جست‌وجوی استاد و پژوهشگر

Guangya Yangمشاهده پروفایل

دانشیار

• Power System Stability
• Offshore Wind Energy
• Cyber-Physical Power Systems
• +۷ مورد دیگر

Guangya Yang is an Associate Professor at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), with expertise in power system stability, control, and protection of low-inertia systems, particularly in offshore wind applications. He has worked full-time as an electrical design and simulation specialist at Ørsted (2020-2021) and maintains active roles in IEEE, IEC standardization, and editorial work as lead editor for IEEE Access PES. PhD in Electrical Engineering (University of Queensland, 2008) Senior Member of IEEE Former expert member of European Technology & Innovation Platform for solar PV His research focuses on electromagnetic transient simulation, cyber-physical energy systems, and grid compliance for wind power plants. He leads the Horizon 2020 InnoCyPES project (€12m+ grants), training 15 early-stage researchers in cyber-physical energy systems. Key contributions include validating synchronous condensers for low-inertia systems and developing industry training programs on offshore wind control strategies. Coordinated Hardware-in-the-Loop test bench standards (IEC61400-21-5) Advances in grid-forming converter stability and fault ride-through assessment Developed digital twins for power grid validation Scientific Recognition: World’s Top 2% Scientists (Elsevier/Stanford, 2024) Advising & Grants: Supervises 5 PhD students in projects related to machine learning, digital twins, and predictive maintenance. Coordinates €12m+ in research grants, including Horizon 2020’s InnoCyPES. Labs & Collaborations: Works with Ørsted, industry partners, and international universities on offshore wind validation and digitalization.

Ulrik Dam Nielsenمشاهده پروفایل

دانشیار

• Naval Architecture
• Ship Motion Dynamics
• Sea State Estimation
• +۷ مورد دیگر

Ulrik Dam Nielsen is an Associate Professor in the Section for Fluid Mechanics, Coastal and Maritime Engineering at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU). He also held an external position as Associate Professor II at the Norwegian University of Science and Technology (NTNU) from 2014 to 2023, reflecting strong international collaboration. His work contributes to UN Sustainable Development Goals related to sustainable maritime operations and clean energy. His research focuses on naval architecture and ship motion dynamics , particularly in the context of sea state estimation , added resistance in waves , and real-time prediction of vessel responses . He integrates data analytics , estimation theory , and machine learning to develop methods for monitoring hydrodynamic performance and enhancing maritime safety and energy efficiency. A central theme of his work is using ships as mobile wave sensors—transforming operational vessels into 'sailing wave buoys' for environmental monitoring. His recent publications show a clear shift toward data-driven methodologies, especially machine learning applications in sea state estimation, added resistance modeling, and performance monitoring. These works span journals like Ship Technology Research and Journal of Offshore Mechanics and Arctic Engineering , and conferences such as IEEE MetroSea, highlighting interdisciplinary innovation at the intersection of classical marine engineering and modern AI. Best Paper Presented by a Young Researcher Award (First Classified), 2024 (jointly awarded) He actively supervises PhD students—such as R. E. G. Mounet, M. Mittendorf, J. P. Tomy, and A. Oikonomakis—on projects funded by DTU and collaborative initiatives. His leadership in projects like WEFOSWAB (Wave Estimation and Forecasting Using Ships as Buoys) and data-driven added resistance modeling underscores his role in advancing smart maritime technologies. He also contributes to open science through the public release of datasets such as NetSSE . He teaches core courses including Introduction to Ships and Floating Structures , Marine and Ocean Engineering , and Ship Operations , shaping the next generation of maritime engineers.

Axel Polleresمشاهده پروفایل

استاد

• Semantic Web
• Knowledge Engineering
• Data Management
• +۱۲ مورد دیگر

Axel Polleres is a full professor in the area of 'Data and Knowledge Engineering' at the Vienna University of Economics and Business (WU Wien) and a faculty member at the Complexity Science Hub (CSH) in Vienna, a position he has held since January 2017. His work bridges academic research and real-world applications in semantic technologies, knowledge graphs, and data governance. His research interests lie at the intersection of semantic web technologies, knowledge engineering, and data management. Focused on querying and reasoning over ontologies, logic programming, and rule-based systems, he explores how structured data can be effectively managed, validated, and integrated—especially through standards like SPARQL and SHACL. His work extends to applications in open data, legal data, biomedical informatics, and socio-environmental challenges such as climate and public health. The most recent publications highlight a growing trend toward practical and societal applications of knowledge graphs, including climate risk assessment, crisis response, healthcare accessibility, and open data governance. These works combine technical rigor in semantic modeling with impactful real-world use cases, particularly in European and Austrian contexts. Axel Polleres has been actively involved in international standardization, notably as co-chair of the W3C SPARQL Working Group, and serves on the editorial boards of the Semantic Web Journal and Journal of Web Semantics . He has contributed to numerous European and national research projects and has published over 100 articles in top-tier journals and conferences. He advises and collaborates with researchers across disciplines and institutions, contributing to interdisciplinary teams working on complex societal challenges. His work is supported by significant research grants, though specific funding sources are not detailed in the provided text. He leads and participates in research groups focused on semantic technologies, knowledge graphs, and data-driven policy.

Frank Kjeldsenمشاهده پروفایل

استاد

• Proteomics
• Mass Spectrometry
• Nanoparticle-Biological Interactions
• +۷ مورد دیگر

Frank Kjeldsen is a Professor and group leader in the Protein Research group at the Department of Biochemistry and Molecular Biology , University of Southern Denmark . His research focuses on proteomics, mass spectrometry, and the biological effects of nanoparticles, with a strong emphasis on method development in negative ion mode and ultrafast proteomic platforms. His research interests span: Proteomics and systems biology Nanoparticle-biological system interactions Development of novel mass spectrometry and chemical biology methods Fundamental gas-phase peptide chemistry Metabolomics and multi-omics integration Recent publications (2023–2025) highlight trends in ultrafast proteomics , multi-omics for environmental and biomedical applications, nanoplastic toxicity , and neuroprotection . His work frequently involves advanced LC-MS/MS techniques, ion mobility, and software development for data analysis. Scientific recognition includes: 2 prizes (as noted in his CV profile) He actively supervises research and collaborates on multiple interdisciplinary projects. His lab, the Frank Kjeldsen Lab , is part of the Biomedical Mass Spectrometry research section. He has contributed to numerous grants and collaborative research efforts in toxicology, cancer, and environmental science.

Morten Munkgaard Møllerمشاهده پروفایل

دانشیار

• Supply Chain Management
• Purchasing and Category Management
• Interorganizational Relationships
• +۴ مورد دیگر

Morten Munkgaard Møller is an Associate Professor at the Aalborg University Business School, affiliated with The Faculty of Social Sciences and Humanities and the Marketing and Market Processes Research Group. His research focuses on Supply Chain Management, particularly procurement and category management, emphasizing strategic theory and interorganizational relationships in B2B contexts. He explores topics such as supplier-buyer dynamics, sustainable sourcing, and cross-functional collaboration in both private and public sectors. Key projects include the 'Innovationshub for Cirkulær Plast' (2025–2028) and 'Technology absorption through supplier relationships' (2003). His work bridges theoretical frameworks like contingency theory and typological models with practical applications in strategic sourcing and supply chain ecosystems. Møller has published widely on themes including supply chain ecosystems, distributive justice in apparel sourcing, and big data in procurement. He actively engages in media discussions about procurement strategies in crisis scenarios and category management best practices. His research emphasizes alignment between organizational strategy and operational execution, with a focus on achieving equitable and sustainable outcomes in supply chain relationships.

Lukas Esterleمشاهده پروفایل

دانشیار

• Autonomous Systems
• Multi-Agent Systems
• Computational Self-awareness
• +۳ مورد دیگر

Lukas Esterle is Associate Professor at Aarhus University's Department of Electrical and Computer Engineering. His research focuses on enabling collaboration among autonomous systems through computational self-awareness, collective learning, and autonomous decision-making. His work draws inspiration from natural systems, psychology, and anthropology to develop resilient distributed systems. Key research areas include: autonomous multi-agent coordination, digital twin architectures, computational trust models, and distributed learning frameworks for robotic systems. His investigations target applications in smart cities, industrial automation, and edge computing environments. Professor Esterle teaches courses in Software Engineering, Computer Games Technologies, and Autonomous Agents & Multi-Agent Systems. He coordinates multiple European research projects including DIAMOND (Developing Personalized Capabilities), FLOCKD (Federated Learning for Collaborative Knowledge), and MARVEL (Multimodal Data Analytics for Smart Cities).

• Big Data
• Mobility Data Analytics
• Predictive Analytics
• +۵ مورد دیگر

Panagiotis Tampakis is an Associate Professor at the Department of Mathematics and Computer Science, University of Southern Denmark. His research focuses on Big Data Analytics, Mobility Data Analysis, and Predictive Modeling with applications in fields such as maritime surveillance, sports analytics, and healthcare informatics. He is actively involved in developing scalable algorithms for trajectory clustering, spatiotemporal data mining, and distributed systems. His work emphasizes practical solutions through platforms like i4sea for maritime activity monitoring and Pythia for distributed trajectory prediction. He has collaborated internationally on mobility data projects and earned the SSTD 2021 Best Paper Award for innovative spatial-keyword indexing techniques. Tampakis also supervises student projects integrating machine learning with real-world problems in finance, sports, and journalism. Key research themes include predictive analytics for traffic patterns, outlier detection in traffic flows, and analyzing passing sequences in football to predict goal-scoring opportunities. His publications span trajectory clustering, spatial-keyword query optimization, and explainable AI in journalism. Awards: SSTD 2021 Best Paper Award Key Projects: i4sea maritime platform, Pythia trajectory prediction framework, RoadRunner big data processing framework Collaborations: Active in global mobility data communities, with contributions to BMDA initiatives

Michele Albanoمشاهده پروفایل

دانشیار

• Internet of Things (IoT)
• Energy Engineering
• Quality of Service (QoS)
• +۵ مورد دیگر

Affiliations & Roles Michele Albano is an Associate Professor at the Department of Computer Science, Aalborg University, Denmark. He is affiliated with The Technical Faculty of IT and Design, focusing on research in IoT, Cyber-Physical Systems, and Edge Computing. He leads the Productive4.0 project (2017–2020), funded by Horizon Europe, addressing Industry 4.0 challenges in product lifecycle management. His work integrates formal verification tools like Uppaal with real-world applications in robotics, energy systems, and blockchain-based platforms. Research Interests Albano's research spans IoT architecture optimization , energy-efficient systems , and model-driven engineering . He develops tools for autonomous exploration algorithms (MAES), edge-cloud resource orchestration, and fault-tolerant computation offloading. His work bridges theoretical models (e.g., Uppaal SMC) with practical implementations in smart grids and robotic systems. Recent projects include blockchain-based crowdsourcing for machine learning and energy-aware thermal dynamics estimation in buildings. Collaborations & Impact He collaborates with the European Industry 6.0 community, contributing to the Arrowhead Framework for interoperable IoT systems. His research outputs include 112 publications, with 2025 highlights in human-inspired robotics and cognitive cloud frameworks. Media coverage in 2024–2025 highlights his work on green IT and secure API generation. Albano advises students on system modeling (e.g., ACSmt plugin development) and edge computing optimization. Labs & Teams His research group focuses on Cyber-Physical Systems and Smart Grids , with contributions to tools like RoutesMobilityModel and FlexHousing. He actively participates in workshops on New Trends in Software Architecture (SATrends '24) and IEEE conferences on Industrial Informatics.

Iskra Dukovska-Popovskaمشاهده پروفایل

دانشیار

• Supply Chain Management
• Circular Economy
• Machine Learning
• +۵ مورد دیگر

Iskra Dukovska-Popovska is an Associate Professor at the Department of Materials and Production, Faculty of Engineering and Science, Aalborg University. She holds a Ph.D. in Industrial Engineering and has over 20 years of research experience focusing on sustainable supply chains, circular economy, healthcare operations, and product development methodologies. Her research integrates machine learning, information systems, and operational research to address challenges in textile recycling, fresh food logistics, and healthcare resource optimization. Recent projects include SATIN (Nordic circular textile systems), RefArc (healthcare reference models), and SmartLog Plus (supply chain innovation). She has supervised 1 Ph.D. student and contributed to over 75 peer-reviewed publications. Key research themes include: End-of-life textile systems and consumer engagement Machine learning applications in surgery duration prediction Manufacturing workforce skill transitions for sustainability Agile-stage gate hybrid product development processes Notable awards include the 2023 NOFOMA Best Paper Award for textile recycling research, 2019 John Burbidge Award for forecasting models, and 2016 Holland Award for product development innovation. She has also contributed to policy development through impacts like the Nordic textile supply-demand balance analysis. Current activities involve cross-industry collaborations on circular economy implementation, digital transformation in manufacturing, and sustainable healthcare operations optimization through data-driven approaches.

János Kertészمشاهده پروفایل

استاد

• Network Science
• Computational Social Science
• Econophysics
• +۷ مورد دیگر

János Kertész is a Professor and Head of the Department of Network and Data Science at the Central European University (CEU), currently based in Vienna. He is also an elected member of the Hungarian Academy of Sciences. Previously, he held professorial and research positions at the Budapest University of Technology and Economics and the Hungarian Academy of Sciences, where he served as Director of the Institute of Physics. His research lies at the intersection of statistical physics and social sciences, with major contributions to network science, econophysics, computational social science, and algorithmic fairness. He investigates systemic risks in economic networks, opinion dynamics in algorithmically biased environments, poverty mapping using big data, and the role of automation in online extremism. The most recent articles highlight a strong trend in applying complex systems methodologies to real-world socioeconomic problems—particularly through large-scale network analysis, multimodal data integration, and policy-relevant modeling in inequality, supply chains, and digital fairness. His collaborative work spans institutions like the Complexity Science Hub (CSH) in Vienna. Elected member of the Hungarian Academy of Sciences He has advised numerous researchers and contributed to major interdisciplinary grants, particularly in complexity science and data-driven social science. His leadership in organizing NetSci 2023, the largest network science conference, underscores his role in fostering global scientific collaboration. He is central to projects involving high-resolution poverty mapping, economic systemic risk, and ethical AI applications. He is actively involved with the Complexity Science Hub (CSH), where CEU is a partner institution, and contributes to interdisciplinary teams working on economic modeling, social network analysis, and crisis preparedness using granular supply chain and VAT data.

Takayuki Mizunoمشاهده پروفایل

دانشیار

• Computational Social Science
• Econophysics
• Network Science
• +۱۲ مورد دیگر

Takayuki Mizuno is an Associate Professor at the National Institute of Informatics and SOKENDAI (The Graduate University for Advanced Studies), where he leads interdisciplinary research at the intersection of informatics, econophysics, and computational social science. His work focuses on analyzing complex global systems such as economic networks, financial markets, human mobility, and geopolitical dynamics using big data and network science. Doctor of Science, Chuo University (Physics) JSPS Research Fellow (2004) Lecturer, Institute of Economic Research, Hitotsubashi University (2007–2010) Associate Professor, University of Tsukuba (2011–2013) Senior Research Fellow, Canon Institute for Global Studies (2009–present) His research interests include computational social science, econophysics, network science, wealth inequality, financial bubbles, cryptocurrency regulation, public opinion manipulation, and global supply chain ethics. He develops models to understand market dynamics, detect hidden financial influences, and visualize geopolitical power shifts. The recent articles highlight a consistent trend in applying big data and network analysis to real-world socio-economic problems: visualizing China's indirect control in global shareholder networks, detecting financial risks, analyzing online market competition, studying supply chain ethics, and understanding cultural integration through human mobility. The work bridges physics, economics, computer science, and political science. Scientific Awards: Best Paper Award, Japanese Society for Artificial Intelligence (2019) Best Paper Award, Information Processing Society of Japan (2019, 2013) Student Encouragement Award, IPSJ (2019) Best Paper Award, Transdisciplinary Federation of Science and Technology (2019) JSPS Research Fellow (2004) Dr. Mizuno advises multiple Ph.D. and master’s students and leads the Mizuno Laboratory, which conducts cutting-edge research on global challenges. He has secured significant research grants from JSPS, JST (Sakigake), and other funding bodies. His work is frequently featured in major media outlets including Nikkei, NHK, The Wall Street Journal, and Yomiuri Shimbun, indicating broad societal impact. He is actively involved in professional service, including as Director of the Society for Computational Social Science of Japan and member of the Editorial Board of the Japanese Society for Artificial Intelligence. He also participates in government advisory committees on big data, economic policy, and telecommunications. His lab, the Mizuno Laboratory, focuses on the fusion of political economy and data science, aiming to disentangle complex global networks to address issues like economic bubbles, terrorism, and social polarization.

Mohsen Banaeiمشاهده پروفایل

پژوهشگر

• Energy Flexibility
• Power Systems
• Distributed Energy Systems
• +۴ مورد دیگر

Mohsen Banaei is a tenure-track researcher in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU) . His work focuses on energy flexibility, power systems, and smart grid technologies, with contributions to renewable energy integration and optimization algorithms. Key research areas: Demand-side flexibility analysis TSO-DSO coordination mechanisms Secure grid automation solutions Energy forecasting models Stochastic optimization of energy systems Collaborations: Banaei collaborates with researchers across Denmark and internationally, with significant contributions to projects involving distributed energy resources, grid resilience, and Internet of Energy platforms. Contact: Email: moban@dtu.dk Phone: 91107129 Location: Asmussens Allé, 303B, 009, 2800 Kgs. Lyngby, Denmark

Rune Hylsberg Jacobsenمشاهده پروفایل

استاد

• Energy Systems
• Drone Technology
• Blockchain Applications
• +۱۲ مورد دیگر

Rune Hylsberg Jacobsen is a Professor at the Department of Electrical and Computer Engineering, Aarhus University. His work bridges energy systems, drone technology, and blockchain applications, with a focus on smart grids, autonomous systems, and decentralized infrastructure. Research interests include: Security frameworks for prosumer-driven energy systems using blockchain mmWave and LEO satellite communication protocols Homomorphic encryption for smart meter privacy Cooperative drone swarm navigation and infrastructure inspection Earth observation via CubeSats for climate research His recent publications highlight advancements in: Zero trust security models for renewable energy certificates Transport protocol optimization in satellite networks AI-driven charging window scheduling for drone fleets Decentralized identity management in Web3 infrastructure Key projects include: DISCO-2: Student CubeSat for Arctic climate monitoring Drones4Safety: Safety-critical inspection systems VPP4SGR: Virtual Power Plant networks

• Journalism
• Media Studies
• Digital Media
• +۳ مورد دیگر

Aske Kammer is an Associate Professor at the Department of Communication and Arts, Roskilde University. His research focuses on innovation in the news industry, particularly how news organizations adapt to new technologies and utilize user data for decision-making. He also investigates digital business models for news media and has contributed to the Journal of Media Management. His recent publications include studies on datafication in news work, podcasting institutional development, and subsidized news-media innovation. Kammer leads and participates in several research projects such as Transnational Media Management and The Datafied News Industry. 2025: Datafied news work: A scoping literature review 2025: Nyhedsmediernes innovationsstøtte 2014-2023 2025: Subsidized news-media innovation: outputs, outcomes, and impact Kammer's work bridges theoretical and practical aspects of media management, emphasizing the intersection of communication, journalism, and digital transformation.

Yushuai Liمشاهده پروفایل

استادیار

• Digital Twin
• Energy Internet
• Reinforcement Learning
• +۷ مورد دیگر

Yushuai Li is an Assistant Professor in the Department of Computer Science at Aalborg University. His research focuses on digital twin technologies, energy internet systems, distributed optimization, and cyber-physical security for energy networks. Institution: Aalborg University, Denmark Academic Rank: Assistant Professor Email: yushuaili@ieee.org, yusli@cs.aau.dk Research Interests: Li's work bridges artificial intelligence with energy systems, emphasizing: Digital Twin for Energy and Transportation Integration Reinforcement Learning in Power Trading Distributed Control for Microgrids Privacy-Preserving Energy Dispatch Autonomous Driving-Energy System Coupling Scientific Contributions: His recent publications address critical challenges in energy internet resilience, including: Distributed control under stealthy attacks Noise-resilient microgrid operations Multi-timescale optimization algorithms Event-triggered control strategies Secure peer-to-peer energy trading Honors & Awards: Recipient of multiple prestigious awards, including: Best Paper Awards (MPCE, ICCSIE, IEEE EI2) Excellent Young Expert Award (MPCE, 2023) National Natural Science Prizes (CAA 2022-2023) Highly Cited Papers (8 ESI Highly Cited, 2 ESI Hot Papers) H-index 24 with 2500+ Google Scholar Citations Academic Leadership: Serves as Associate Editor for four IEEE journals and chairs sessions at leading conferences like IEEE SmartGridComm, ISIE, and IEEE EI2. His 70+ publications span top venues including IEEE Transactions on Cybernetics, Smart Grid, and ACM SIGMOD.