August Rosholm Rehm is an Instructor at the Department of Computer Science (DIKU), University of Copenhagen. His work aligns with the Image Analysis, Computational Modelling, and Geometry section, focusing on interdisciplinary research bridging theoretical analyses, algorithm development, and real-world applications for science and society. He is based at Universitetsparken 1, 2100 Copenhagen Ø. Research Interests: Image Analysis, Computational Modelling, Machine Learning, Computer Vision, Numerical Optimization Contact: aure@di.ku.dk
Jonas Wolpers Reholt is an Instructor at the Department of Computer Science, University of Copenhagen, affiliated with the Algorithms and Complexity (AC) section. His work bridges theoretical computer science with practical applications, particularly in the realm of efficient computation and algorithmic paradigms. Role: Instructor University: University of Copenhagen Department: Algorithms and Complexity Email: jonas.reholt@di.ku.dk The AC section focuses on understanding computational efficiency through mathematical theory, with impacts on machine learning and applied domains. Jonas’s research aligns with themes like program analysis and reversible computing, as evidenced by his 2023 publication on static dereversibilization techniques. His recent work contributes to the theoretical foundations of reversible computation, with applications in software optimization and data structures. The publication appears in the Lecture Notes in Computer Science series, reflecting interdisciplinary collaboration and rigorous peer-reviewed scholarship. As a member of the AC section, Jonas engages in teaching and research alongside prominent figures like Professor Mikkel Thorup, who leads the section. The AC section also hosts major research centers such as BARC and DABAI, fostering innovation in algorithm design and big data analytics.
Lukas Thomas Schilling serves as an Instructor (mapped to Lecturer) at the Department of Computer Science (DIKU), University of Copenhagen, with contact email lusc@di.ku.dk and office at Universitetsparken 1, 2100 Copenhagen Ø. His research spans foundational computer science domains: Computer Science (broad theoretical and applied frameworks) Software Engineering (systems design, development methodologies) Algorithms (complexity analysis, optimization) Programming Languages (theory, implementation, type systems) Artificial Intelligence (core principles, ethical implications) Machine Learning (statistical models, data-driven systems) These interests align with DIKU's research sections including Programming Languages and Theory of Computation, and Software, Data, People, & Society, reflecting the department's emphasis on both theoretical rigor and societal impact in computing.
Thor Alexander Bøje Simonsen is an Instructor at the Department of Computer Science , University of Copenhagen , focusing on interdisciplinary research at the intersection of machine learning, quantum computing, and real-world applications. He is affiliated with the SCIENCE AI Centre and contributes to projects in sustainability, medical data analysis, and quantum-enhanced algorithms. His research spans theoretical and applied domains, including: Quantum computing for biomolecular simulations Environmentally sustainable AI systems Medical data analysis and clinical decision support Image reconstruction and remote sensing Explainable AI for large language models Thor's work engages with cutting-edge challenges in machine learning, from hardware acceleration to ethical considerations in clinical contexts. He is part of the university's Machine Learning Section , which has access to a dedicated compute cluster and collaborates with initiatives like TreeSense for global tree resource monitoring.
Ana Alina Tudoran is an Associate Professor at Aarhus University, specializing in quantitative methods within business intelligence. Her academic work bridges machine learning, data mining, and consumer behavior analysis. Primary affiliation: Department of Economics Research focus areas: Artificial Intelligence, Customer Lifetime Value modeling, and Hybrid Intelligence systems Notable projects include pandemic-era consumer behavior studies and IoT privacy reviews Her recent publications span supply chain optimization, organizational text analytics, and responsible AI deployment. Tudoran actively contributes to methodological advancements through hybrid PLS-SEM/machine learning frameworks and is a frequent speaker at management conferences.
Professor Tine Jess, MD, DMSc, serves as Center Director of the Center for Molecular Prediction of Inflammatory Bowel Disease (PREDICT) at Aalborg University's Department of Clinical Medicine, Faculty of Health Sciences. She is also a Senior Physician at Aalborg University Hospital with extensive leadership in gastroenterological research and clinical practice. Her educational background includes a Doctor of Medical Science (DMSc) degree focused on Prognosis of Inflammatory Bowel Disease Across Time and Countries , completed on April 28, 2008. Jess has held significant leadership positions including heading the Center for Clinical Research and Prevention in the Capital Region of Denmark and the Department of Epidemiology Research at Statens Serum Institut. As an international expert in inflammatory bowel disease (IBD), Jess's research spans epidemiology, cohort analysis, and molecular prediction of disease progression. Her work examines Crohn's Disease, Ulcerative Colitis, and the impact of environmental factors on IBD development. She employs precision medicine approaches to develop prediction models that guide preventive strategies and personalized treatment protocols. Her fingerprint analysis reveals strong expertise in cohort studies (63%), patient-focused IBD research (40%), and meta-analysis methodologies (15%). Professor Jess has received numerous prestigious awards including the UNESCO For Women in Science Award, the UEGW Rising Star Award, and the Joanna and David B. Sachar International Award (2024). She is a Fellow of the Royal Danish Academy of Science and Letters and received a Danish Medal of Honor for her contributions to medical science. Her research leadership includes supervision of multiple PhD students and management of significant grant-funded projects including Improved Treatment of Inflammatory Bowel Disease (2025-2030), Nutrition and inflammatory bowel disease epidemiology (2023-2026), and Long-term impact of COVID-19 on patients with Immune-Mediated Inflammatory Diseases (2022-2025). In 2023, she was appointed by the Danish Minister for Higher Education and Science to the Danish Council for Research and Innovation Policy (DFiR). Professor Jess leads the National Center of Excellence for Molecular Prediction of Inflammatory Bowel Disease (PREDICT) in Copenhagen, which serves as her primary research hub. The center focuses on developing molecular prediction models for IBD progression and treatment response through interdisciplinary collaboration between clinicians, epidemiologists, and molecular biologists. Her team maintains strong international connections including previous collaborations with the Mayo Clinic in the United States.
Anders la Cour-Harbo serves as an Associate Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design. His academic career spans over two decades with consistent publication output since 2000, demonstrating sustained research activity in unmanned aircraft systems and related technologies. His institutional affiliation places him within Denmark's prominent engineering research environment focused on practical technological applications. Professor la Cour-Harbo's research interests center on unmanned aircraft systems engineering, with particular expertise in drone applications for industrial settings. His work spans drone load systems, emergency landing technologies, predictive maintenance, and offshore operations. The research fingerprint shows strong emphasis on Unmanned Aircraft Engineering (100%), Load System Engineering (87%), and Unmanned Aircraft System Engineering (46%), reflecting his specialized focus areas. His projects consistently address real-world applications of drone technology, particularly in challenging environments like offshore wind farms. Analysis of his publication trends reveals a strategic focus on practical drone applications with increasing emphasis on safety systems, regulatory compliance, and industrial implementation. Recent publications (2023-2024) show strong industry relevance with applications in offshore wind turbine maintenance, predictive maintenance systems, and vision-based control technologies. His research bridges theoretical control systems with practical implementation challenges in drone operations. Teacher of the Year 2015 Teacher of the Year 2006 Professor la Cour-Harbo leads multiple significant research projects including SafeEye (Automated emergency landing for small unmanned aircraft), UAS-ability (research infrastructure for drone development), and OPAL (Offshore Delivery of Packages). He serves as chair for JARUS (Joint Authority for Rulemaking of Unmanned Systems), significantly influencing European drone legislation. His spin-off company Vixos demonstrates successful technology transfer from academic research to commercial application. The Harm threshold for unmanned aircraft in European legislation impact shows his direct contribution to shaping regulatory frameworks. His laboratory and research team focus on practical drone applications with infrastructure supporting airborne data collection and drone development. The UAS-ability project specifically created research infrastructure for drone development and airborne data collection. His collaboration network spans multiple countries, with significant European partnerships focused on advancing drone technology standards and applications. His work with JARUS places him at the forefront of international drone regulation development.
Ana Alacovska is an Associate Professor at the Department of Management, Society and Communication of Copenhagen Business School . Her research focuses on the intersection of digital labor, creative work, and technology-driven societal transformations. She examines topics such as gig economy dynamics, algorithmic management, and the cultural implications of digital platforms like NFTs and social media. Her work contributes to understanding how workers navigate precarious conditions in the creative industries and gig economy, including issues of identity construction, speculative labor practices, and anti-surveillance art as ethical responses to technological control. She has explored these themes through studies of global contexts, including Ghanaian creative entrepreneurs and Danish digital labor platforms. Alacovska’s publications frequently appear in top journals like Human Relations and New Media & Society , and her research has been widely covered in media outlets across Europe. She has supervised six academic works, though specific student names are not listed. Her scholarship bridges sociology, management studies, and cultural theory, addressing both academic and public audiences. While no formal awards are cited, her impactful contributions are evidenced by citations, media mentions, and Mendeley readership numbers. She actively engages with societal issues through her research on UN Sustainable Development Goals, particularly those addressing economic inequality and technological ethics.
Luca Pezzarossa is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on real-time systems, embedded computer systems, digital microfluidics, compiler optimizations, and hardware accelerators. He leads projects such as the Edu4Chip: Joint Education for Advanced Chip Design in Europe initiative and supervises PhD students in areas like compiler optimizations for neural networks and speech enhancement algorithms. His academic journey includes contributions to interdisciplinary fields, combining computer engineering with biomedical applications such as biochip design and PCR optimization. He actively engages in open-source tool development, particularly using the Chisel framework for hardware design education and research. Key research themes include: Real-time systems and time-predictable architectures Compiler-driven optimizations for constrained devices Digital microfluidics for lab-on-a-chip systems Edge computing and TinyML applications Recent publications highlight innovations in microplastic detection on edge devices, dynamic channel pruning for speech enhancement, and parallel execution engines for digital microfluidics. His work aligns with sustainable development goals through environmental applications and energy-efficient technologies. Current projects involve: PhD Supervision: Andrea Cerioli (Compiler Optimizations), Riccardo Miccini (AI-to-Neural Network Mapping), Ehsan Khodadad (Time-predictable Systems) Research Grants: EU-funded Edu4Chip (2023–2025), multiple industry-academia collaborations Labs and teams: Leads the Embedded Systems Engineering group at DTU, focusing on interdisciplinary hardware-software co-design for real-world applications. Active in developing open-source frameworks for education and research.
Henrik Bredmose is a Professor at the Technical University of Denmark (DTU) within the Department of Wind and Energy Systems. His research focuses on water wave dynamics, applied mathematics, and numerical methods, with a specific emphasis on violent flows and offshore engineering challenges. He has held postdoctoral positions at the University of Bristol and DHI Water & Environment, contributing to both academic and industrial projects. Education: Mathematical Modelling of Nonlinear Irregular Water Waves (PhD, DTU, 1999-2002). Research interests include computational fluid dynamics (CFD), floating wind turbine hydrodynamics, extreme wave load prediction, and design wave methodologies. His recent work addresses aero-elastic stability of wind turbines, second-order force models for non-slender structures, and optimization of floating wind farm layouts. Key projects include FloatLab (2023-2027) and FloatStep, focusing on advanced hydrodynamic analysis and design tools for offshore wind energy systems. Collaborations span international teams, addressing challenges in wave-structure interaction and turbine dynamics. He advises PhD students on topics like floating wind farm modeling and monopile wave impact loads. His contributions include the DeRisk Database, providing extreme design wave data for offshore structures.
Rongling Li is an Associate Professor at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU). His research focuses on smart energy systems, smart cities, and building energy flexibility, emphasizing modeling and data-driven approaches. He leads projects like SEEDS and IEA EBC Annex 82, contributing to resilient low-carbon energy systems. He has supervised seven PhD graduates and currently advises two students on energy flexibility topics. Key affiliations include chairing the IEA EBC Annex 82 and serving on the Built4People board under Horizon Europe. His expertise spans energy resilience, building physics, and machine learning applications. Notable awards include the 2019 Best Presentation Award and a 2021 research fellowship at the University of Tokyo. His research portfolio includes 55 publications across journals like Applied Energy and Energy and Buildings. Current projects involve data-driven control for smart energy systems and energy management in sports facilities. He actively reviews PhD theses at institutions such as UC Dublin and Chalmers University.
Henning Christiansen is a Professor at Roskilde University's Department of People and Technology, affiliated with the Programming, Logic and Intelligent Systems (PLIS) research group. He is also a Knight/Chevalier of the Dannebrog (2018) and serves as Coordinator for International Student Exchanges in Computer Science, Informatics & Humanities-Technology Studies. His research spans Deep Learning for medical diagnosis, Robotics in theatrical performances, Constraint Logic Programming, Probabilistic-logic models, Natural Language Processing, Logical methods for context comprehension, Interactive art installations, Database query systems, Cultural technology projects like Viskbook. Key projects include SEAFACTS (digital maritime history platform), EXPLAIN-ME (explainable AI in medical education), NDH (cross-border health data collaboration). Publications highlight contributions to AI ethics, robot choreography, medical image analysis, constraint-based formal methods. He has supervised over 16 projects and 285+ activities, including international conferences and exhibitions. His photography has been displayed in Roskilde libraries and cultural venues.
Rob van der Goot is an Associate Professor in Data Science at the IT University of Copenhagen. His affiliations include the NLPnorth group and the Pattern Recognition Revisited lab . His research focuses on Natural Language Processing (NLP), with emphasis on language modeling, lexical normalization, and computational job market analysis. Key contributions include the development of the EEVEE annotation tool, studies on language model biases, and cross-lingual parsing techniques. He has received prestigious awards such as the Best Paper Award at W-NUT 2022 and the Outstanding Paper Award at EACL 2021 . His work spans projects like the Pioneer Centre for Artificial Intelligence (funded by the Danish National Research Foundation) and Multi-Task Sequence Labeling Under Adverse Conditions (funded by Amazon). His research also intersects with societal impacts, addressing bias in AI systems and improving NLP tools for under-resourced languages. Media engagements include discussions on AI adoption in Danish municipalities and business applications. His publications (48+) span topics from domain adaptation to large language model evaluation, emphasizing practical NLP solutions and reproducible research practices.
Michele Coscia is an Associate Professor in the Department of Data Science at the IT University of Copenhagen. He also serves as the Head of Programme for the BSc in Data Science. His research focuses on network analysis, social networks, data mining, and their applications in understanding human mobility, complex systems, economic development, and memetics. He has contributed to projects such as the Pioneer Centre for Artificial Intelligence and leads initiatives like ROMNET (Past social network reconstruction from material culture data) and Work2Vec (exploring deep learning in healthcare and work hours analysis). His research interests encompass interdisciplinary network science, including misinformation dynamics, ideological polarization, and the impact of social media systems. He has developed methodologies like the generalized Euclidean measure for multilayer networks and explored cultural data analytics through case studies like Italian music history. His work also addresses real-world challenges, such as quantifying the effects of violence on migration patterns and optimizing network sampling strategies for cost efficiency. Michele Coscia has received the Årets Forskningsmiljø 2022 award, recognizing his contributions to fostering outstanding research environments. He actively engages with media, discussing topics like misinformation and data visualization. As a principal investigator, he oversees projects funded by institutions such as the Villum Foundation and Danish National Research Foundation. His research spans academic collaborations across countries, reflecting his global network and commitment to advancing network theory and its applications.
Karol Szwagrzak is an Associate Professor in the Department of Economics at Copenhagen Business School (CBS). His research focuses on Microeconomics, Mechanism Design, and Resource Allocation, with particular emphasis on strategy-proof mechanisms, fair division, and networked economies. He has published extensively in top journals such as Economics Letters , Management Science , and Social Choice and Welfare . Key research areas include bankruptcy problems, priority rules, team productivity measurement, and axiomatic analysis of allocation rules. His work bridges theoretical economics with practical applications in policy and institutional design. Notable contributions include analyzing how individuals claim resources strategically and designing mechanisms to allocate resources under network constraints. Recent publications (2021–2025) explore topics like sample evidence weighting, teamwork productivity, and proportional allocation rules. His research often combines game theory with empirical analysis to address fairness and efficiency challenges. No scientific awards are explicitly listed, though his work is widely cited in academic circles. No formal advising or grant details are provided in the text. His professional activities are centered at CBS, with no reported external affiliations. The department’s focus on economics aligns with his research in mechanism design and resource allocation, reflecting CBS’s emphasis on business-related economic analysis.
