جست‌وجوی استاد و پژوهشگر

• Bioinformatics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Ole Winther is Professor in High dimensional biological data analysis/Machine learning at the Department of Biology, University of Copenhagen and Professor in Data science and complexity at DTU Compute, Technical University of Denmark. He serves as CRO and co-founder of raffle.ai, CTO and co-founder of FindZebra, Head of ELLIS Unit Copenhagen, and co-PI of the Machine Learning for Life Science Center. His research spans Bioinformatics , Machine Learning , and AI for Science , focusing on applying deep learning to biological sequence analysis, latent variable models, and medical NLP. Winther's work develops predictive and generative models for bioinformatics, with significant contributions to protein localization tools (SignalP, DeepLoc, DeepTMHMM), single-cell genomics, and novel deep learning architectures like variational autoencoders and diffusion models. Analysis of Winther's recent publications (2023-2025) reveals a strong trend toward integrating protein language models with traditional bioinformatics approaches and applying diffusion models to scientific problems. His work bridges theoretical machine learning advancements with practical applications in biology and medicine, particularly in protein sequence analysis, medical search engines, and scientific simulation acceleration. Winther currently supervises a diverse research group including Panagiotis Antoniadis, Rachael M. DeVries, Jun Wang, Beatrix M. G. Nielsen, Felix G. Teufel, Irene R. Rodriguez, Anders Christensen, and Christopher Heje Grønbech. His former students have established successful careers at institutions including Google, Apple, and various startups, with notable alumni like Casper Sønderby (Google Brain) and Søren Sønderby (Apple). He leads significant research initiatives including the ELLIS Unit Copenhagen and the Machine Learning for Life Science Center, while maintaining active industry partnerships through his co-founded companies raffle.ai (enterprise search using NLP) and FindZebra (search engine for rare diseases). His teaching includes Deep Learning courses at both DTU (02456) and University of Copenhagen (NDAK24002U).

Maxim Kontsevichمشاهده پروفایل

استاد

• Mathematical Physics
• Algebraic Geometry
• Deformation Quantization
• +۵ مورد دیگر

Maxim Kontsevich is a permanent professor at the Institut des Hautes Études Scientifiques (IHÉS), holding the AXA Chair for Mathematics since 1995 and a visiting chair at Rutgers University (one month annually since 1997). Born in 1964 in Khimki, USSR, he earned his PhD from Bonn University in 1992. His career includes visiting positions at Harvard, the Institute for Advanced Study, and Berkeley, where he was a professor from 1993 to 1995. His research spans mathematical physics, algebraic geometry, and non-commutative geometry. Notable contributions include deformation quantization, mirror symmetry, and motivic integration. His work bridges algebraic structures with geometric and physical concepts, influencing areas like topological field theories, string theory, and integrable systems. Awardees of Fields Medal (1998), Crafoord Prize (2008), and Breakthrough Prize (2014), he also holds editorial roles at Compositio Mathematica and Publications Mathématiques IHÉS. His over 50 publications explore advanced topics such as quantum cohomology, Hodge theory, and categorical structures in geometry.

Sebastian Risiمشاهده پروفایل

استاد

• Neuroevolution
• Evolutionary Robotics
• Self-Organizing AI
• +۹ مورد دیگر

Sebastian Risi is a Professor at the IT University of Copenhagen , where he directs the Creative AI Lab and co-directs the Robotics, Evolution and Art Lab (REAL) . His work bridges computational evolution, deep learning, and collective intelligence for applications in robotics, art, and video game design. His research focuses on self-organizing AI systems that grow or assemble through local interactions, inspired by biological development. Key areas include neuroevolution , neural cellular automata , and generative modeling , with applications in adaptive robotics, game content creation, and damage-resilient AI. Recent publications highlight trends in self-assembling neural architectures (NDPs) and 3D functional machine generation (Minecraft experiments). Awards include ERC Consolidator Grant (2022), Best Paper at FDG’21 , and Google Faculty Award (2019). Scientific Awards : ERC Consolidator Grant (GROW-AI), Best Paper FDG’21, Runner-Up IEEE Games’20, GECCO 2017 Competition Winner, Sapere Aude Grant, Amazon/Google Faculty Awards He advises on projects like GROW-AI (EU-funded), AI-TESTER (game testing), and C2SIM (military systems). Media coverage includes Science , Wired , and Popular Science .

• Algorithms
• Algorithmics
• Big Data
• +۷ مورد دیگر

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.

• Algebra
• Category Theory
• Commutative Algebra
• +۳ مورد دیگر

Henrik Granau Holm is a Professor in the Department of Mathematical Sciences at the University of Copenhagen. His research focuses on advanced algebraic structures within category theory and commutative algebra, with significant contributions to derived categories and quiver representations. His primary research areas include Algebra, Category Theory, Commutative Algebra, Derived Categories, Quiver Representations, and Homological Algebra. His work explores the structural properties of derived categories, particularly Q-shaped derived categories, and their applications in representation theory. Recent research investigates compact and perfect objects in ring-derived categories, tensor embeddings in Grothendieck cosmos, and vanishing properties of Tor functors. Holm's publication record shows consistent output in top mathematics journals, with multiple 2024 publications including a book on derived category methods in commutative algebra. His research demonstrates strong international collaboration, particularly with researchers in representation theory and category theory. Holm has supervised PhD students and postdoctoral researchers as indicated by departmental records. His activities include editorial work for Mathematical Reviews and Zentralblatt MATH, along with numerous lecture presentations on cohomology and AC rings dating back to 2007.

Nathalie Wahlمشاهده پروفایل

استاد

• Algebraic Topology
• Mapping Class Groups
• Topological Field Theory
• +۷ مورد دیگر

Nathalie Wahl is a Professor at the Department of Mathematical Sciences, University of Copenhagen, and serves as the Center Director for the Copenhagen Centre for Geometry and Topology (GeoTop). Her research focuses on algebraic topology, particularly mapping class groups of surfaces and 3-manifolds, homological stability, topological field theory, and loop spaces. PhD from Oxford University (2001) Current leadership of GeoTop (since 2020) Her recent work explores homological stability across automorphism groups, string topology, and structured algebras. Key collaborations include Allen Hatcher, Craig Westerland, and Nancy Hingston. She has received prestigious awards such as the ERC Consolidator Grant and the Young Elite Researcher Award. ERC Consolidator Grant (2018-2023) Female Research Leader Scholarship (2009-2013) Marie Curie European Fellowship (2003-2004)

• Technology
• Digital Design
• Algorithmic Design
• +۴ مورد دیگر

Niels Martin Larsen is an Associate Professor at the Aarhus School of Architecture, affiliated with Research Laboratory 2: Technology, Building Cultures and Settlement. He holds a PhD in algorithmic design and has been part of academic staff since 2009. His roles include teaching and research in technology-driven architectural design. Education and Career: PhD student at Aarhus School of Architecture (2009–present) Master's and Bachelor's teaching assistant (2002–2008) Worked at architectural firms including Stuff Aps and 3XNielsen A/S (1999–2008) Graduated from Aarhus School of Architecture (1992–1998) with an internship at Enrique Miralles in Barcelona (1996) Research Interests: Focus on technology and digital design , including algorithmic design, architectural geometry, and sustainable materials. Recent work explores building reuse, digital fabrication, and timber structures. His projects bridge computational methods with practical architectural applications. Awards: 2012: Best Paper Award at Advances In Architectural Geometry for 'Engineering of complex geometry' Grants and Projects: Key roles in projects like 'Recycling on the Land Register' (2023–2025) and 'Material Imagination: Reconnecting with the Matter of Architecture' (2017–2021). Collaborates on Nordic networks for digital fabrication and timber innovation. Labs/Teams: Active in Research Laboratory 2, focusing on technology-driven solutions for building cultures and habitation.

• Algebraic Topology
• Moduli Spaces
• Homology Spheres
• +۵ مورد دیگر

Søren Galatius is a Visiting Professor at the Department of Mathematical Sciences, University of Copenhagen. His research focuses on algebraic topology with an emphasis on moduli spaces, homology spheres, K-theory, and cobordism categories. He holds a PhD and has established himself as a leading figure in geometric topology and algebraic structures in mathematics. Recent research has explored topics such as general linear groups over finite fields, Pontryagin classes, and tropical geometry applications to moduli spaces. His work bridges pure algebraic topology with geometric and combinatorial methods, contributing foundational insights into modern mathematical frameworks. Key collaborations include projects with Oscar Randal-Williams and Martin Hairer, advancing understanding of cobordism categories and topological field theories. His articles consistently appear in top-tier journals like Annales Scientifiques de l'Ecole Normale Superieure and Inventiones Mathematicae . No scientific awards or grants are explicitly listed in the provided materials, though his publication record speaks to significant academic contributions. No advisee students are documented here.

Lars Hesselholtمشاهده پروفایل

استاد

• Algebraic Topology
• K-Theory
• Homological Algebra
• +۳ مورد دیگر

Lars Hesselholt is a Professor at the Department of Mathematical Sciences, University of Copenhagen, and a key member of the Copenhagen Centre for Geometry and Topology (GeoTop). His research focuses on the intersection of algebraic topology, K-theory, and arithmetic geometry, with significant contributions to topological Hochschild homology and its applications to number theory and algebraic geometry. His recent work includes advancements in Dirac geometry, connections between topological cyclic homology and the Fargues–Fontaine curve, and studies on the K-theory of division algebras over local fields. These publications highlight his role in bridging homotopy theory with arithmetic structures. Hesselholt maintains an active research profile, with 36 research outputs documented, including collaborations with mathematicians like Thomas Nikolaus, Morten Larsen, and Ayelet Lindenstrauss. His work spans topological methods in algebraic geometry, cyclic homology, and noncommutative geometry. For correspondence, he can be reached at larsh@math.nagoya-u.ac.jp or via phone at +4551319971. His office is located at Universitetsparken 5, 2100 København Ø, Denmark.

Francesco Sanninoمشاهده پروفایل

استاد

• Quantum Field Theory
• Elementary Particle Physics
• Particle Physics
• +۵ مورد دیگر

Francesco Sannino is a Professor of Computational Science at the University of Southern Denmark's Department of Mathematics and Computer Science. He is affiliated with the Danish Institute for Advanced Study (DIAS) and holds a Ph.D. His research spans quantum field theory, particle physics, and complex systems modeling. Key interests include Standard Model duality, black hole physics, and epidemiological dynamics. Education: Ph.D. in Physics (not explicitly stated in provided text, inferred from title). Research focuses on theoretical physics, including conformal field theories, gauge dynamics, and applications of quantum chromodynamics (QCD). Recent work addresses black hole metrics, pandemic modeling via renormalization group methods, and composite dark matter signatures. His studies often bridge high-energy physics and complex systems. Main Research Trends: Over 15 years, Sannino has produced 333+ publications, emphasizing: Black hole physics and effective metrics Standard Model extensions and dualities Quantum field theory at conformal windows Epidemiological modeling of pandemics Awards: Elected Member of the Finnish Academy of Science and Letters (2015) EU Excellence Grant in Theoretical Physics (2005) International Referee for Austrian Science Fund Grants & Projects: Leader of the DG Center for Particle Physics Phenomenology (2014–2019) Carlsberg Foundation Semper Ardens grant (2023–2029) Coordinator for Danish CERN Instrument Center (2017–2019) Labs/Teams: Active in CP³ - Center for Particle Physics Phenomenology and DIAS, collaborating globally on projects like gravitational wave detection and pandemic modeling.

• Operator Algebra
• C*-algebras
• K-theory
• +۳ مورد دیگر

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.

• Machine Learning
• Artificial Intelligence
• Quantum Computing
• +۵ مورد دیگر

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.

Kasper Green Larsenمشاهده پروفایل

استاد

• Machine Learning
• Theoretical Computer Science
• Algorithms and Data Structures
• +۳ مورد دیگر

Kasper Green Larsen is a Professor in the Department of Computer Science at Aarhus University. His research focuses on theoretical computer science, machine learning, algorithms, and data structures. He has made significant contributions to boosting algorithms, PAC learning theory, and computational geometry. His work often bridges algorithm design with complexity theory, addressing challenges in optimization, memory efficiency, and lower bounds analysis. Key research areas include: Algorithmic Learning Theory (e.g., boosting, bagging, and PAC learners) Data Structure Design (e.g., invertible Bloom tables, succinct representations) Computational Complexity (e.g., lower bounds for dynamic and oblivious algorithms) Geometric Algorithms (e.g., hierarchical searching, range queries) Recent publications emphasize foundational advancements in learning theory (e.g., optimal weak-to-strong learning) and data efficiency (e.g., memory-reduced Bloom filters). His work frequently appears in top conferences like IJCAI, ICALP, and SODA, reflecting rigorous theoretical contributions with practical implications.

Andreas Kugiمشاهده پروفایل

استاد

• Control Theory
• Automatic Control
• Complex Dynamical Systems
• +۶ مورد دیگر

Andreas Kugi is the Scientific Director at the AIT Austrian Institute of Technology and a full professor of Complex Dynamical Systems at TU Wien (Vienna University of Technology) in the Faculty of Electrical Engineering and Information Technology, Institute of Automation and Control. He has held significant academic and leadership roles across Europe, including professorships at Saarland University and offers from TU Dresden and KIT. His research focuses on the modeling, control, and optimization of complex dynamical systems , with strong applications in mechatronics, robotics, and industrial automation . He has led major research centers such as the Christian Doppler Laboratory for Model-Based Process Control in the Steel Industry and the Center for Vision, Automation & Control at AIT. His work bridges theoretical control design and real-world industrial implementation. The recent publications reflect a consistent focus on nonlinear, hybrid, and distributed parameter systems , with applications in robotics, manufacturing, energy, and process industries. His research integrates advanced control theory with practical engineering challenges, emphasizing real-time optimization, robustness, and system efficiency. Scientific Awards: Mechatronic Systems Outstanding Investigator Award (IFAC, 2022) Goldene Stefan-Ehrenmedaille (OVE, 2023) 16 best paper awards Andreas Kugi has supervised over 50 completed PhD dissertations and has been deeply involved in research leadership, including serving as Editor-in-Chief of Control Engineering Practice (2010–2017) and Vice President of the OVE Austrian Electrotechnical Association (2017–2023). He has secured and led numerous research grants, particularly through industrial collaborations in automation and process control. He leads and contributes to major research initiatives, including the Center for Vision, Automation & Control at AIT and the Christian Doppler Laboratory , fostering interdisciplinary teams focused on industrial digitalization and smart systems.

Sergey Arkhipovمشاهده پروفایل

دانشیار

• Geometric representation theory
• DG categories
• Homological algebra
• +۸ مورد دیگر

Sergey Arkhipov is an Associate Professor in the Department of Mathematics at Aarhus University. His primary research focuses on homotopy theory of DG-categories, homotopy descent, categorical braid group actions, matrix factorizations, derived algebraic geometry, chiral algebras, and semiinfinite cohomology. He has taught undergraduate and Master's courses such as Complex Analysis and Advanced Algebra, organized graduate seminars on DG Categories and Homotopical Algebra, and supervised PhD students. Research Interests Geometric representation theory DG categories Homological algebra Algebraic homotopy theory Algebraic operads Homotopy descent Categorical braid group actions Matrix factorizations Derived algebraic geometry Chiral algebras Semiinfinite cohomology Publications Trends Arkhipov's publications center on advanced topics in category theory, homotopy theory, and geometric representation theory, with a strong emphasis on DG-categories, matrix factorizations, and categorical structures in algebraic geometry. His work often bridges abstract categorical frameworks with concrete applications in algebra and topology.