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.

Niels Aageمشاهده پروفایل

دانشیار

• Topology Optimization
• Acoustics and Vibroacoustics
• Biomechanics
• +۵ مورد دیگر

Niels Aage is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on topology optimization, biomechanics, and multiphysics modeling, with applications in acoustic devices, biomedical implants, and microelectromechanical systems (MEMS). He holds roles such as Vice President of the International Society for Structural and Multidisciplinary Optimization (2023–2027). Education and Professional Background: Conducted a 5-month research visit at the University of Colorado, Boulder (USA) in 2010. Specializes in giga-scale numerical modeling, finite element methods, and topology optimization algorithms. Research Interests: Develops novel methods for topology optimization of fluidic, thermal, and acoustic systems. Explores applications in patient-specific spinal implants, metamaterials with vibroacoustic bandgaps, and nonlinear dynamic substructuring. His work integrates machine learning and reduced-order modeling for efficient simulation. Publications: Over 100 peer-reviewed articles, including recent contributions on connectivity promotion in topology optimization (2025), vibroacoustic metamaterial design (2025), and anatomically conforming spinal fusion cages (2024). Research emphasizes high-resolution modeling and bridging computational design with additive manufacturing. Scientific Awards: ISSMO Haftka Young Investigator Award (2021), Equinor Prize 2020, and Hyperion Innovation Excellence Award (2017). Recognized for contributions to structural optimization and computational mechanics. Advising and Grants: Supervises multiple PhD projects, including work on vibroacoustic shape optimization, quantum-opto-mechanical systems, and smart hearing aid modeling. Engages in collaborative projects funded by industry and academia. Labs/Teams: Collaborates with DTU’s Solid Mechanics group and industry partners on projects involving topology optimization, multiphysics simulation, and biomedical engineering. Active in international conferences and serves on editorial boards.

Dao Zhouمشاهده پروفایل

دانشیار

• Power Electronics
• Renewable Energy Systems
• Wind Turbine Reliability
• +۴ مورد دیگر

Dao Zhou is an Associate Professor at Aalborg University's Department of Mechatronic Systems, part of The Faculty of Engineering and Science. His research focuses on power electronics reliability, wind turbine systems, and grid integration of renewable energy. He holds a PhD in Electrical Engineering from Aalborg University (2014), specializing in reliability assessment of wind turbine systems. His key research areas include power converter control strategies, semiconductor reliability, and grid-forming/grid-following inverter technologies. He has led projects such as the Physics-informed AI for Prognostics in Power Converters and the HELP laboratory platform initiative. Zhou has supervised four PhD students and authored over 198 publications, with notable awards including the IEEE ICPE 2023-ECCE Asia and MPCE 2021 Best Paper Award. Recent work emphasizes predictive maintenance via physics-informed neural networks and seamless control transitions between grid modes. His lab collaborations span Europe, focusing on improving renewable energy system reliability and educational lab infrastructure.

Xing Liمشاهده پروفایل

استاد

• International Relations
• Globalization and Social Change
• China and International Relations
• +۵ مورد دیگر

Xing Li is a Professor in the Department of Politics and Society at Aalborg University, affiliated with the Faculty of Social Sciences and Humanities. Their research focuses on global political dynamics, particularly China's role in international relations, multi-order world governance, and Arctic peace initiatives. Key projects include the 'Anticipating Governance in the Coming Multi-Order World' (2023-2026) and 'Preserving the Arctic as an International Zone of Peace' (2021-2023). Education details are not explicitly provided in the text, but Li's expertise spans international relations theory, political economy, and development studies. Their research interests integrate themes like globalization, social change, and East Asian regional integration, often addressing contemporary challenges in global governance. Recent research trends include interdisciplinary collaboration between political science and technical fields (e.g., energy systems and materials science), as evidenced by publications on fuel cell diagnostics and battery technologies. These studies highlight innovative applications of data-driven methods in both social and engineering contexts. Li has received the 'Teacher of the Year' award (2020) and has supervised one PhD student, J. Pang. They actively engage in academic activities, including organizing conferences on global south dynamics and multi-order world narratives. Li's work is supported by grants from institutions like the Asia Foundation and has been widely disseminated through media outlets like China Daily and South China Morning Post .

Mahdi Abkarمشاهده پروفایل

دانشیار

• Fluid Mechanics
• Turbulence
• Data-driven Modeling
• +۵ مورد دیگر

Mahdi Abkar is an Associate Professor at the Department of Mechanical and Production Engineering, Aarhus University, leading the Fluids and Energy section. His research focuses on fluid mechanics, turbulence modeling, and wind energy optimization using computational fluid dynamics (CFD) and machine learning techniques. Research Areas: Fluid Mechanics, Turbulence, Wind Energy, Data-Driven Modeling Affiliation: Aarhus University, College of Engineering His recent work emphasizes turbulence modeling, LES/RANS simulation improvements, and wind farm power prediction. Articles highlight data-augmented models, flow separation analysis, and drag reduction strategies. He contributes to CFD applications in renewable energy systems, including ultrasonic flow meter design and atmospheric boundary layer interactions.

Andrea Vandinمشاهده پروفایل

دانشیار

• Formal methods
• Qualitative and quantitative system modeling and analysis
• Domain Specific Languages
• +۷ مورد دیگر

Andrea Vandin serves as an Associate Professor in the Formal Methods for Safe and Secure Systems section at DTU Compute, Department of Applied Mathematics and Computer Science, Technical University of Denmark. Her research integrates theoretical computer science with practical system analysis, focusing on formal verification methodologies for complex systems. Her primary research interests include: Formal methods for system verification Qualitative and quantitative modeling techniques Domain-specific language development Large-scale performance analysis Model reduction algorithms Chemical reaction network analysis Statistical model checking Recent publications demonstrate expertise in constrained lumping of chemical systems, network embedding through equitable partitions, and stochastic conformance checking. Her work bridges computer science, mathematics, and systems biology with applications in sustainable system design. She actively contributes to UN Sustainable Development Goals through formal verification approaches for safe and secure systems. Her research shows strong trends toward applying model reduction techniques to chemical reaction networks and agent-based systems, with increasing focus on statistical verification methods and probabilistic modeling. The integration of MultiVeStA with Mesa for Python agent-based models represents a significant contribution to verification capabilities in simulation environments.

Jordan Andrew Snyderمشاهده پروفایل

مدرس

• Hematology
• Mathematical Biology
• Oncology
• +۳ مورد دیگر

Jordan Andrew Snyder serves as a Visiting Lecturer in the Department of Science and Environment at Roskilde University, Denmark, where he is affiliated with the Centre for Mathematical Modeling - Human Health and Disease. His academic work integrates advanced mathematical techniques with biomedical research, particularly in hematology and complex network dynamics. Dr. Snyder's research spans two primary domains: Biomedical Modeling : Focused on myeloproliferative neoplasms (MPNs), including stem cell dynamics during ruxolitinib treatment, CALR mutation progression from clonal hematopoiesis to myelofibrosis, and prognostic markers like neutrophil-to-lymphocyte ratios Network Science : Investigating oscillator synchronization, coarse-grained modeling of complex systems, cascading failures in modular networks, and emergent structures in mutualistic ecosystems His publication analysis reveals a distinctive interdisciplinary trajectory where mathematical frameworks bridge hematologic malignancies and fundamental network principles. Recent work demonstrates how amplitude dynamics stabilize oscillator clusters (2025) and how CALR mutations manifest in population screening (2024), showcasing dual expertise in theoretical dynamics and clinical translation. Dr. Snyder operates within Roskilde University's Centre for Mathematical Modeling - Human Health and Disease, an interdisciplinary hub where mathematical approaches address complex biomedical challenges through close collaboration with clinical researchers and international institutions including Memorial Sloan Kettering Cancer Center.

• Software Engineering
• Process Modeling
• Business Process Management
• +۵ مورد دیگر

Thomas Troels Hildebrandt is a Professor in the Department of Computer Science at the University of Copenhagen, where he heads the Software, Data, People & Society research section. His work focuses on developing reliable and flexible software systems that adapt to user needs and legislative changes, with applications in digital law, workflows, and business processes. His educational background includes: PhD in Computer Science from Aarhus University (awarded February 23, 2000) Professor Hildebrandt's research spans Software Engineering , Process Modeling , and Business Process Management , with a focus on declarative approaches like Dynamic Condition Response (DCR) graphs. His work integrates formal methods to ensure system reliability in contexts ranging from smart contracts to public governance. He actively explores societal implications of AI, advocating for transparency and user-centered design in digital systems. Recent publications demonstrate a strong trend toward declarative process modeling applied to smart contracts and public governance . Key developments include DCR graphs for dynamic behavior modeling, cross-chain business logic monitoring, and digital compliance frameworks. His interdisciplinary approach bridges computer science with real-world societal challenges, particularly in adapting systems to evolving legislation and user requirements. No specific scientific awards are mentioned in the provided information. Professor Hildebrandt leads interdisciplinary research projects and serves on advisory boards for digitalization and AI. His work has fostered industry collaboration, including founding DCR Solutions based on his research. He acts as an independent consultant and speaker in digital transformation, with recent projects focusing on blockchain integration and public sector AI ethics. He directs the Software, Data, People & Society research section, which develops human-centered methods for adaptable digital systems. Current initiatives include DCR graph applications for GDPR compliance, smart contract security, and transparent AI in public services, with strong industry and government partnerships.

Stig Helvegمشاهده پروفایل

استاد

• Catalysis
• Surface Science
• Electron Microscopy
• +۷ مورد دیگر

Stig Helveg is a Professor and Director of the Danish National Research Foundation’s Center for Visualizing Catalytic Processes (VISION) at the Technical University of Denmark. He holds a PhD in Physics from Aarhus University (2000) and previously served as a Fellow at Topsoe A/S. His research focuses on atomic-resolution electron microscopy in catalysis and surface science, pioneering in situ and operando techniques under reaction conditions. His interdisciplinary work integrates electron microscopy with MEMS, chemical engineering, and materials science to study catalyst dynamics at the atomic level. Key achievements include the development of advanced TEM imaging methods, such as exit-wave reconstruction and high-resolution environmental TEM. His awards include the EliteForsk Prize (2018), MRS Innovation Award (2019), and Microscopy Society of America Fellowship (2021). He supervises multiple PhD students and leads projects on catalyst stability, CO 2 electrolysis, and nanoparticle dynamics. The VISION Center and Department of Physics provide his primary affiliations, with research spanning catalysis, nanomaterials, and quantum phenomena observed via electron microscopy. Recent articles highlight advancements in single-electron coherence, CO 2 electrolysis catalysts, and atomic-scale imaging of defects in CrSBr. His work bridges quantum mechanics with practical catalytic applications, emphasizing real-time observation of material behavior under reaction conditions.

Ira Assentمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Clustering Algorithms
• +۵ مورد دیگر

Professor Ira Assent is affiliated with the Department of Computer Science at Aarhus University. Their research focuses on machine learning, data mining, and visualization, with applications in climate science, medical informatics, and computer vision. Professor Assent leads projects such as Light-IoT (analytics on compressed IoT data), WallViz (interactive visualization for massive datasets), and eData (anomaly detection in e-science). Their work emphasizes scalable algorithms, explainable AI, and interdisciplinary applications. Recent publications address rainfall prediction using deep learning, entity summarization via knowledge graphs, and efficient clustering techniques. Projects like RainAI demonstrate contributions to weather modeling and satellite data analysis. Collaborative efforts span academic and industrial domains, with a strong emphasis on practical, user-centric solutions. Selected research contributions include advancements in density-based clustering (e.g., AnyDBC, DISCO), parallel algorithms optimized for GPUs (HUNIPU), and visualization frameworks (AVID). Their work bridges theoretical computer science with real-world challenges, such as improving decision-making through interactive visualizations and enhancing medical information retrieval systems. Ongoing projects aim to address computational efficiency in large-scale data analytics while maintaining interpretability. Key areas of innovation include explainable AI (e.g., InteDisUX), climate modeling (DROPP), and hardware-accelerated algorithms (GPU-FAST-PROCLUS). These efforts reflect a commitment to advancing both foundational methods and applied technologies that impact diverse fields from environmental science to healthcare.

Marco Antonio Muniz Rodriguezمشاهده پروفایل

دانشیار

• Timed Automata
• Formal Verification
• Model Checking
• +۶ مورد دیگر

Marco Antonio Muniz Rodriguez is an Associate Professor at the Department of Computer Science, part of The Technical Faculty of IT and Design at Aalborg University. His research focuses on formal methods, specifically timed automata and model checking, with applications in machine learning, stochastic systems, and safety-critical decision-making. He contributes to the UPPAAL verification tool and explores interdisciplinary areas like healthcare optimization and traffic systems. He participated in the BEO-COVID project (2020), developing decision support tools for pandemic management. His work integrates formal verification techniques with machine learning to address real-world problems such as traffic rerouting and epidemic prevention. Key collaborations include projects with the Poul Due Jensen Foundation and industrial partners. His research spans theoretical advancements in timed systems and practical implementations, emphasizing computational efficiency through GPU acceleration and static analysis. He has published on topics ranging from stubborn set reduction to proactive traffic management, demonstrating a commitment to both foundational research and applied solutions.

Torben Knudsenمشاهده پروفایل

دانشیار

• Wind Turbine Engineering
• Process Control
• Control Systems
• +۶ مورد دیگر

Torben Knudsen is an Associate Professor at the Department of Electronic Systems, Aalborg University, Denmark. He is affiliated with the Automation & Control Learning and Decisions Lab and holds positions in The Technical Faculty of IT and Design. His research focuses on control systems, wind turbine engineering, stochastic processes, and biomedical applications such as diabetes modeling. Education: Advanced degrees in engineering, though specific details are not explicitly listed. Research Interests: Wind turbine dynamics, offshore wind farm control, stochastic modeling of biomedical systems, fault detection, and optimization techniques. His work integrates control theory with renewable energy systems, particularly addressing challenges in wind turbine aeroelasticity and floating offshore wind farms. Recent projects include the development of health-aware simulation platforms (FOWLTY) and insulin dose optimization algorithms for type 2 diabetes. Key Projects: ICONIC (2023-2027) : Focuses on intelligent control of industrial processes. PRESTIGE (2020-2023) : Explored predictive manufacturing and quality control. Modelling and Control of Type 2 Diabetes (2019-2024) : Developed stochastic models for glucose-insulin dynamics. Knudsen has received the Best Paper Award (2015) for contributions to predictive manufacturing. His research also extends to pandemic modeling, including work on SARS-CoV-2 variant outbreaks and hospital preparedness during epidemics. Advising & Grants: Active in interdisciplinary collaborations, including funding from EU projects like Aeolus and OFFWIND. He contributes to grants focusing on wind farm control, diabetes modeling, and stochastic systems. Labs & Teams: Leads the Automation & Control Learning and Decisions Lab, collaborating with international teams on energy systems and biomedical engineering challenges.

Tiziana Di Matteoمشاهده پروفایل

استاد

• Econophysics
• Complex Systems
• Complex Networks
• +۷ مورد دیگر

Tiziana Di Matteo is a Professor of Econophysics in the Department of Mathematics at King's College London, part of the Faculty of Natural, Mathematical & Engineering Sciences. She is also External Faculty at the Complexity Science Hub and affiliated with the UCL Centre for Blockchain Technologies, the Complex System Laboratory, the Complex Systems Society, and the Museo Storico della Fisica e Centro Studi e Ricerche “E. Fermi”. Her research focuses on econophysics, complex systems, complex networks, and data science , with applications in financial modeling, systemic risk, and multiscaling analysis. She integrates methods from statistical physics and network science to analyze financial markets and economic interactions. The most recent publications reveal a strong trend in financial network modeling, multiscaling volatility, tensor-based learning for multidimensional data, and early warning systems using scaling properties . Her work bridges econophysics and traditional financial economics, emphasizing empirical validation and interdisciplinary approaches. Scientific Leadership and Editorial Roles: Editor-in-Chief, Journal of Advances in Mathematical Physics Main Editor, Physica A Editor, European Physical Journal B Editor, Artificial Intelligence in Finance Former Editor-in-Chief, Journal of Network Theory in Finance Guest Editor for multiple special issues Tiziana is the co-founder of the Econophysics Network and has served as a consultant for the Financial Services Authority, hedge funds, and financial companies. She has authored over 100 papers and delivered keynote talks globally. She supervises PhD students and leads collaborative research in complex financial systems. She is actively involved in interdisciplinary research collaborations with institutions like the Francis Crick Institute and industrial partners including EDF Research and Unilever.

Sergey Sorokinمشاهده پروفایل

استاد

• Solid Mechanics
• Computational Mechanics
• Structural Dynamics
• +۷ مورد دیگر

Sergey Sorokin is a Professor in the Department of Materials and Production at Aalborg University, Faculty of Engineering and Science, Denmark. His research centers on solid and computational mechanics, with a focus on structural dynamics, wave propagation, vibro-acoustics, and finite element modeling. His research interests include: Wave propagation in periodic and elastic structures Vibro-acoustics and noise control Finite element methods and reduced-order modeling Nonlinear dynamics of beams and shells Acoustic black hole effects and vibration suppression Structural optimization and industrial system analysis The recent publications (2020–2025) demonstrate sustained activity in mechanical wave analysis, nonlinear structural behavior, and acoustic optimization. Key themes include the suppression of bending waves, asymptotic modeling of cylindrical shells, and bi-orthogonality in waveguides. These works reflect an interdisciplinary blend of theoretical mechanics, numerical simulation, and engineering applications. Scientific contributions include: Active participation in long-term research projects on mechanical vibro-acoustics and wave transmission since 2010 Supervision of at least four PhD students Extensive publication record (188 research outputs) with consistent contributions to journals like the Journal of the Acoustical Society of America and European Journal of Mechanics A/Solids He has advised several researchers and contributed to collaborative projects involving structural optimization and industrial component analysis. His work is deeply integrated into both theoretical and applied mechanical engineering, with emphasis on modeling and enhancing structural performance under dynamic loads. Sergey Sorokin is actively involved in research through ongoing projects such as 'Mechanical Vibro-Acoustics and Noise' and 'Analysis and Optimization of Wave Propagation in Periodic Structures'. These efforts are supported by advanced computational modeling and collaboration with peers like N. Olhoff and E. Lund.

Finn Tarpمشاهده پروفایل

استاد

• Development Economics
• Poverty Analysis
• Income Distribution
• +۶ مورد دیگر

Finn Tarp is a Professor of Development Economics at the University of Copenhagen 's Department of Economics since 2002 and Coordinator of the Development Economics Research Group (DERG) . He previously served as Director of UNU-WIDER (2009-2018) and has advised institutions in Vietnam, Finland, and Mozambique. Education : Doctoral dissertation (lic. polit.) in Economics, University of Copenhagen (1989-1992) M.Sc. (cand. polit.) in Economics, University of Copenhagen (1977-1978) Graduate Studies, University of Illinois (1976-1977) Research Interests focus on development economics , particularly poverty dynamics, income distribution, structural transformation, and climate change impacts. His work combines empirical analysis with policy modeling in Sub-Saharan Africa and Southeast Asia, emphasizing institutional diagnostics and socioeconomic resilience. Recent publications demonstrate expertise in disaster recovery economics (Cyclone Idai in Mozambique), inequality analysis (Vietnam experiments), and industrial development (Africa-Asia comparisons). Key journals include World Development , Journal of Development Studies , and Review of Development Economics . Awards include: Knighthood, Order of the Dannebrog (2015) Vietnamese Government Medals for Planning Support (2014) and Science Merit (2011) University of Copenhagen Teaching Award (1996) Zeuthen Award, Danish Economic Society (1979) With supervision experience across bachelor to PhD levels and roles in academic governance (e.g., Journal of Development Studies Board), his contributions span research, policy, and education. Current work examines structural transformation in Vietnam and Mozambique's institutional development.