Find Academic Supervisors

• Operator Algebra
• C*-algebras
• K-theory
• +3 more

Søren Eilers is a Professor at the Department of Mathematical Sciences , University of Copenhagen. His research focuses on Operator Algebras , particularly the classification of C*-algebras related to discrete and low-dimensional structures. He is a member of the FNU network 'Automorphisms and Invariants for Operator Algebras' and advocates for experimental mathematics using computational methods in pure mathematics. Education: MS in Mathematics and Computer Science, University of Copenhagen (1993) PhD in Mathematics, University of Copenhagen (1995) Research Interests: Operator Algebras K-theory Symbolic Dynamics Discrete Mathematics Experimental Mathematics Recent Publications (2016-2024) demonstrate expertise in graph C*-algebras , symbolic dynamics , and computational approaches to pure mathematics, with key collaborations in Denmark, Japan, Canada, and the U.S. Scientific Leadership: President, Danish Mathematical Society (2006-2008) Principal Investigator, Villum Fonden (2012-2016) Main Organizer, Mittag-Leffler Institute Program (2016) Advisory Roles: Supervised 28 master's theses and mentored 9 PhD students/postdocs (2003-2022) across institutions in Denmark, Canada, Japan, and the U.S.

Joachim KockView profile

Associate Professor

• Category theory
• Homotopy theory
• Combinatorics
• +4 more

Joachim Kock is an Associate Professor at the Department of Mathematical Sciences, University of Copenhagen, with research focusing on category theory, homotopy theory, combinatorics, and algebraic geometry. His work explores intersections with probability theory, mathematical physics, and computer science, particularly through decomposition spaces, operads, and categorical structures. Education: Not explicitly mentioned External Employment: Professor Titular at Autonomous University of Barcelona Research Areas: Category theory and higher structures Homotopy-theoretic combinatorics Decomposition spaces and incidence algebras Applications in computer science and mathematical physics Recent Publications: 2024: ∞-operads as symmetric monoidal ∞-categories 2022: Tracelet Hopf Algebras and Decomposition Spaces 2022: Infinity-Operads as Analytic Monads 2021: Every 2-Segal space is unital 2021: Operadic categories and decalage Editorial Activities: Editor, Theory and Applications of Categories (since 2017) Editor, Higher Structures (2016–2022) Editor, Compositionality (since 2018)

Peter DanholtView profile

Associate Professor

• Sociotechnical perspectives on work, management and technology
• IT in the health service
• Working practice and the use of IT
• +13 more

Peter Danholt is an Associate Professor at the School of Communication and Culture, Aarhus University, affiliated with the Department of Digital Design and Information Studies, the Centre for Science-Technology-Society Studies, and the SHAPE – Shaping Digital Citizenship research initiative. His work spans multiple interdisciplinary domains, focusing on the sociotechnical dimensions of digital systems in healthcare, welfare, and organizational contexts. His research interests include IT in healthcare , pervasive computing , gender and technology , organizational change , and qualitative research methods . He employs ethnographic and fieldwork-based approaches to study how digital technologies reshape work practices, citizenship, and care relations. His work often draws on Science and Technology Studies (STS), Actor-Network Theory, and relational ontologies. The recent publications highlight a consistent focus on digital healthcare systems (e.g., Teledialogue), data-driven governance , and the ethical implications of surveillance in welfare . Themes such as vulnerability, privacy, and citizen agency recur across his research, particularly in projects involving digital interventions in social work and patient care. Principal Investigator : Shaping Digital Citizenship – SHAPE (Independent Research Fund Denmark, 2022–2023) Collaborative Projects : CDC: Cultures of Data Collaboration , Teledialog , Håndhygiejne projektet , Sundhedsbarometer projektet He has contributed extensively to academic discourse through journal articles, conference papers, and book chapters, with a strong emphasis on ethnographic depth and theoretical innovation. His public engagement includes media contributions on AI, digital ethics, and urban technology. He has participated in organizing workshops and conferences, including EASST2010 and SHAPE Workshop (2024), and has delivered lectures on technoscience, surveillance, and welfare technology. His collaborations extend across Denmark and internationally, reflecting a robust network in STS and digital society research.

Martin AumüllerView profile

Lecturer

• Algorithms
• Algorithm engineering
• Algorithmic privacy
• +6 more

Martin Aumüller is a Lecturer in Theoretical Computer Science Algorithms at the IT University of Copenhagen . He serves as Head of Education and Master of Software Design , focusing on algorithm engineering, differential privacy, and similarity search. Research interests include: Algorithm engineering for high-dimensional data Locality-sensitive hashing and nearest neighbor search Privacy-preserving machine learning Fairness in approximate search algorithms Benchmarking and evaluation of similarity search tools Publications trends highlight his work on approximate nearest neighbor search , privacy-preserving techniques , clustering algorithms , and scalable outlier detection in high-dimensional spaces. His recent projects (2024-2025) focus on fairness, differential privacy, and efficient indexing. Grants and projects : DIREC (2020-2025): Digital Research Centre Denmark (Innovation Fund Denmark) DIREC: Bias and Benefit of Approximate Nearest Neighbor Search (2022-2025): Principal Investigator (Innovation Fund Denmark) BARC (2017-2024): Basic Algorithms Research Copenhagen (Villum Fonden) SSS (2014-2019): Scalable Similarity Search (European Commission)

• International Trade
• Agricultural Trade Policy
• Agricultural and Food Policy
• +3 more

Wusheng Yu is a full-time Professor in the Department of Food and Resource Economics at the Faculty of Science, University of Copenhagen, holding this position since March 2018 after serving as Associate Professor from 2005-2018. His academic foundation includes a PhD in Agricultural Economics from Purdue University (2000) and an MSc in Economics from Renmin University of China (1995). Educational background: PhD in Agricultural Economics, Purdue University, West Lafayette, IN, USA (2000) MSc in Economics, Renmin University of China, Beijing, China (1995) Professor Yu's research centers on international trade, agricultural policy, computable general equilibrium modeling, and climate-food security intersections. He employs advanced quantitative methods to analyze global trade dynamics and environmental policy impacts, with recent work emphasizing geopolitical dimensions of food systems under climate stress. His methodological approach combines empirical analysis with scenario-based modeling to address real-world policy challenges. Analysis of his 2023-2025 publications reveals three dominant trends: (1) Geostrategic assessments of food security amid global tensions, (2) Climate-agriculture policy integration through emission modeling, and (3) Trade mechanism innovations like carbon border adjustments. His work bridges theoretical economics with actionable policy insights, particularly for EU and developing economies. Professor Yu coordinates graduate courses in Advanced International Trade and Applied Trade and Climate Policy Models. His research is funded by the European Union, Danish governmental bodies, and international organizations, operating under an advisory committee with private sector representatives as specified by departmental Terms of Reference. He maintains strict institutional alignment as a full-time permanent employee without external remuneration. His collaborative network spans seven countries with significant engagement in Danish animal food sectors and public authorities. The Section for Production, Markets and Policy at IFRO serves as his primary research hub, facilitating cross-border studies on trade-displacement effects and food demand elasticity modeling under socioeconomic pathways.

Diego F. AranhaView profile

Associate Professor

• Cryptography
• Cybersecurity
• Homomorphic Encryption
• +7 more

Diego F. Aranha is an Associate Professor in the Department of Computer Science at Aarhus University . His research focuses on cryptographic systems, cybersecurity, and privacy-preserving technologies with applications in voting systems, post-quantum cryptography, and secure computation. He has contributed extensively to homomorphic encryption, secure multiparty computation (MPC), and cryptanalysis of cryptographic implementations. Key projects include: MPCC (2025-2028) : Multi-Party Computation in the Confidential Cloud SCI (2024-2027) : Secure Computation Infrastructures for the Retail Industry RENAIS (2021-2026) : Residue Number Systems for Cryptography His work emphasizes practical efficiency and formal verification of cryptographic protocols. Recent publications highlight advancements in lattice-based cryptography, secure voting schemes, and mitigating side-channel vulnerabilities in post-quantum algorithms. He actively collaborates on open-source cryptographic libraries and standards, with a focus on bridging theoretical security and real-world implementation challenges.

Mogens FosgerauView profile

Professor

• Transport Economics
• Discrete Choice Modeling
• Travel Behavior
• +7 more

Mogens Fosgerau is a Professor in the Department of Technology, Management and Economics at the Technical University of Denmark (DTU), where he conducts research in transport policy and transportation science. His work spans econometrics, travel behavior modeling, and transport economics, contributing to sustainable urban mobility and policy design. Institution: Technical University of Denmark Department: Department of Technology, Management and Economics Email: mogens.fosgerau@econ.ku.dk ORCID: https://orcid.org/0000-0002-6452-5215 His research focuses on discrete choice modeling, travel time valuation, scheduling preferences, and congestion pricing. He develops theoretical and empirical models to understand how individuals make travel decisions under uncertainty and how these behaviors affect urban transport systems. His work integrates economic theory with data-driven methods, often using large-scale datasets and advanced econometric techniques. The recent trend in his publications highlights innovations in perturbed utility models for route choice, stochastic traffic assignment, and the analysis of induced demand for cycling. His research bridges transportation science, behavioral economics, and operations research, with applications in urban planning and policy evaluation. Scientific awards received include: The International Choice Modeling Conference (ICMC) award for Most Innovative Application (2022) Best Overall Paper Award, ITEA Conference (2015) Best Paper Awards from BIVEC-GIVET (2007), Kuhmo-Nectar (2008) Hedorfs Fonds Pris for Transportforskning (2011) Mogens Fosgerau has supervised PhD students such as Fentie Abegaz and has been involved in multiple externally funded research projects, including URBAN (Innovation Fund Denmark), IRUC (Danish Council for Strategic Research), and Horizon 2020 initiatives. He has also served on review panels, including for the Norwegian Research Council, and contributed to peer review and editorial duties. He is actively engaged in research networks and has presented his work at international conferences. His projects often involve interdisciplinary collaboration with researchers in economics, engineering, and urban planning.

• Gravitational Physics
• Astrophysics
• High-Energy Physics
• +3 more

Juno Chan is a Research Fellow at the Niels Bohr Institute , University of Copenhagen , specializing in Theoretical High Energy, Astroparticle and Gravitational Physics . Holding a permanent position since 2025, Chan contributes to advanced research in gravitational wave astronomy and neutron star dynamics. Role: PhD Fellow (converted to Research Fellow) Location: Blegdamsvej 17, Copenhagen Ø Contact: chun.lung.chan@nbi.ku.dk , +45 35 32 87 21 Chan's research focuses on gravitational wave detection , neutron star magnetohydrodynamics , and gravitational lensing in astrophysical contexts. Key contributions include: Developing gravitational wave detection algorithms in lensed systems Modeling magnetized rotating neutron stars with relativistic MHD simulations Curating the LensCAT catalog for known gravitational lenses Multi-messenger lensing studies through LIGO-Virgo-KAGRA collaborations Publications and Research Trends Chan's 15 most recent publications (2023-2025) demonstrate expertise in gravitational wave astronomy , neutron star physics , and computational astrophysics . The work involves: Waveform analysis for lensed events MHD simulations of compact objects Multi-messenger lensing frameworks Signal processing for detector networks Cosmological implications of lensing Collaborations span international institutions in gravitational wave networks, with frequent contributions to Physical Review D and Monthly Notices of the Royal Astronomical Society . No formal awards or student mentorship details are publicly available.

Rebecca Adler-NissenView profile

Professor

• International Relations
• Practice Theory
• Diplomacy
• +8 more

Rebecca Adler-Nissen is a Professor of International Politics at the Department of Political Science , University of Copenhagen , and Director of Strategic Partnerships at the Copenhagen Centre for Social Data Science (SODAS) . Her academic career spans roles as Associate Professor (2013–2016) and Visiting Scholar at institutions like the University of Sydney and McGill University. She holds a PhD (2009) and MSc (2005) from the University of Copenhagen, along with a diploma from Sciences Po, Paris (2002–2003). Her research intersects International Relations , Practice Theory , and Digital Diplomacy , with theoretical emphasis on International Political Sociology , Stigma , and Norms . She explores how digital technologies reshape diplomacy, focusing on sovereignty , disinformation , and EU integration , particularly through projects like Digital Sovereignty (VELUX) and HOPE (Carlsberg). Her 15 most recent articles (2021–2024) examine topics like digital sovereignty in Gaia-X, blended diplomacy through social media, and contestation of the liberal order . Keywords span International Relations , EU Policy , and Science and Technology Studies . Scientific Awards Distinguished Scholar in Diplomatic Studies EliteForsk Prize Nils Klim Prize Royal Danish Academy of Sciences and Letters Silver Medal (2017) Carlsberg Foundation’s Researcher of the Month (2021) She supervises PhD students including Anna Helene Kvist Møller and Nicklas Johansen, and has advised completed candidates like Alexei Tsinovoi and Yevgeniy Golovchenko. Her advisory roles include the Danish Government’s Expert Group on Tech Giants and the Danish Intelligence Oversight Board . She co-leads projects funded by the VELUX Foundation and Carlsberg Foundation .

Petar PopovskiView profile

Professor

• Wireless Communication
• Internet of Things
• Ultra-Reliable Low Latency Communication
• +12 more

Petar Popovski is a Professor at the Department of Electronic Systems within the Technical Faculty of IT and Design at Aalborg University, Denmark. His research focuses on next-generation wireless communication systems, with a strong emphasis on ultra-reliable low-latency communication (URLLC), Internet of Things (IoT), multiple access, and 6G technologies. He leads several high-impact research projects, including the Classique - Center for Classical Communication in the Quantum Era funded by the Danish National Research Foundation and WATER (Wireless Architectures for intelligent and Trusted connectivity in the posT-5G ERa) supported by Villum Fonden. His research interests span key areas in modern communication theory and systems, including random access , non-terrestrial networks , satellite communication , and machine learning for reliable communication . He is actively involved in advancing the integration of sensing and communication, digital twin technologies, and quantum-era classical communication frameworks. The recent publications highlight a strong trend toward deterministic and reliable access in wireless networks, integration of sensing and communication for industrial automation, and novel physical-layer techniques using reconfigurable intelligent surfaces. These works are published in top IEEE journals such as IEEE Transactions on Communications , IEEE Transactions on Haptics , and IEEE Transactions on Vehicular Technology . Award highlights include the Best Student Paper Award (2021) , recognizing his mentorship and collaborative research excellence. Prof. Popovski serves as a principal investigator (PI) and supervisor in multiple research projects, securing significant funding from national and international bodies such as the Danish National Research Foundation and the European Space Agency (ESA). He hosts visiting researchers regularly and contributes to scientific leadership through editorial roles and conference participation. He is a key figure in the Connectivity section at Aalborg University and leads cutting-edge research in future wireless systems, contributing to both theoretical foundations and practical implementations in smart infrastructure, space communication, and dependable 6G networks.

• Machine Learning
• Artificial Intelligence
• Data Analysis
• +7 more

Jonathan Voersaa Wenshøj is an academic researcher at the Department of Computer Science, University of Copenhagen. He contributes to the Machine Learning section's activities spanning theoretical foundations and applications in diverse domains like information retrieval, medical data analysis, remote sensing, sustainability, and biological modeling. The section participates in the SCIENCE AI Centre and collaborates with initiatives like TreeSense for global tree resource analysis. His research intersects machine learning with quantum computing, medical informatics, and sustainability. Recent publications highlight applications in environmental monitoring, healthcare diagnostics, and energy-efficient AI systems. The department provides advanced compute resources including a powerful cluster for intensive machine learning tasks. This researcher's work appears in diverse machine learning domains, with recent publications addressing quantum-inspired architectures, explainable AI in medical imaging, and sustainable computing practices. The section actively hosts events including seminars, conferences, and PhD defences related to machine learning advancements.

• Machine Learning
• Artificial Intelligence
• Quantum Computing
• +5 more

Sophia Natasha Wilson is a Research Fellow in the Department of Computer Science (DIKU) at the University of Copenhagen, specializing in machine learning applications across interdisciplinary domains. She is affiliated with the SCIENCE AI Centre and holds a cross-departmental position at the Niels Bohr Institute . Her research bridges theoretical machine learning with practical implementations in healthcare, quantum computing, and environmental sustainability. University of Copenhagen Department of Computer Science (DIKU) Niels Bohr Institute SCIENCE AI Centre Her research focuses include: Quantum-enhanced machine learning algorithms Explainable AI for healthcare applications Environmental sustainability in computing Emotion-aware language models Quantum computing hardware optimization Public health risk modeling Her recent publications demonstrate cross-disciplinary work in quantum machine learning (hybrid optical processors, qubit stabilization), health informatics (hypothyroidism analysis, nursing values evaluation), and ethical AI (sustainable AI, fairness in recommender systems). Technical work also appears in non-Euclidean generative models and real-time adaptive systems . Current projects include quantum dot array simulation (QDarts platform) and federated learning for personalized medicine . She contributes to the TreeSense center for remote sensing of global tree resources and works on climate-aware AI frameworks.

• Natural Language Processing
• Legal Informatics
• Multilingual NLP
• +3 more

Ilias Chalkidis is an Assistant Professor specializing in Natural Language Processing at the Department of Computer Science, University of Copenhagen. He is actively affiliated with the Natural Language Processing research section, contributing to both theoretical and applied advancements in the field. His research spans multiple high-impact domains with particular emphasis on: Legal natural language processing and multilingual legal reasoning Large language model applications in political and social contexts Fairness-explainability trade-offs in AI systems Innovative representation learning techniques for textual data Analysis of his recent publications reveals a strong focus on bridging legal informatics with cutting-edge NLP methodologies. His work on multilingual legal corpora (including the 689GB MultiLegalPile dataset) and legal decision influence prediction demonstrates practical applications for judicial systems. Simultaneously, his investigations into LLMs as voting assistants and European political spectrum analysis showcase innovative intersections between computational social science and language technology. His technical contributions to contrastive learning and hyperbolic embeddings provide foundational advances for document representation. Chalkidis actively participates in the research community through workshop organization (Natural Legal Language Processing Workshop 2023-2024) and conference presentations. His research has been published in top-tier venues including ACL, EMNLP, and ECAI, with significant citations reflecting community impact. While specific advising relationships aren't documented in the provided materials, his collaborative work patterns suggest active mentorship within the NLP research ecosystem.

• Business Process Management
• Declarative Process Modeling
• Hybrid Process Notations
• +5 more

Tijs Slaats is an Associate Professor in the Software, Data, People & Society section at the Department of Computer Science, University of Copenhagen. His research focuses on Business Process Management with particular emphasis on declarative and hybrid process notations to provide flexible workflow support for knowledge workers, funded by the Danish Council for Independent Research. His educational background includes: M.Sc. in Information Technology from IT University of Copenhagen Ph.D. in Computer Science from IT University of Copenhagen (supervised by Thomas Hildebrandt) Dr. Slaats specializes in declarative process modeling, particularly Dynamic Condition Response (DCR) graphs which enable flexible workflow systems. His work bridges theoretical foundations with practical applications in cross-organizational settings. Recent research extends into blockchain technologies, smart contracts, and applications in sensitive domains like asylum processing and refugee law. He combines formal methods with empirical evaluation to ensure both correctness and usability of workflow systems. His publication pattern shows increasing application of process mining techniques to blockchain technologies and socially impactful domains, while maintaining core research in Business Process Management. Notable trends include integration of DCR graphs with smart contracts, privacy-preserving techniques for asylum data, and object-centric approaches to process discovery. Research funding includes: Hybrid Business Process Management Technologies project (Danish Council for Independent Research) Technologies for Flexible Cross-organizational Case Management Systems (FLExCMS) industrial Ph.D. project Alongside his academic work, Dr. Slaats maintains strong industry connections through Exformatics A/S where he developed the DCR Graphs workflow solution (www.dcrgraphs.net), and previously worked as a software engineer in the Dutch e-commerce sector. His dual expertise in academia and industry ensures his research addresses real-world workflow challenges while maintaining theoretical rigor.

Nika AkopianView profile

Associate Professor

• Quantum Photonics
• Nanowire Quantum Dots
• Quantum Networks
• +3 more

Nika Akopian is an Associate Professor and Group Leader at the Quantum Networks Group within the Department of Electrical and Photonics Engineering at the Technical University of Denmark (DTU). His research focuses on quantum nanophotonics, nanowire quantum dots, and multi-qubit photonic devices, with a particular emphasis on hybrid atomic-solid state systems and epsilon-near-zero materials for quantum networks. He leads the MultiQubit project funded by an ERC Consolidator Grant, exploring multi-qubit quantum photonic devices. Education includes a Ph.D. in Physics from the Technion – Israel Institute of Technology (2008), followed by postdoctoral research at Delft and Eindhoven Universities of Technology. Key awards include the ERC Consolidator Grant (2020), Villum Young Investigator Program (2014), and Veni Grant (2008). Research interests span quantum control of nanowire quantum dots, hybrid systems coupling quantum dots to atomic vapors, and epsilon-near-zero materials for integrated quantum networks. Major contributions include demonstrating frequency-locked quantum dot emission to atomic transitions and developing crystal-phase quantum dots in nanowires. Scientific awards highlight his work, including the IUPAP Young Author Award (2006) and Gutwirth Fellowship (2006). His team includes advisees such as A. Srikanth, R. Radhakrishnan, and D. Li. Current projects involve advancing quantum networks and multi-qubit photonic devices.