جستجوی استاد راهنمای دانشگاهی

Kohei Nakajimaمشاهده پروفایل

دانشیار

• Soft Robotics
• Physical Reservoir Computing
• Physical Deep Learning
• +۵ مورد دیگر

Kohei Nakajima is an Associate Professor at the Department of Intelligent Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo. He holds concurrent positions at the Department of Creative Informatics and the Next Generation Artificial Intelligence Research Center (AI Center). As an Endowed Chair in Advanced Artificial Intelligence Education, he leads the Physical Intelligence Lab, which focuses on the intersection of soft robotics, nonlinear dynamics, and physical computing. His research interests center on Physical Reservoir Computing (PRC), a paradigm that exploits the natural dynamics of physical systems for computation, with applications in soft robotics, spintronics, and quantum machine learning. Nakajima's work demonstrates how physical systems can inherently process information without traditional digital computation, leveraging phenomena like chaos, bifurcations, and embodied intelligence. Nakajima's publications reveal a strong focus on understanding how physical systems can perform computational tasks. His recent work spans from biological applications (jellyfish cyborgs, ostrich-inspired robotics) to fundamental theoretical advances in reservoir computing. The research demonstrates how physical phenomena can be harnessed for information processing, with implications for energy-efficient computing and novel robotic control paradigms. As the organizer of the Reservoir Computing Seminar, Nakajima has built a vibrant research community exploring the nature of information processing across disciplines. His lab actively recruits graduate students and postdocs, indicating strong research momentum and institutional support for his work in physical intelligence.

Rob Gleasureمشاهده پروفایل

استاد

• Information Systems
• Digitalization
• Blockchain Technology
• +۷ مورد دیگر

Rob Gleasure is a Professor in the Department of Digitalization at Copenhagen Business School (CBS), Denmark. His research focuses on the intersection of information systems, digital technologies, and human behavior, with particular expertise in blockchain technology, crowdfunding, AI applications, and technology adaptation. Based at Solbjerg Square 3 in Frederiksberg, he contributes to CBS's mission of advancing knowledge in business and society through digital transformation. Professor Gleasure's research spans several key areas within information systems and digital innovation: Digital finance and blockchain technologies, including cryptocurrency and financial applications Crowdfunding platforms and digital fundraising mechanisms Artificial intelligence applications in various domains including healthcare and banking Human-computer interaction and the psychological aspects of technology adoption Digital collaboration and the affective dimensions of online work Quantum computing infrastructure and emerging technologies His recent publications reveal an evolving research trajectory that increasingly addresses the societal implications of digital technologies. Gleasure has moved from foundational work on crowdfunding and blockchain to more complex examinations of AI ethics, gender bias in technological systems, and the psychological impacts of digital media. His research demonstrates growing attention to sustainable development goals, particularly those related to responsible consumption and production, reduced inequalities, and climate action. The interdisciplinary nature of his work bridges business, technology, and social sciences, often employing both qualitative and experimental methodologies. Professor Gleasure has served as a supervisor for numerous students (21 supervisor tasks mentioned) and has been active in academic service including co-chairing the ACM Collective Intelligence Conference in 2021. His research has attracted media attention, with contributions to discussions on cryptocurrency, carbon offsetting in aviation, and AI applications.

Nicola Dragoniمشاهده پروفایل

استاد

• Cybersecurity
• Internet of Things (IoT)
• Machine Learning
• +۷ مورد دیگر

Nicola Dragoni is a Professor in Cybersecurity Engineering at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). As Deputy Director and Head of Section, he leads research initiatives focused on securing emerging technologies. Key Research Areas : Internet of Things (IoT) security, machine learning for intrusion detection, cyber-deception techniques, fog computing, malware analysis, blockchain applications, and wireless sensor network security. Supervision : Actively supervising multiple PhD students in projects related to cyber-deception, moving target defense, and bio-inspired security mechanisms. Recent Publications : Contributions to IoT honeypots, drone identification via RF signals, passkey adoption challenges, and cyber range taxonomies.

Charles Marcusمشاهده پروفایل

استاد

• Condensed Matter Physics
• Quantum Computing
• Quantum Coherent Electronics
• +۴ مورد دیگر

Charles Marcus is a Professor at the University of Copenhagen's Niels Bohr Institute, holding the Villum Kann Rasmussen Chair in Quantum Sciences. He directs the Center for Quantum Devices and Microsoft Station Q – Copenhagen, while affiliating with the Niels Bohr International Academy. Education : Stanford University (B.S. 1984), Harvard University (Ph.D. 1990), IBM Postdoctoral Fellow (1990-92) Employment : Faculty at Stanford (1992-2000), Harvard (2000-2011), and UCPH (2012-present) His research focuses on experimental condensed matter physics, particularly quantum coherent electronics in semiconductors/superconductors. Key areas include spin qubits for quantum computing, Majorana modes in nanowires, quantum Hall systems, and superconductor-semiconductor hybrids. Recent work explores topological quantum information schemes and novel magnetic resonance imaging approaches. Scientific publications span quantum devices, Josephson junctions, and topological materials. Awards include the H.C. Ørsted Gold Medal, AAAS Newcomb-Cleveland Prize, and fellowships from AAAS and APS. He serves on advisory boards for quantum technology centers globally. Significant Awards : H.C. Ørsted Gold Medal (2020) Industry Prize, Danish Academy of Natural Sciences (2019) Member, National Academy of Sciences (2018) Award for Research Excellence in Nanotechnology (2014) Professional Roles : Director, Center for Quantum Devices (2012-2019) Lab Director, Microsoft Quantum (2016-2021) Scientific Director, Harvard Center for Nanoscale Systems (2004-2009)

Konstantin Wernliمشاهده پروفایل

استادیار

• Quantum Field Theory
• Mathematical Physics
• Geometric Quantization
• +۳ مورد دیگر

Konstantin Wernli is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark, affiliated with the Quantum Mathematics research group. His research focuses on quantum field theory, geometric quantization, and mathematical physics, with a particular emphasis on topological field theories and perturbative methods. He has contributed to foundational work in Chern-Simons theories, BV-BFV formalisms, and geometric analysis. His research interests include quantum field theories, algebraic geometry, and the intersection of topology with physics. Notably, he explores combinatorial approaches to quantum field theory, geometric quantization frameworks, and the application of advanced mathematical tools to solve problems in theoretical physics. Recent work includes studies on partition functions, constrained dynamical systems, and the globalization of sigma models. His articles often bridge abstract mathematics with physical applications, such as analyzing heat kernels, theta invariants, and entanglement polytopes. Wernli is a project participant in the Sapere Aude grant 'FROM PERTURBATIVE TO NON-PERTURBATIVE QUANTUM FIELD THEORY BY CUTTING AND GLUING' (2024–2028), which aims to advance non-perturbative QFT techniques. He has advised on research projects involving heat kernel analysis and geometric quantization, though no formal student advisees are listed.

Andrea Crovettoمشاهده پروفایل

دانشیار

• Photovoltaics
• Solar Energy Conversion
• Thin Film Technology
• +۳ مورد دیگر

Andrea Crovetto is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the National Centre for Nano Fabrication and Characterization and the Department of Nanofabrication. His research focuses on advanced materials for photovoltaic applications, including solar cell technologies, thin films, and semiconductor materials. His work contributes to UN Sustainable Development Goals related to affordable and clean energy. Key research interests include photovoltaic materials discovery, tandem solar cell design, and semiconductor characterization. Notable achievements include developing monolithic selenium/silicon tandem solar cells and pioneering studies on phosphosulfide semiconductors. He has authored over 90 publications and datasets, including high-impact articles in journals like JPhys Energy and PRX Energy . Dr. Crovetto has received the Young Scientist Award (2016) and actively supervises PhD students in projects such as Experimental Discovery of Phosphosulfide Materials for Solar Cells and Thiophosphate Thin Films for Quantum Technology . His research also involves collaborations on material synthesis, computational modeling, and device fabrication. He has presented at international conferences, including talks on monolithic tandem solar cells and materials discovery methodologies. His lab, based at DTU’s Produktionstorvet , integrates experimental and theoretical approaches to advance sustainable energy technologies.

• Microgrid Control Systems
• Renewable Energy Integration
• Smart Grids
• +۳ مورد دیگر

Juan C. Vasquez is a Professor at Aalborg University's Faculty of Engineering and Science, Department of Energy Technology, and Co-Director of the Center for Research on Microgrids (CROM). He holds a PhD in Automatic Control from the Technical University of Catalonia and has held academic positions at Aalborg University since 2011. His research focuses on microgrid control, renewable energy integration, power electronics, and smart grids. He has supervised numerous PhD and master’s students and leads projects funded by EU and national grants. Education: BS in Electronics Engineering (Autonomous University of Manizales, Colombia, 2004); PhD in Automatic Control (Technical University of Catalonia, Spain, 2009). Research interests include operation and control strategies for AC/DC microgrids, maritime microgrids, energy management systems, and IoT integration in smart grids. He has authored 648+ publications, including highly cited works, and received awards like the Young Investigator Award (2019) and Clarivate’s Highly Cited Researcher status since 2017. Key projects: EU-DREAM (Digital Services for Energy Transition), NEST (National Research Infrastructure), and ActRes (Resilience in Energy Systems). Collaborations include Virginia Tech and Ritsumeikan University.

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.

Sadegh Talebiمشاهده پروفایل

استادیار

• Reinforcement Learning
• Markov Decision Processes
• Online Learning
• +۲ مورد دیگر

Sadegh Talebi is a Tenure Track Assistant Professor in the Machine Learning Section at the Department of Computer Science, University of Copenhagen . His research focuses on theoretical aspects of reinforcement learning, Markov decision processes, online learning, stochastic multi-armed bandit problems, and resource allocation in networks. Education BSc in Electrical Engineering (minor: Electronics) from Iran University of Science and Technology (IUST) (2004) MSc in Electrical Engineering (minor: Communication Systems) from Sharif University of Technology (2006) PhD in Electrical Engineering from the Department of Automatic Control at KTH Royal Institute of Technology (supervised by Alexandre Proutiere and Mikael Johansson) Research Specializes in theoretical foundations of reinforcement learning and online learning Key contributions in stochastic optimization, MDPs, and bandit algorithms Collaborates on applications in resource allocation and quantum computing Publications include high-impact work on offline RL, differentially private exploration, and scalable MDP solutions in journals like Neural Processing Letters and conferences such as NeurIPS and UAI.

• Machine Learning
• Quantum Computing
• Medical Data Analysis
• +۷ مورد دیگر

Luka Radic is a Researcher in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His work bridges theoretical and applied research in machine learning, with a focus on quantum machine learning , large language models , and fairness in AI systems.

Shashi Raj Pandeyمشاهده پروفایل

استادیار

• Network Economics
• Game Theory
• Wireless Networks
• +۷ مورد دیگر

Shashi Raj Pandey serves as Assistant Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design, Denmark. His research is anchored in the Connectivity section and Connectivity Classique-Center for Classical Communication in the Quantum Era, with office location at Fredrik Bajers Vej 7C, C1-111, 9220 Aalborg Øst. His core research spans Network Economics, Game Theory, and Wireless Networks, with specialization in Decentralized Machine Learning and Semantic/Goal-oriented Communications. Current work integrates Digital Twin technologies with 6G systems for industrial automation and earth observation, emphasizing resource-efficient protocols for Internet of Things and edge intelligence applications. Recent publications (2024-2025) reveal a clear trajectory toward AI-6G convergence, featuring semantic communications for satellite imaging, game-theoretic network resource allocation, and digital twin implementations for autonomous systems. Key themes include communication efficiency in distributed learning and physical-digital world integration. Notable recognitions include: Best PhD Thesis Nominee (2021) Excellent Paper at Korea Software Congress, KIISE 2021 Student Best Paper Award at APNOMS 2019 Best Paper at Korea Software Congress, KIISE, 2018 Brain Korea 21st Century Plus Fellowship Academic service includes external PhD examination for EU SNS projects and peer review for premier conferences (AAAI, ICLR, ICML). His lab work within the Connectivity Classique-Center explores classical communication frameworks applicable to quantum-era networks, with focus on semantic information theory and decentralized network architectures.

Shachar Carmeliمشاهده پروفایل

پژوهشگر

• Homotopy Theory
• Algebraic Geometry
• Representation Theory
• +۳ مورد دیگر

Shachar Carmeli is a researcher in the Department of Mathematics at the Weizmann Institute of Science. He previously held a postdoctoral position at the University of Copenhagen's Department of Mathematical Sciences, working with the Copenhagen Centre for Geometry and Topology. Carmeli earned his PhD from the Weizmann Institute under the supervision of Professor Dmitry Gourevitch, focusing on advanced topics in algebraic topology and representation theory. His research interests span homotopy theory, chromatic homotopy theory, algebraic geometry, and representation theory, with a current emphasis on higher semiadditivity in chromatic homotopy theory and its connections to algebraic K-theory. He also explores Nash stacks and geometric representation-theoretic frameworks. Notable collaborations include work with Tomer M. Schlank, Lior Yanovski, and Allen Yuan on cyclotomic extensions, redshift phenomena, and categorified trace constructions. Carmeli's recent publications highlight contributions to topics like chromatic Fourier transforms, descent in algebraic K-theory, and the topology of crystalline materials. His work bridges abstract algebraic structures with geometric and topological applications, often leveraging tools from higher category theory and spectral algebraic geometry.

• Quantum Mathematics
• Mathematical Physics
• Theoretical Computer Science
• +۲ مورد دیگر

Nadia Ott is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark, specializing in Quantum Mathematics. She is actively contributing to research at the intersection of mathematics and quantum theory within the Faculty of Science. Her research interests lie primarily in Quantum Mathematics , with strong emphasis on Mathematical Physics , Algebraic Geometry , and Topological Quantum Field Theory . Her work explores the deep mathematical structures underlying quantum systems, drawing from advanced topics in pure mathematics and theoretical physics. The available information does not include recent publications; therefore, no article trends can be identified at this time. Nadia Ott has not been mentioned as receiving any scientific awards or honors in the provided text. There is no information available regarding graduate student supervision, research grants, or advising activities. Similarly, no details about specific laboratories, research teams, or collaborative groups have been provided in the source material.

Christian Pascal Hirschمشاهده پروفایل

دانشیار

• Topological data analysis
• Large deviations theory
• Spatial random networks
• +۳ مورد دیگر

Christian Pascal Hirsch is an Associate Professor for Data Science and Statistics at the Department of Mathematics, Aarhus University. His research focuses on random networks inspired by biology and health sciences, utilizing techniques from topological data analysis and stochastic geometry. He is affiliated with the Stochastics group, AU DIGIT Centre, and AU Quantum Campus. Research Interests: Topological data analysis, large deviations theory, spatial random networks, and stochastic geometry. His work includes studies on percolation theory, Gibbs measures, and applications to neural networks and geometric functionals. Publications span journals such as the Journal of Applied and Computational Topology, Journal of Statistical Physics, and Stochastic Processes and Their Applications, covering topics from network topology to Poisson approximation.

Tuukka Ruotsaloمشاهده پروفایل

دانشیار

• Brain-Computer Interfaces
• Human-Information Interaction
• Recommender Systems
• +۴ مورد دیگر

Tuukka Ruotsalo serves as Associate Professor in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His research bridges human cognition with computational systems through brain-computer interfaces and physiological computing. As Academy Research Fellow at University of Helsinki (2019-2024), he maintained dual institutional affiliations while leading cutting-edge work in neuro-linguistic modeling and affective relevance. His research focuses on brain-computer interfaces for information retrieval , where he pioneers methods to decode cognitive states from neural signals to improve search systems. Key areas include affective relevance modeling that integrates emotional states into search algorithms, and neuro-linguistic reconstruction that translates brain activity into language. His work on fairness-relevance tradeoffs in recommender systems established Pareto frontier evaluation frameworks now widely adopted in ethical AI research. Recent publications demonstrate how physiological signals like EEG and galvanic skin response can create more adaptive human-information interaction systems. Ruotsalo's scientific recognition includes the prestigious Academy Research Fellow position. His publications in IEEE Transactions on Human-Machine Systems , Journal of the Association for Information Science and Technology , and Communications Biology reveal growing interdisciplinary impact. His advising spans cognitive neuroscience and machine learning students, with notable collaborations across the SCIENCE AI Centre. Current projects include the TreeSense initiative for remote sensing of global tree resources and development of quantum-inspired neural architectures. His lab leverages the department's powerful compute cluster for large-scale physiological data analysis.