Find Academic Supervisors

• Algorithms
• Algorithmics
• Big Data
• +7 more

Stephen Alstrup is a Professor in the Algorithms and Complexity section at the Department of Computer Science (DIKU), University of Copenhagen, Faculty of Science. His research bridges theoretical computer science with practical applications in modern computational challenges. His primary research interests include: Algorithm design and analysis Graph algorithms and data structures Big Data processing techniques Streaming algorithms and Internet distribution Theoretical foundations with practical implementations Alstrup's work demonstrates how theoretical algorithm research can lead to real-world applications, as evidenced by his development of Octoshape technology for large-scale Internet streaming. His research spans from fundamental theoretical problems to applications in Big Data, cloud computing, and information retrieval systems. He has published extensively with 93 research outputs including journal articles, conference proceedings, and books. His recent work focuses on graph spanners, semantic hashing, recommendation systems, and universal graph structures, showing continued productivity in theoretical computer science. Alstrup actively engages with industry and media, contributing to discussions about Big Data applications, technology innovation, and how businesses can collaborate with universities to access cutting-edge knowledge and funding opportunities. His work has been featured in 10 media contributions discussing practical applications of algorithms in education, municipal IT projects, and business innovation.

Eva ErikssonView profile

Associate Professor

• Human-Computer Interaction
• Participatory Design
• Interaction Design
• +7 more

Eva Eriksson is an Associate Professor at Aarhus University, affiliated with the School of Communication and Culture and the Department of Digital Design and Information Studies. Her work bridges design, technology, and social values, focusing on participatory and human-centered approaches. Her research interests center on Human-Computer Interaction (HCI) , Participatory Design , and Design for Sustainability . She explores how co-design methods can empower youth, support children with learning differences like dyscalculia, and integrate more-than-human perspectives—considering non-human actors such as nature and technology—in design processes. Her work emphasizes ethical, inclusive, and reflective design practices. The recent publications highlight a strong trend in co-design with youth , XR and AR for education , sustainable technology , and methodological innovation in design research . These works span case studies, scoping reviews, and conceptual provocations, often published in top-tier venues like CHI and Interacting with Computers . Honourable Mention Award at CHI 2020 Honorable Mention, Design Space, CHI 2021 Most Cited Paper of 2021, International Journal of Child-Computer Interaction Eva Eriksson leads and contributes to externally funded research projects such as COMPILE (focused on dyscalculia and AR) and MOVA (on more-than-human values in design education), supported by the Independent Research Fund Denmark and Erasmus+. She supervises student projects and teaches courses such as Co-design and Bachelor Project . She also serves on international PhD examination and evaluation panels, demonstrating her active role in the global academic community. She is a core member of the Center for Computational Thinking & Design (CCTD) , a multidisciplinary research center at Aarhus University that fosters innovation in design, education, and technology.

Arijit KhanView profile

Associate Professor

• Graph Neural Networks
• Blockchain
• Data Management
• +5 more

Arijit Khan is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark. He leads the Data Engineering, Science and Systems group and is affiliated with the Technical Faculty of IT and Design. His research focuses on Graph Neural Networks , Blockchain , Data Management , and AI interpretability . He is the Principal Investigator (PI) of a major project on Data Management, Fundamental Algorithms, and Machine Learning for Emerging Problems in Large Networks (2022–2027). Research Interests : Graph Data Management & Machine Learning Blockchain Transaction Analysis Large Language Model + Knowledge Graph Synergies Healthcare AI (e.g., ICU glucose prediction) Explainable AI for Graph Neural Networks Research Trends : His publications emphasize neuro-symbolic systems , uncertain graph analysis , and AI-driven blockchain insights . Recent work bridges large language models with knowledge graphs and explores GPU performance optimization via shader code analysis. Awards & Grants : No explicit awards listed, but his active research grants include a 5-year project on large network analysis with interdisciplinary applications in life and health sciences. Funding emphasizes algorithmic innovation and data science integration. Labs/Teams : Head of the Data Engineering, Science and Systems research group, focusing on AI for societal impact ('AI for the People') and scalable graph data systems. Collaborations span blockchain analytics, healthcare informatics, and GPU architecture design.

Peter SestoftView profile

Professor

• Programming Languages
• Software Development
• Parallel Programming
• +4 more

Peter Sestoft is a Professor at the IT University of Copenhagen (ITU), leading the Computer Science Department since 2017. His primary roles include academic leadership, research in programming languages and software engineering, and teaching. He holds a PhD in Computer Science from the University of Copenhagen (1991) and has held academic positions at institutions like the Royal Veterinary and Agricultural University and the Technical University of Denmark before joining ITU in 1999. His research focuses on programming languages, functional and managed object-oriented languages, parallel programming, compilers, and spreadsheet implementation technologies. He has developed influential tools like the C5 Generic Collection Library for C# and Moscow ML, a Standard ML implementation. His work on Funcalc and Corecalc advanced spreadsheet technology with user-defined functions and efficient recalculation algorithms. Key contributions include over 30 publications, including books on programming language concepts and Java/C# syntax. He has led major research projects such as 'Popular Parallel Programming' (P3) and 'Probabli' for actuarial calculations. His academic service includes roles on national grant committees and international conference organizing committees. Notable advising includes PhD students like Andrzej Wasowski (ITU Professor) and David Christiansen (Director of Haskell Foundation). His work has been recognized through grants exceeding 25 million DKK and collaborations with institutions like Microsoft Research and Harvard University.

Martin ElsmanView profile

Professor

• Programming Languages
• Theory of Computation
• Functional Programming
• +5 more

Martin Elsman is a full-time Professor in the Programming Languages and Theory of Computation section at the Department of Computer Science, University of Copenhagen (DIKU). He serves as head of the PLTC section and head of studies for the BSc education in Computer Science and Economics. Elsman is also an active maintainer of several software tools including the MLKit and SMLtoJs. Joined DIKU in 2012 after 4 years at SimCorp (2008-2012) and previous Associate Professorship at IT University of Copenhagen (2003-2008). Co-developer of Futhark, TAIL APL compiler, SMLtoJs, and SMLserver. Education: M.Sc. in Engineering, Technical University of Denmark Ph.D. in Computer Science, University of Copenhagen (DIKU), supervised by Mads Tofte. Research Interests: Elsman works on programming language design and implementation, with a focus on functional programming, module systems, domain-specific languages for financial contracts, region-based memory management, compilation techniques for parallelism, program optimization, and static type systems. His work spans both theoretical and applied domains, including blockchain-based financial contract execution, web technology, and GPU programming using functional languages. Publication Trends: His recent articles focus on functional programming, array programming, parallelism, and memory management. Topics include region inference, type systems for data-parallelism, program optimization techniques, and domain-specific compilation for financial and quantum computing. He frequently collaborates with Troels Henriksen and others on tools like Futhark and MLKit.

• Cryptology
• Post-Quantum Cryptography
• Embedded Security
• +3 more

Ruben Niederhagen is an Associate Professor at the Department of Mathematics and Computer Science, University of Southern Denmark. His roles include affiliation with the Digital Democracy Centre and the VIP group in Artificial Intelligence, Cybersecurity, and Programming Languages. He holds external positions as Assistant Research Fellow at Academia Sinica (since 2022) and previously led the 'Advanced Cryptographic Engineering' and 'Post-Quantum Cryptography' departments at Fraunhofer SIT (2016–2020). He earned his PhD in Mathematics and Computer Science from Eindhoven University of Technology (2010–2012). His research focuses on cryptology, post-quantum cryptography, and embedded security. Key areas include quantum-resistant algorithms, cryptographic protocols, and hardware security implementations. His work addresses challenges like signature scheme optimization, electric vehicle cybersecurity, and quotable signature systems for data authenticity. Niederhagen has been featured in multiple media outlets discussing post-quantum cryptography’s role in future security. He teaches courses such as Cryptographic Engineering (DM886) and Networks and Cybersecurity (DM572). His research outputs span 33 publications, including book chapters and peer-reviewed conference papers, with a focus on practical implementations and theoretical advancements in cryptographic systems.

Anders MøllerView profile

Professor

• Programming Languages
• Software Engineering
• Static Program Analysis
• +4 more

Anders Møller is a Professor and Vice Head of Department at the Department of Computer Science, Aarhus University, Denmark. He is a leading researcher in programming languages and software engineering, with a primary focus on static and dynamic program analysis. He serves as Chairman of the PhD Committee and holds leadership roles in the international research community, including Vice-Chair of ACM SIGPLAN and Associate Editor for ACM TOPLAS and ACM TOSEM. His research interests include programming languages, software engineering, static and dynamic analysis, program verification, and security. His work bridges theoretical foundations and practical applications, particularly in improving software reliability and security through advanced analysis techniques. The trends in his recent publications reflect a strong emphasis on static analysis for security, scalability, and real-world impact—especially in web applications, smart contracts, and open-source software supply chains. His research has evolved toward practical deployment, demonstrated by the founding and acquisition of Coana by Socket in 2025 for enhanced vulnerability detection. Recipient of the Danish Elite Research Prize 2020 ACM Distinguished Member He actively mentors students and contributes to the academic community through conference leadership (e.g., OOPSLA, PLDI, ICSE). He also co-authored the widely used textbook Static Program Analysis with Michael I. Schwartzbach. His work is deeply integrated into both academic and industrial advancements in software analysis and security.

Carsten Munk-HansenView profile

Professor

• Property Law
• Civil Law
• Legal Methodology
• +6 more

Carsten Munk-Hansen is a Professor of Law at the Department of Law, Aalborg University, within the Faculty of Social Sciences and Humanities. He specializes in property law, civil law, and legal methodology. His research focuses on legal aspects of property transactions, environmental protection, urban planning, liability issues, and legal theory. Notable works include the three-volume treatise on property law (Fast ejendom I-III), a textbook on legal theory (Retsvidenskabsteori), and analyses of real estate brokerage regulations. He has held leadership roles in academic committees, including chairing the Planklagenævnet under the Danish Ministry of Industry, Business and Financial Affairs (2017-2021). Research interests span property-related legal topics such as land registration, servitudes, neighbor rights, zoning, environmental law, expropriation, and construction law. He has also explored liability issues for professionals and real estate agents, as well as psychological-economic factors in real estate transactions. His work integrates legal theory, jurisprudence, and practical regulatory challenges. Awarded 'Årgangens underviser 2008-2013' for teaching excellence in legal studies, Munk-Hansen has taught courses on legal theory, contract law, insurance law, and Roman law. He currently oversees courses in property law, insurance law, and legal methodology. Recent activities include serving on academic review committees at the University of Southern Denmark (2025) and University of Copenhagen (2025). Key publications emphasize critical analysis of property law frameworks, including contractual obligations, enforcement mechanisms, and evolving legal standards. His research also addresses modern challenges like environmental protection in property use and digital compliance in real estate brokerage. Media engagements (84+ items) highlight his influence in public discourse on property law controversies and urban development issues.

Anders BondeView profile

Associate Professor

• Musicology
• Sound Branding
• Media Psychology
• +7 more

Anders Bonde is an Associate Professor at Aalborg University's Department of Communication and Psychology, within The Faculty of Social Sciences and Humanities. His research focuses on music analysis, sound branding, media psychology, and the interplay between music and audiovisual media. He employs both qualitative and quantitative methods, integrating diverse data into aesthetically informed frameworks. His work bridges musicology, media studies, semiotics, aesthetics, affective computing, and data visualization. Teaching responsibilities include courses in music theory, voice leading, sound branding, and epistemology across programs in Music, Communication, and Media Studies. He leads the Study Board for Art, Health, and Technology, overseeing programs in Music Therapy, Art and Technology, and Nordic master's programs in Visual Studies and Media Arts. Research projects include investigations into sound branding, audiovisual interaction effects, and multimodal meaning-making. Notable outputs include works on the aesthetics of ambiguity in 20th-century music, sensory atmospheres in retail contexts, and the effectiveness of non-musical sound branding. His work spans theoretical frameworks, empirical studies, and interdisciplinary collaborations. Recent articles explore interactive music visualization, sound branding conceptualizations, and the role of music in advertising. Media engagement includes commentary on sound branding strategies and its psychological impacts. Grants and collaborations reflect his commitment to bridging theoretical and applied research.

• Quantum Physics
• Semiconductor Devices
• Quantum Computing
• +4 more

Anasua Chatterjee is a researcher at the Center for Quantum Devices, part of the Niels Bohr Institute at the University of Copenhagen. Her work focuses on quantum dot arrays, spin qubits, and semiconductor-based quantum computing platforms. She collaborates with leading quantum research groups and contributes to advancements in quantum device calibration, optimization, and noise mitigation. Affiliation: Center for Quantum Devices, Niels Bohr Institute, University of Copenhagen Her research spans quantum device automation, charge sensing, and real-time control of qubit fluctuations. Recent publications highlight her expertise in radio-frequency reflectometry, gate voltage optimization, and topological superconductivity in hybrid devices. Key article trends include autonomous calibration of quantum dots using evolutionary algorithms, spin qubit control via FPGA-based feedback systems, and integration of superconducting elements with semiconductor platforms. These studies often involve collaborations with institutions in the U.S. and Europe. While no formal awards are listed in the provided texts, her work appears integral to scaling quantum processors and improving qubit coherence for fault-tolerant systems.

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.

• Machine Learning
• Data Systems
• Resource-Aware Computing
• +5 more

Pinar Tözün is an Associate Professor and Head of the Data, Systems, and Robotics department at the IT University of Copenhagen. She leads multiple research groups, including the Resource-Aware Data Systems and Data-intensive Systems and Applications. Her roles also include academic responsibility for DASYA and involvement in the Center for Climate IT. Her research focuses on resource-aware computing, machine learning systems, heterogeneous hardware optimization, and sustainable data management. Key areas include workload characterization, GPU utilization, and benchmarking frameworks for edge devices and cloud systems. Dr. Tözün has led significant projects such as MOTH (Machine Learning on Tiny Hardware), RAD+ (Resource-Aware Data Science), and DAPHNE (Integrated Data Analysis Pipelines), funded by institutions like the Novo Nordisk Foundation and the European Commission. She has published extensively in top venues, including Proc. ACM Manag. Data and Dagstuhl Reports, with a focus on efficient machine learning pipelines and hardware-aware systems. Her work has been highlighted in media discussions on sustainable hardware and software practices. Tözün also actively participates in academic governance, serving on hiring committees and shaping future faculty recruitment in data-intensive systems.

Alan IrwinView profile

Professor

• Science and Technology Studies
• Citizen Science
• Innovation Policy
• +5 more

Alan Irwin is a Professor at Copenhagen Business School , affiliated with the Department of Organization . His work bridges Science and Technology Studies (STS) with innovation policy , citizen science , and organizational research , emphasizing the intersection of science, society, and governance. Research Interests : Science communication, academic-industry relations, public engagement with science, and transformative innovation policy. Recent Publications : Focus on global-local policy dynamics, citizen science during crises, and organizational frameworks for sustainable innovation. Media Engagement : Active contributor to public discourse, with 33 media appearances discussing topics like citizen science , academic leadership , and science policy . His academic contributions highlight the role of STS in addressing contemporary challenges, from pandemic response to institutional governance, while advocating for inclusive and socially responsible scientific practices.

• Computer Science
• Programming Language Technology
• Theory of Computation
• +6 more

Johannes Tang Reuss is a Lecturer at the Department of Computer Science , University of Copenhagen , affiliated with the Programming Languages and Theory of Computation (PLTC) section. His role involves teaching and research in programming language technology, software security, and distributed systems, with a focus on blockchain and fintech applications. He can be contacted via emails: bkp334@psy.ku.dk (possibly related to the Psychology Study Board) and jtre@di.ku.dk . The PLTC section at DIKU conducts interdisciplinary research in areas such as: Decentralized Systems : blockchain, distributed ledger technology, and smart contracts Security & Privacy : software-based security techniques and quantum cryptography Functional Technology : compiler research for GPUs/multicore CPUs Quantum Programming : design of quantum computing languages

• Programming Languages
• Theory of Computation
• Computer Security
• +3 more

William Shi is an Instructor at the Department of Computer Science, University of Copenhagen. His academic work is aligned with the Programming Languages and Theory of Computation Section (PLTC), which focuses on programming language technology and theoretical aspects of computation. The PLTC section engages in interdisciplinary research across areas such as decentralized systems, security and privacy, functional programming for high-performance architectures, and quantum computing. Specific projects include blockchain technology, formal verification, and probabilistic programming with applications in bioinformatics and AI-driven vaccine design. Research interests intersect algorithmic programming, formal methods, and applied domains like fintech and cybersecurity. While no direct information about William Shi's specific research contributions, awards, or publications is available in the provided text, his affiliation with PLTC suggests involvement in cutting-edge computational theory and its practical implementations.