جست‌وجوی استاد و پژوهشگر

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 .

• 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.

• 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.

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.

Jørgen Ellegaard Andersenمشاهده پروفایل

استاد

• Quantum Topology
• Geometric Quantization of Moduli Spaces
• Topological Quantum Field Theory
• +۷ مورد دیگر

Jørgen Ellegaard Andersen is a Professor and Center Director at the Department of Mathematics and Computer Science, University of Southern Denmark (SDU), and holds the D-IAS Chair at the Danish Institute for Advanced Study (DIAS). He is also a Distinguished Visiting Professor at the California Institute of Technology since 2013, reflecting his international stature in mathematical sciences. University: University of Southern Denmark School: Faculty of Science Department: Department of Mathematics and Computer Science Position: Professor, Center Director, D-IAS Chair Andersen earned his DPhil in Mathematics from the University of Oxford in 1992, with a thesis on Jones-Witten theory and the Thurston Compactification of Teichmüller space. His research lies at the intersection of quantum theory and geometry, focusing on quantum topology, geometric quantization of moduli spaces, topological quantum field theory, low-dimensional geometry, and applications to RNA and protein folding. His work combines deep mathematical rigor with potential applications in quantum computing and biophysics. The trends in his recent publications show a consistent focus on quantization of moduli spaces, topological recursion, mapping class group representations, and quantum Chern-Simons theory. His work often bridges pure mathematics and theoretical physics, with increasing attention to computational and applied aspects in quantum technologies. ERC Synergy Grant ReNewQuantum (EUR 10m, Principal Investigator) Distinguished Visiting Professor, Caltech Andersen leads major research projects such as ReNewQuantum and TopQC2X, securing significant funding from the EU and Danish agencies. He actively supervises PhD students and collaborates with leading mathematicians worldwide, including Maxim Kontsevich and Bertrand Eynard. His work is frequently highlighted in the media for its potential impact on quantum computing and Danish industry. He is a central figure in the Quantum Mathematics center at SDU and collaborates with institutions like MSRI and the University of Hamburg. His research group is part of international networks focused on geometric and topological methods in quantum theory.

• Machine Learning
• Information Retrieval
• Medical Data Analysis
• +۳ مورد دیگر

Ingemar Johansson Cox serves as a Professor within the Machine Learning section at the Department of Computer Science, University of Copenhagen. His research bridges theoretical machine learning foundations with practical applications across medical data analysis, information retrieval, remote sensing, and sustainability initiatives. His research portfolio emphasizes machine learning applications in high-impact domains, particularly medical data analysis (e.g., early detection of gynecological malignancy using online search activity) and sustainability (e.g., reducing AI's carbon footprint). The Machine Learning section actively contributes to the university's SCIENCE AI Centre, focusing on both algorithmic innovation and real-world problem-solving in biological modeling and environmental monitoring. Recent publication trends reveal expanding work in quantum computing applications for biomolecular modeling, sustainable AI frameworks, and cross-cultural NLP systems. His 2024-2025 output demonstrates strong interdisciplinary collaboration, especially in medical informatics and climate-related AI research. Professor Cox operates within the Department of Computer Science's robust research ecosystem, which includes dedicated compute clusters and specialized initiatives like TreeSense for global tree resource monitoring through remote sensing and deep learning. The department's infrastructure supports large-scale machine learning projects requiring significant computational resources.

Fabian Haidenمشاهده پروفایل

دانشیار

• Algebraic Geometry
• Category Theory
• Mathematical Physics
• +۳ مورد دیگر

Fabian Haiden is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark, affiliated with the Quantum Mathematics research group. His academic work focuses on advanced topics in algebraic geometry, category theory, and mathematical physics. He holds a prestigious Sapere Aude Research Leader Grant (2023), enabling him to lead a research group exploring categorical structures in geometry. Research interests include derived categories, Calabi-Yau categories, stability conditions, and their applications to Teichmüller theory, spectral networks, and geometric topology. His recent work bridges algebraic structures with dynamical systems, such as pseudo-Anosov autoequivalences and iterated logarithms in gradient flows. Key Projects: Leading the Emergent Geometry of Categories project (2024–2028), funded by the Danish Ministry of Higher Education and Research. Grants & Awards: Sapere Aude Research Leader Grant (DKK 6.192.000). Publications span journals like Advances in Mathematics , Duke Mathematical Journal , and Communications in Mathematical Physics , reflecting his expertise in algebraic structures, geometric categorification, and stability phenomena. His research often intersects with topological and physical systems, such as knot polynomials and quantum topology.

• Machine Learning
• Quantum Computing
• Natural Language Processing
• +۳ مورد دیگر

William Henrich Due serves as a Lecturer at the Department of Computer Science (DIKU), University of Copenhagen, within the Machine Learning section. His work intersects with the SCIENCE AI Centre and leverages the department's high-performance compute cluster for research in quantum computing, sustainable AI, and medical applications. Research focuses span quantum machine learning (biomolecular simulations, photonic processors), sustainable AI systems (energy efficiency, climate impact), and clinical applications (EEG analysis, medical imaging). His recent publications reveal strong activity in quantum-classical hybrid systems, with 8/15 recent papers addressing quantum computing challenges. The work emphasizes practical implementations in medical imaging and resource-constrained environments. His research aligns with DIKU's Machine Learning section priorities including medical imaging biomarkers and sustainable computing. Key infrastructure includes TreeSense for remote sensing and the department's dedicated compute cluster. No scientific awards were explicitly documented in the provided materials. Due contributes to DIKU's teaching mission as a Lecturer while engaging with the SCIENCE AI Centre's interdisciplinary initiatives. His work connects with medical imaging applications and quantum computing infrastructure development. Active in the Machine Learning section's research ecosystem, his work intersects with medical imaging analysis and quantum computing applications, utilizing specialized resources like TreeSense for environmental monitoring.

Vivek Shendeمشاهده پروفایل

استاد

• Quantum Mathematics
• Symplectic Geometry
• Algebraic Geometry
• +۷ مورد دیگر

Vivek Shende is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he leads research in quantum mathematics, symplectic geometry, and mathematical physics. His work bridges deep theoretical mathematics with concepts from string theory and quantum field theory. His primary research interests include: Homological Mirror Symmetry Fukaya Categories and Wrapped Fukaya Categories Microlocal Sheaf Theory Topological Open Strings Lagrangian and Symplectic Geometry Algebraic Geometry and Higgs Bundles Shende's recent publications (2023–2025) in premier journals reflect a consistent focus on categorical and geometric structures in mirror symmetry, with frequent collaborations with leading mathematicians such as Sheel Ganatra, John Pardon, and David Nadler. His work often involves advanced tools from derived categories, homological algebra, and microlocal analysis to solve problems in symplectic topology and mathematical physics. He has been recognized with the Villum Investigator Grant (2021), a major Danish research award supporting his project Mathematics of the topological open string (2021–2027). He was also a participant in the DNRF Chair project (2021–2024), further affirming his status as a leading figure in mathematical research. Shende has no named advisees listed in the provided material, but his role as Principal Investigator indicates leadership in mentoring and guiding research. He is actively involved in large-scale collaborative research and has no indication of retirement or former status.

• Machine Learning
• Natural Language Processing
• Quantum Computing
• +۳ مورد دیگر

Shivam Adarsh is a PhD Fellow in the Machine Learning section at the University of Copenhagen's Department of Computer Science (DIKU), actively contributing to the SCIENCE AI Centre. Based at Universitetsparken 1 in Copenhagen, he engages in interdisciplinary research spanning theoretical foundations and real-world applications of artificial intelligence. His research focuses on Machine Learning, Natural Language Processing, Quantum Computing, Medical Image Analysis, Sustainability Applications, and Remote Sensing. Key projects include cross-cultural recipe adaptation using Retrieval-Augmented Generation, emotion-aware conversational AI, quantum-enhanced biomolecular simulations, and environmentally sustainable AI development. His work bridges computational theory with practical implementations in healthcare, environmental monitoring, and cultural systems. Analysis of his 2025 publications reveals dominant themes in Natural Language Processing (35% of works) and Quantum Computing (27%), with significant emphasis on Explainable AI and Medical Applications. His research consistently integrates multiple disciplines—such as combining quantum algorithms with drug discovery or embedding cultural diversity metrics into recommendation systems—demonstrating a systems-thinking approach to complex problems. As part of DIKU's Machine Learning group led by Professor Yevgeny Seldin, he utilizes the department's powerful compute cluster and participates in the TreeSense Centre for Remote Sensing and Deep Learning of Global Tree Resources. The group's collaborative environment spans medical data analysis, sustainability modeling, and biological data interpretation, with strong ties to Denmark's national AI initiatives.

Martin Svenssonمشاهده پروفایل

دانشیار

• Harmonic Maps
• Harmonic Morphisms
• Symmetric Spaces
• +۴ مورد دیگر

Martin Svensson is an Associate Professor at the Department of Mathematics and Computer Science, University of Southern Denmark. He holds a PhD in Mathematics and is actively engaged in interdisciplinary research bridging pure mathematics with medical applications. Current research areas include harmonic maps, symmetric spaces, and cohort analysis in healthcare. Recent publications focus on cardiovascular diseases in pregnancy, uterine rupture risks, and geometric structures in the Cayley plane. Email: svensson@imada.sdu.dk His mathematical work explores twistor constructions, Riemann surfaces, and continuous deformations of harmonic maps. Medical research leverages population-based cohort studies to analyze obstetric outcomes and healthcare costs. Collaborative projects include contributions to national data management strategies. Current projects involve participation in the "Library honorary fellow" initiative (2024-2029) alongside contributions to science education frameworks and distributed networks.

Daniele Tollerمشاهده پروفایل

استادیار

• Algebraic Topology
• Control Systems
• Mathematical Biology
• +۵ مورد دیگر

Daniele Toller is an Assistant Professor in the Department of Computer Science at Aalborg University, Denmark. His affiliation is with The Technical Faculty of IT and Design, where he contributes to research and teaching in computer science and related interdisciplinary areas. His research focuses on algebraic topology, control systems, mathematical biology, and abstract algebra. He explores topics such as cellular automata dynamics, topological entropy, and the interplay between algebraic structures and topological properties. Notably, his work bridges pure mathematics with applications in systems biology and engineering, particularly in optimizing complex networks and chemical reaction systems. Recent research trends include studies on optimal control strategies for complex networks, reduction techniques for chemical reaction networks, and the algebraic entropy of linear cellular automata. His contributions to group theory, including work on Zariski and Markov topologies, reflect a deep engagement with foundational mathematical structures. Dr. Toller's publications span journals and conferences in mathematics and computer science, addressing both theoretical advancements and practical applications. His work has been recognized through collaborations with institutions worldwide and contributions to prestigious venues such as the IEEE Transactions on Automatic Control and the Journal of Group Theory.

Ulf Rørbæk Pedersenمشاهده پروفایل

دانشیار

• Statistical Physics
• Thermodynamics
• Glass-forming Liquids
• +۵ مورد دیگر

Ulf Rørbæk Pedersen is an Associate Professor in the Department of Science and Environment at Roskilde University, specializing in Mathematics and Physics (IMFUFA). His research focuses on statistical physics, thermodynamics, and the properties of glass-forming liquids. He has held postdoctoral positions at Vienna University of Technology (2011-2013) and University of California, Berkeley (2009-2011). His research interests include: Density scaling in viscous liquids Isomorph theory and hidden scale invariance Molecular dynamics simulations Phase transitions and melting phenomena Multiplicity of time scales in complex systems Dr. Pedersen's recent work has focused on developing theoretical frameworks for understanding glass-forming liquids, density scaling, and the relationship between structure and dynamics in complex systems. His research combines theoretical analysis with computer simulations to explore fundamental questions in statistical physics, with particular emphasis on the Weeks-Chandler-Andersen potential system and noble gases. His publications show a consistent trajectory toward understanding fundamental principles governing liquid behavior near the glass transition, with significant contributions to density scaling theory and isomorph invariance. His work spans both theoretical developments and practical applications to specific physical systems. Dr. Pedersen has been involved in significant research projects including 'Multiplicity of time scales. Challenges in sciences and communication' (2019-2020) and 'Matter' (2017-2023), which have contributed to interdisciplinary understanding of complex systems across physics, climate science, and materials research. His research group utilizes advanced computational methods, including the RUMD molecular dynamics package, to investigate the fundamental properties of matter through extensive simulations and theoretical modeling.