جستجوی استاد راهنمای دانشگاهی

Kunihiko Kanekoمشاهده پروفایل

استاد

• Theoretical Biophysics
• Complex Systems
• Chaos
• +۶ مورد دیگر

Kunihiko Kaneko is a Professor at the Niels Bohr Institute, University of Copenhagen, with a distinguished career in theoretical biophysics and complex systems. He received his PhD and MSc in Physics from the University of Tokyo, and has held leadership roles at the Universal Biology Institute and Center for Complex Systems Biology. PhD Physics, 1984 - University of Tokyo MSc Physics, 1981 - University of Tokyo His research spans five primary areas: Universal Biology, Evolutionary Constraints, Ecosystem Dynamics, Neural Cognition, and Universal Anthropology. He has published extensively on multi-level consistency principles, dimensional reduction in biological systems, and reciprocity between robustness and plasticity across scales. Recent publications show strong focus on microbial ecosystems (2025), evolutionary game theory (2025), neural modular architectures (2024), and dimensional reduction in cellular systems (2024). His work bridges physics and biology through dynamical systems theory applied to diverse phenomena from protocells to human societies.

Philip Billeمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• String Processing
• +۹ مورد دیگر

Philip Bille is a Professor and Head of the Algorithms, Logic and Graphs section at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), College of Engineering. His research centers on the design and analysis of efficient algorithms, particularly for string processing, compressed data, and data structures. His research interests lie at the intersection of theoretical computer science and practical applications. He focuses on algorithms , data structures , string indexing , pattern matching , and compressed computation . His work enables efficient querying and processing of large-scale, repetitive data, with applications in bioinformatics, intrusion detection, and green computing. The recent publications reflect a strong trend in developing space-efficient and fast algorithms for modern computational challenges. Key themes include compressed data structures , sliding window indexing , finite automata compression , and energy-aware matrix operations . These works demonstrate expertise in balancing theoretical rigor with practical performance. Philip Bille actively supervises multiple PhD students and leads several research projects. He contributes to advancing sustainable computing aligned with UN SDGs. His work integrates algorithmic theory with real-world efficiency. Supervises PhD projects on hierarchical compression, adaptive computation, and vector processor algorithms. Involved in research on green computing, compressed formats, and efficient data models. He is affiliated with the Algorithms, Logic and Graphs group at DTU, a hub for theoretical and applied algorithmic research. The team explores fundamental problems in data representation and processing, pushing the boundaries of what is computationally feasible in terms of time and space.

Abayomi Baiyereمشاهده پروفایل

دانشیار

• Digital Transformation
• Information Systems
• Digital Strategy
• +۶ مورد دیگر

Abayomi Baiyere serves as an Associate Professor in the Department of Digitalization at Copenhagen Business School (CBS), where he conducts cutting-edge research at the intersection of digital technologies and organizational transformation. His work significantly contributes to UN Sustainable Development Goals through digitally-enabled societal impact initiatives and has yielded 69 research outputs including high-impact publications in premier journals like Information Systems Journal and Information Systems Research . His research program focuses on: Digital transformation frameworks (notably the MIND framework for capability assessment) Platform design and governance mechanisms Smart service systems development Workplace transformation through digital subtraction logic Digital strategy implementation challenges Analysis of his 15 most recent publications (2024-2025) reveals a strong theoretical grounding in institutional and practice-based perspectives, with increasing emphasis on ethical dimensions of digital transformation, AI implementation constraints, and methodological innovations in computational research. His work consistently bridges conceptual rigor with practical applicability for organizational leaders. Dr. Baiyere actively shapes academic discourse through editorial roles including co-editing The Routledge Companion to Management Information Systems (2025) and organizing key events like the African IS Paper Development Workshop (2020). His public engagement includes 6 media contributions discussing digital workplace transformation and strategic implementation challenges, demonstrating commitment to translating research into practical insights for broader audiences. Within CBS, he has supervised 8 academic works while contributing to the department's international recognition in digitalization research. His activities reflect deep engagement with both theoretical advancement in information systems and practical solutions for organizational digital maturity.

• Natural Language Processing
• Explainable AI
• Fact-Checking
• +۴ مورد دیگر

Isabelle Augenstein is a Professor at the University of Copenhagen, Department of Computer Science (DIKU), where she heads the Copenhagen Natural Language Understanding (CopeNLU) research group and the Natural Language Processing section. She is also a co-lead of the Danish Pioneer Centre for Artificial Intelligence, Denmark's largest research center initiated by the Danish Ministry of Higher Education and Science. In October 2022, she became Denmark's youngest ever female full professor. Dr. Augenstein earned her undergraduate degree in Computational Linguistics and Psychology from Heidelberg University, followed by a Master's in Computational Linguistics. She completed her PhD in Computer Science at the University of Sheffield under the supervision of Dr. Diana Maynard and Prof. Fabio Ciravegna. In 2021, she earned a Habilitation at the University of Copenhagen in Explainable Fact-checking. Professor Augenstein's primary research focuses on fair and accountable Natural Language Processing, with particular emphasis on explainability, factuality, and bias detection. Her work spans multiple subfields including automated fact-checking, stance detection, gender bias analysis, and cultural bias in language models. She has pioneered research in explainable fact-checking, developing methods that not only predict claim veracity but also provide meaningful explanations of the decision-making process. Her research group has produced numerous influential papers on measuring model fragility, quantifying gender biases, and developing robust fact-checking systems that account for distribution shifts. Her significant contributions have been recognized with several prestigious awards: ERC Starting Grant on 'Explainable and Robust Automatic Fact Checking' DFF Sapere Aude Research Leader fellowship on 'Learning to Explain Attitudes on Social Media' Karen Spärck Jones Award from the British Computing Society and Bloomberg Hartmann Diploma Prize from the Hartmann Foundation Member of the Royal Danish Academy of Sciences and Letters since 2024 Professor Augenstein has secured significant research funding including her ERC Starting Grant supporting five years of blue-sky research. She actively mentors PhD students and postdoctoral researchers through her 'ExplainYourself' project. She served as President of SIGDAT (which organizes the EMNLP conference series), having previously held leadership roles as Vice President and Vice President-Elect. She is a co-founder of Widening NLP (WiNLP), an initiative to increase diversity in the NLP community, and maintains the BIG Directory of underrepresented groups in NLP. She leads the Copenhagen Natural Language Understanding (CopeNLU) research group, which relocated to the historic Østervold Observatory in Copenhagen's Botanical Gardens in 2023. The group focuses on developing methods for explainable and robust natural language understanding, with applications in fact-checking, bias detection, and social media analysis. Professor Augenstein also co-leads the Speech and Language collaboratory at the Pioneer Centre for Artificial Intelligence, where her team investigates how language models can better serve diverse populations while maintaining accountability and transparency.

Joachim Kockمشاهده پروفایل

دانشیار

• Category theory
• Homotopy theory
• Combinatorics
• +۴ مورد دیگر

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)

Johannes Bjervaمشاهده پروفایل

استاد

• Natural Language Processing
• Artificial Intelligence
• Linguistic Typology
• +۵ مورد دیگر

Johannes Bjerva is a Full Professor at Aalborg University's Department of Computer Science (Campus Copenhagen), leading the Copenhagen branch and conducting interdisciplinary NLP research integrating linguistic typology. His work focuses on low-resource languages, language model security, and societal AI impact. PhD (University of Groningen, 2017): Thesis on multitask/multilingual lexical modeling M.A. & B.A. in Computational Linguistics (Stockholm University) Research interests span linguistically-informed NLP , language model security , and low-resource language technology . Current projects include the DFF Sapere Aude grant (2025) for language model detection security and the LM2-SEC project (2025–2030). His 2024 ACL paper on embedding inversion security and 2024 EMNLP paper on typological diversity exemplify recent work. Scientific awards include: 2021: Teacher of the Year (AAU Computer Science) 2019: Google Cloud research credits 2022: Carlsberg Semper Ardens (5M DKK) 2024: Novo Nordisk Data Science grant (~10M DKK) Supervision includes 8 PhD students across projects like CreoleVal and HiFi-KPI . He serves on the Industrial Researcher Committee at Innovation Fund Denmark and is a member of Det Unge Akademi (2023–2028).

Markus Listمشاهده پروفایل

استاد

• Data Science
• Systems Biology
• Bioinformatics
• +۴ مورد دیگر

Prof. Dr. Markus List is a Professor of Data Science of Systems Biology at the TUM School of Life Sciences, Technical University of Munich (since 2023). He previously served as Group Leader at the Chair of Experimental Bioinformatics (2018–2023) and held a PostDoc position in Computational Biology at the Max-Planck Institute for Informatics (2015–2018). His educational background includes a PhD in Molecular Oncology, an MSc in Bioinformatics from the University of Southern Denmark, and BSc and further studies in Bioinformatics at Eberhard-Karls Universität Tübingen. Current Role: Professor of Data Science and Systems Biology Previous Roles: Group Leader, PostDoc, and Academic Researcher His research focuses on interdisciplinary applications of data science to systems biology, bioinformatics, and molecular oncology. He also explores organizational theory, innovation processes, and the dynamics of routines in management contexts. His work bridges computational methods and organizational challenges, addressing topics like digital twins, distributed innovation, and strategic adaptation. Key contributions include studies on organizational imprinting, digital transformation in firms, and the role of routines in institutional dynamics. His research has been published in top-tier journals and presented at international conferences.

Elli Anastasiadiمشاهده پروفایل

استادیار

• Formal Verification
• Concurrency Theory
• Parallel Programs
• +۷ مورد دیگر

Elli Anastasiadi is an Assistant Professor in the Department of Computer Science at Aalborg University, part of the Technical Faculty of IT and Design. She is a member of the DEIS (Distributed, Embedded and Intelligent Systems) research group, which focuses on formal methods, verification, and intelligent systems. Prior to her current role, she was a postdoctoral researcher at Uppsala University and completed her PhD at Reykjavik University. Education: PhD in Computer Science, Reykjavik University (2022) Master’s in Applied Mathematics and Computer Science, NTUA, Greece Her research centers on formal verification of concurrent and parallel systems , with emphasis on runtime verification, process algebra, and logical foundations. She works extensively with hyperproperties, modal logic, and equational reasoning. Her work bridges theoretical computer science with practical verification tools. Recent publications show a strong trend in logic-based verification , particularly in modal and temporal logics, recursion, and monitor synthesis. Her work often involves complexity analysis and axiomatization of logical systems. Scientific Awards: PhD grant from Reykjavik University research fund She has advised no publicly listed students yet and is actively involved in academic service, including co-organizing workshops and being an invited speaker. She collaborates closely with leading researchers in concurrency theory and formal methods. Labs and Teams: Member of the DEIS research group at Aalborg University, contributing to projects on verification, distributed systems, and intelligent decision-making.

Matteo Acclavioمشاهده پروفایل

استادیار

• Proof Theory
• Logic in Computer Science
• Concurrency Theory
• +۵ مورد دیگر

Matteo Acclavio is an Assistant Professor in Computer Science at the School of Engineering and Informatics, University of Sussex, affiliated with the Foundations of Software Systems (FoSS) research group. A logician specializing in proof theory and its applications to computer science, his work bridges mathematical logic with concurrency theory and process calculi. Education: PhD in Mathematics, Aix-Marseille University, France Master in Discrete Mathematics and Foundations of Theoretical Computer Science, Aix-Marseille University Master in Mathematics, Roma Tre University, Italy Bachelor in Mathematics, Roma Tre University His research focuses on graphical proof systems, linear logic, modal logic, and concurrency theory. Publications highlight contributions to deep inference, sequent calculus, and the intersection of logic with distributed systems. Recent work explores logical frameworks for concurrency, such as choreographic programming, and graphical models for proof systems. He teaches courses like Operating Systems and maintains active collaborations in theoretical computer science.

Michael Reichhardt Hansenمشاهده پروفایل

دانشیار

• Formal Methods
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

Michael Reichhardt Hansen is an Associate Professor at the Department of Applied Mathematics and Computer Science (DTU Compute) at the Technical University of Denmark. He holds a MSc in Engineering (1982) and a PhD in Computer Science (1987) from DTU. He has held postdoctoral and visiting roles, including a fellowship at IBM Research Center (1984–1985) and a guest professorship at Oldenburg University (1992–1993). His research focuses on formal methods, embedded systems, and real-time systems, emphasizing mathematically grounded software development. He has authored/co-authored three books and over 70 scientific articles. Research interests include model-based program construction, temporal logic, functional programming, and ontology alignment. He has led projects on ontology matching frameworks (e.g., MDMapper) and formal methods for real-time systems. Hansen has supervised PhD students in areas like data integration and genetic circuit synthesis. He has contributed to international conferences and serves as a reviewer/examiner for academic programs. His work bridges theoretical foundations with industrial applications, particularly in embedded systems and data management. He has collaborated internationally, with projects addressing ESG reporting standards and regulatory compliance through automated data traceability.

Alvaro Torralbaمشاهده پروفایل

دانشیار

• Symbolic Search
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Alvaro Torralba is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, affiliated with the Technical Faculty of IT and Design. His research focuses on symbolic search, heuristic functions, and planning algorithms within artificial intelligence and machine learning. Notable projects include the ConAn initiative exploring contrastive analysis for state-space exploration. He has contributed extensively to classical planning, probabilistic planning, and automated planning competitions, earning awards such as the First Prize in the Agile Track of the 10th International Planning Competition (IPC’23). His work often bridges theoretical advancements with practical applications, including game-based network update synthesis and believable non-player character development. Research outputs include over 60 publications since 2011, with a focus on optimizing search algorithms and enhancing planning efficiency through techniques like operator-potential heuristics and bidirectional search strategies. His scientific contributions span algorithmic innovation, verification methodologies, and large-scale abstraction evaluation. Collaborations and datasets include foundational work on PDDL generators and pattern databases, with open-access resources available via Zenodo. As a program committee member and award-winning researcher, Torralba actively contributes to advancing the frontiers of AI planning and decision-making systems.

• Quantum Information Theory
• Quantum Optics
• Quantum Computing
• +۳ مورد دیگر

Dr. Daniel Malz is an Assistant Professor at the Department of Mathematical Sciences, University of Copenhagen. His research focuses on quantum many-body systems, quantum optics, and quantum computing, with affiliations to research groups QA, QMATH, and QfL. His work bridges theoretical physics and mathematical modeling, addressing topics like superradiance, entanglement dynamics, and quantum state preparation. Key research interests include quantum information theory, non-Markovian dynamics, and the development of efficient quantum simulation techniques. His recent publications explore advanced topics such as photonic cluster states, tensor network simulations, and cross-platform quantum network verification. Much of his work addresses foundational questions in quantum mechanics while maintaining practical relevance for quantum technologies. His contributions span both theoretical derivations and numerical methods, with a focus on bridging classical and quantum many-body dynamics.

• Artificial Intelligence
• Machine Learning
• Data Science
• +۴ مورد دیگر

Jens Ulrik Hansen is an Associate Professor at Roskilde University's Department of People and Technology. His work bridges artificial intelligence, data science, and social epistemology. He holds a PhD and MSc, and his research focuses on explainable AI, machine learning applications in healthcare, social network dynamics, and logical frameworks for multi-agent systems. Hansen participates in interdisciplinary projects like #echopol (studying social media polarization) and ROROGREEN (digital innovation in maritime shipping). He has published widely on topics including AI ethics, expert knowledge integration in ML systems, and opinion dynamics in social networks. Research Interests: Artificial Intelligence & Machine Learning Data Science & Big Data Analysis Explainable AI Social Network Analysis Formal Epistemology Key Projects: #echopol: Echo chambers and polarization dynamics ROROGREEN: Green RORO shipping innovations FeedbackBox: Collaborative workshop methodologies Awards: No specific prizes listed, though his work has received media attention for innovations in AI research and healthcare applications.

Daniel Gratzerمشاهده پروفایل

استادیار

• Programming Languages
• Type Theory
• Category Theory
• +۱۰ مورد دیگر

Daniel Gratzer is an assistant professor in the Department of Computer Science at Aarhus University, affiliated with the Logic and Semantics group. He studies programming languages and type theories through category theory, focusing on dependent, modal, and homotopy type theory. He co-teaches graduate courses on type theory and maintains a forthcoming textbook with Carlo Angiuli. Daniel is visiting Oxford from August 2024 to February 2025. His research explores applications of modal type theory to synthetic (∞,1)-category theory, guarded type theory for denotational semantics, and categorical methods in program logics like Iris. He collaborates with researchers including Carlo Angiuli, Lars Birkedal, and Jonathan Sterling. Recent work includes publications at LICS 2025, FoSSaCS 2025, and LMCS 2025. He contributed to the development of proof assistants like mitten and formal verification tools for higher-order concurrent separation logic. Contact: gratzer@cs.au.dk

• Theoretical Computer Science
• Mathematical Logic
• Structured Programming
• +۷ مورد دیگر

Siddharth Bhaskar is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark. His research lies at the intersection of theoretical computer science and mathematical logic, with a focus on programming language foundations and formal structures. His research interests include structured programming, imperative languages, graph traversal algorithms, and the application of category theory (particularly functors) to computation. These areas reflect a deep engagement with the mathematical underpinnings of programming and algorithmic processes. The two recent publications show a consistent trend in formalizing programming concepts through mathematical structures—particularly using universal constructions from category theory and extending structured programming into transfinite domains. This indicates a research trajectory grounded in computability, logic, and the semantics of programming languages. No scientific awards mentioned in the provided text. Siddharth Bhaskar has no listed advisees or grant information in the available data. However, his peer-reviewed publications in high-quality conference proceedings (CiE and MFCS) suggest active research supervision and potential involvement in collaborative projects, though specific details are not disclosed. There is no mention of specific laboratories, research groups, or teams in the provided text. However, his affiliation with the Department of Mathematics and Computer Science and his research profile suggest potential collaboration within formal methods or logic research circles at the University of Southern Denmark.