:Global initiatives, exploring global phenomena through interdisciplinary humanities approaches. His work examines identity politics, militia dynamics, and governance challenges in conflict-affected states. Research interests include the transformation of sectarian identities, the role of armed groups in state structures, and the interplay between nationalism and communalism in the Middle East. He investigates how historical narratives shape contemporary political struggles and how post-conflict societies navigate hybrid power systems. He is part of the Professional Project Group (PPG) coordinating HUM:Global programs, ensuring broad disciplinary inclusion across departments like Cultural Studies, Communication, and the Saxo Institute. His work bridges academic analysis with policy-relevant insights on global challenges. Labs/Teams: Active in the Department of Cross-Cultural and Regional Studies and HUM:Global's interdisciplinary research network.
Davide Mottin is an Associate Professor at the Department of Computer Science, Aarhus University. His primary research focuses on graph theory, machine learning, and data mining, with significant contributions to knowledge graphs, algorithm design, and interdisciplinary applications in drug discovery and material science. He holds a leadership role in large international conferences such as CIKM 2024 as a Program Chair. His research explores scalable graph algorithms (e.g., subgraph matching, alignment), robust knowledge graph cleaning, and leveraging large language models for scientific tasks. Mottin has pioneered work on spectral methods for graph analysis (e.g., NetLSD, VERSE embeddings) and developed frameworks for interactive data exploration (e.g., X2Q, MetaExp systems). Key contributions include FUGAL for graph alignment and Ucode for community detection Active in reproducibility efforts, as seen in retraction notices and algorithmic redesigns Focus on practical applications in drug discovery via evolution-based models (EvolMPNN) He has authored over 60 peer-reviewed publications and holds grants supporting interdisciplinary research at the intersection of computer science and life sciences. Mottin is affiliated with the university's AI and data science initiatives, contributing to both theoretical advancements and real-world system implementations.
Thiago Rocha Silva is an Associate Professor in the Software Engineering group at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU). His work bridges software engineering, human-robot interaction, and end-user development, with a focus on making robotic systems accessible through intuitive programming interfaces. University: University of Southern Denmark Institute: Maersk Mc-Kinney Moller Institute Department: Software Engineering Academic Rank: Associate Professor His research interests are centered on end-user development , domain-specific languages , and interactive systems , particularly in the context of robotics and software engineering. He investigates how users can program robots without deep technical expertise, using gesture-based interfaces, visual-textual synchronization, and low-code environments. The recent publications highlight a strong trend in human-robot collaboration , focusing on user-centric design, behavior modeling, and programming frameworks that empower non-experts. These works span robotics, software engineering, and human-computer interaction, often employing participatory and user-centered methodologies. Thiago actively leads and contributes to major research initiatives, including projects on sustainable human-robot synergy in extended reality and low-code programming for mobile robotics. He supervises students and teaches courses such as End-User Development and Software Engineering and Organization . He is involved in interdisciplinary collaborations, particularly in projects integrating AI, robotics, and Earth observation data. His work emphasizes practical applications in smart societies, logistics, and physical training.
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.
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.
