جست‌وجوی استاد و پژوهشگر

Hendrik Harmsمشاهده پروفایل

پژوهشگر ارشد

• Ion Channel Biophysics
• Protein Engineering
• Molecular Pharmacology
• +۳ مورد دیگر

Hendrik Harms is a Postdoctoral Researcher (Research Fellow) in the Department of Drug Design and Pharmacology at the Faculty of Health and Medical Sciences, University of Copenhagen, with research focusing on ion channel biophysics and protein engineering. His work investigates sodium channel regulation by G protein-coupled receptors, phosphorylation mechanisms, and disease-causing mutations using advanced biochemical and computational techniques. His research spans ion channel biophysics, molecular pharmacology, and cardiac electrophysiology, emphasizing structure-function relationships in sodium channels (NALCN and Nav1.5). He employs protein semi-synthesis, molecular dynamics simulations, and trans-splicing methodologies to dissect channel dysfunction in neurological and cardiac disorders, bridging fundamental biochemistry with therapeutic applications. Analysis of his 2020-2023 publications reveals a cohesive research trajectory centered on sodium channel pathophysiology, with increasing emphasis on engineering approaches for channel modification. His work integrates biophysical, computational, and protein engineering disciplines to elucidate mutation-phosphorylation cross-talk and develop novel tools for ion channel manipulation, demonstrating strong interdisciplinary collaboration. Dr. Harms operates within the Department of Drug Design and Pharmacology at the University of Copenhagen, maintaining active collaborations with Sørensen A. Pless's research group and international partners on ion channel structure-function studies and protein engineering applications.

Lars Konzackمشاهده پروفایل

دانشیار

• Industrial gamification
• Game research
• Ludology
• +۶ مورد دیگر

Lars Konzack is an Associate Professor at the University of Copenhagen's Department of Media, Cognition and Communication within the Faculty of Humanities. His academic work spans digital culture, game studies, and transmedial phenomena, with a particular focus on ludology and the application of game elements in non-game contexts. He maintains an active research profile with numerous publications and collaborations with institutions including Innovation Fund Denmark, Novo Nordisk, and Biolean. His educational background isn't explicitly detailed in the available sources, but his expertise demonstrates deep knowledge of media theory, cultural studies, and digital humanities. Konzack's research interests include industrial gamification, game research/ludology, and transmediality, with significant contributions to understanding imaginary worlds, internet phenomena, and the cultural impact of gaming. Konzack's scholarly output shows consistent focus on the theoretical frameworks of gaming culture, particularly examining how fictional worlds are constructed and experienced across media platforms. His recent work on gamification in industrial contexts represents an important expansion of game studies into practical business applications, while his earlier publications establish him as a significant voice in the academic understanding of role-playing games and transmedial storytelling. His research output includes numerous book chapters, encyclopedia entries, and journal articles, with notable contributions to The Routledge Companion to Imaginary Worlds and Encyclopedia of Information Science and Technology. His 2024 book Gamification and Industry 4.0: Gamified Smart Manufacturing represents a significant interdisciplinary contribution bridging game studies with industrial applications. Konzack maintains an active presence in academic discourse through lectures, conference participation, and media appearances, with documented press coverage across multiple Danish media outlets including DR's 'Kulturen på P1' and 'Go' morgen Danmark.' His work has been referenced in 13 Wikipedia pages and cited by various academic and professional sources. He has developed theoretical frameworks such as the Wunderkammer-Gesamtkunstwerk Model for role-playing game analysis, demonstrating innovation in methodological approaches to game studies. His current research includes a gamification project in collaboration with Innovation Fund Denmark, Novo Nordisk, and Biolean, focusing on practical applications of game elements in industrial contexts.

• Quantum Optics
• Photonics
• Atomic Physics
• +۲ مورد دیگر

Jonas Bundgaard Mathiassen is a Guest Researcher at the Niels Bohr Institute within the Faculty of Science at the University of Copenhagen. His research focuses on quantum photonics and optomechanics, specializing in photonic crystal devices for quantum applications with cold atoms and cavity systems. He recently completed his PhD at the University of Copenhagen in 2024. His doctoral dissertation, titled 'Design and Fabrication of Suspended Si3N4 Photonic Crystal Devices For Use With Cold Atoms', addressed nanofabrication challenges for quantum technologies using silicon nitride photonic structures. Mathiassen's work bridges quantum optics, atomic physics, and condensed matter physics. He develops photonic crystal membranes for quantum optomechanics, with emphasis on phononic engineering to suppress thermal noise. His expertise includes nanofabrication techniques, cavity quantum electrodynamics, and quantum interface design for cold atom systems. His 2023 publication in Optics Express on phononically shielded mirror membranes demonstrates innovative approaches to enhance quantum coherence in optomechanical systems. This research contributes to advancing quantum sensing platforms and quantum network interfaces through precision control of light-matter interactions. No scientific awards were documented in the available information. There is no evidence of graduate student advising or research grant leadership in the provided materials. Mathiassen collaborates within Professor Eugene Polzik's research group at the Niels Bohr Institute, a world-leading team in quantum optics. The group specializes in quantum entanglement, quantum memory, and quantum-enhanced measurements using cold atoms and optomechanical systems, with applications in quantum computing and precision metrology.

Milad Zamaniمشاهده پروفایل

استادیار

• Integrated Circuits
• Biomedical Engineering
• Wireless Power Systems
• +۳ مورد دیگر

Milad Zamani is a Tenure Track Assistant Professor in the Department of Electrical and Computer Engineering at Aarhus University. His research focuses on integrated circuits, biomedical engineering, and wireless power systems with applications in neural engineering and sensor systems. He leads projects such as DONUT (European Doctoral Network for Neural Prostheses and Brain Research) and CorroSense (Self-powered corrosion monitoring). His work spans topics like bio-impedance sensing for wearables, ultrasonic energy transfer for implants, and high-precision analog circuits. Recent projects include thermally-powered leakage detection systems and optogenetic implantable devices. Zamani collaborates on advanced sensor technologies, neuromorphic hardware, and biomedical device miniaturization. His lab develops low-power circuits for medical applications, combining signal processing with cutting-edge microelectronic design.

Peter Nielsenمشاهده پروفایل

استاد

• Artificial Intelligence for Operations Research
• Logistics and Supply Chain Optimization
• Unmanned Aerial Vehicles (UAVs)
• +۳ مورد دیگر

Professor Peter Nielsen is a faculty member at Aalborg University's Department of Materials and Production, part of The Faculty of Engineering and Science. He specializes in Artificial Intelligence for Operations Research, focusing on logistics optimization, unmanned aerial vehicles (UAVs), and heuristic algorithms. His work bridges theoretical research and practical applications in industrial automation and sustainable systems. He has led or participated in multiple research projects, including the ORMS project (Operational Reliability Management System) and the ValuePole initiative, which addressed value chain optimization for SMEs. His research emphasizes AI-driven solutions for maritime search and rescue, UAV operations in dynamic environments, and autonomous systems for healthcare logistics. Notable research interests include optimizing routing and scheduling problems, trustworthiness in autonomous vehicle algorithms, and cross-infection risk mitigation in indoor environments. His contributions span over 210 publications, with recent work highlighted in journals like Journal of Intelligent and Robotic Systems and Marine Policy . Peter has advised two PhD students and contributed to academic activities as a peer reviewer for Production & Manufacturing Research . His work often integrates computational fluid dynamics (CFD) and Taguchi methods for optimizing ventilation systems and reducing disease transmission risks.

Rasmus Løvenstein Olsenمشاهده پروفایل

دانشیار

• Smart Grids
• Distribution Grid Modeling
• Cybersecurity in Energy Systems
• +۵ مورد دیگر

Rasmus Løvenstein Olsen is an Associate Professor at Aalborg University’s Department of Electronic Systems, part of The Technical Faculty of IT and Design. His research focuses on smart grids, energy systems, and cybersecurity in distribution networks. Key areas include distribution grid modeling, smart meter optimization, and anomaly detection in electrical systems. Education: Not explicitly detailed in the provided text, but his academic role implies advanced degrees in Electrical Engineering. His research interests revolve around enhancing grid resilience, improving state estimation techniques, and leveraging data analytics for energy systems. He collaborates on projects like Data Analytics in Smart Distribution Grids and ReDistXAI , addressing challenges in renewable integration and cyber-physical security. Publications span anomaly detection algorithms, cyber-physical control systems, and stochastic network modeling. His work emphasizes practical applications, such as optimizing smart meter deployment and securing grid communication networks. Grants/Projects: 12+ projects, including EU-funded initiatives like Net2DG and RemoteGRID . Awards: None explicitly listed in the text. Labs/Teams: Involved in the Wireless Communication Networks and Green Digital Energy Systems research groups.

Esben Lindgaardمشاهده پروفایل

استاد

• Composite Materials
• Wind Turbine Engineering
• Fracture Mechanics
• +۳ مورد دیگر

Esben Lindgaard is a Professor at the Department of Materials and Production, Faculty of Engineering and Science, Aalborg University. His research focuses on composite materials, fracture mechanics, and fatigue-driven damage in wind turbine structures. Projects: CIRCWIND (Circular material solutions for wind turbines), MulFat (Multiscale fatigue modeling), MADE4WIND (Innovative floating wind components). Research: Specializes in delamination behavior, crack propagation, and computational modeling of composite structures under static and fatigue loading. His recent work explores deep learning for delamination traction fields, cohesive element fatigue modeling, and binder-stabilized fabric forming simulations. Collaborates extensively with industry partners and contributes to open-access datasets and software tools. Awards: AAU Talent Project (2018), honored for wind turbine blade defect research (2020). Expertise: Composite material failure, multiscale modeling, industrial validation, and wind energy structural integrity.

Mehdi Shafiei Joudمشاهده پروفایل

استادیار

• Satellite Geodesy
• Machine Learning Applications
• Geophysical Modeling
• +۷ مورد دیگر

Dr. Mehdi Shafiei Joud is an Assistant Professor in the Department of Sustainability and Planning at Aalborg University , affiliated with the Technical Faculty of IT and Design. His research focuses on integrating satellite geodesy, machine learning, and remote sensing to advance environmental monitoring and Earth system dynamics analysis. Key projects include developing the Real-Time Earth Monitoring and Prediction Systems (REMPS) to assess climate-related risks like land subsidence and sea-level rise. Education : PhD in Satellite Geodesy (KTH Royal Institute of Technology, 2018) MSc in Geographical Information Systems (K.N. Toosi University of Technology, 2007) MSc in Geodesy (K.N. Toosi University of Technology, 2005) BSc in Surveying Engineer and Geoinformatics (K.N. Toosi University of Technology, 2002) His work emphasizes post-glacial rebound modeling , satellite gravity missions (GRACE/GRACE-FO) , and machine learning-driven data assimilation . Research outputs span interdisciplinary topics such as hydrological monitoring, crustal stress prediction, and climate resilience infrastructure. He actively contributes to UN Sustainable Development Goals related to environmental sustainability and education. Grants & Advising : No explicit grants or advisees listed in the text. Labs/Teams : None explicitly mentioned, though his REMPS initiative implies collaborative computational and geospatial teams.

Yuan Liمشاهده پروفایل

پژوهشگر ارشد

• Predictive Control
• Power Electronics
• Microgrid
• +۴ مورد دیگر

Yuan Li is a Postdoctoral Researcher at the Applied Power Electronic Systems group within the Faculty of Engineering and Science at Aalborg University, Denmark, working under the supervision of Professor Frede Blaabjerg. Her research focuses on advanced control methodologies for power electronic systems and microgrids. Her primary research interests include: Predictive Control Power Electronics Microgrid Battery Energy Storage Model Predictive Control DC/DC Converters Transients Dr. Li specializes in model predictive control (MPC) applications for DC microgrids and power converters, with recent work emphasizing transient response optimization, prediction horizon design, and integration of neuromorphic computing for grid resilience. Her publications reveal a strong trend toward machine learning-enhanced control systems and hardware-efficient implementations for renewable energy integration. She serves as Principal Investigator for the project "Dynamic Stabilization of DC Microgrids Based on Model Predictive Control of Point-of-Load Converters" (2021-2024), securing significant research funding to develop MPC algorithms for DC microgrid stabilization. Her collaborative network includes prominent researchers like Frede Blaabjerg, Sahoo, and Dragicevic across multiple high-impact publications.

Birger Andersenمشاهده پروفایل

استاد

• Internet of Things
• Cybersecurity
• Wireless Communication
• +۴ مورد دیگر

Birger Andersen is a Professor in the Department of Engineering Technology and Didactics at the Technical University of Denmark (DTU), specializing in Energy Technology and Computer Science. His research actively contributes to UN Sustainable Development Goals through IoT security, wireless communication, and machine learning applications. He leads multiple projects including Machine Learning for Beehives Monitoring and Towards The 6G Authentication Protocol. Andersen's research spans post-quantum cryptography for IoT devices, security vulnerabilities in autonomous vehicle infrastructures, and wireless protocol analysis (LoRaWAN/NB-IoT). His work integrates machine learning for environmental monitoring and addresses jamming attacks on critical communication systems. Key focus areas include cryptographic algorithm implementation on microcontrollers and securing next-generation 6G networks. Recent publications reveal strong trends toward hybrid post-quantum cryptography solutions for resource-constrained IoT devices and 6G authentication systems. His research emphasizes practical security implementations in wireless communication protocols, with significant attention to LoRa-based systems and autonomous vehicle infrastructures. The work consistently bridges theoretical cryptography with real-world hardware constraints. Andersen supervises PhD student Turnip, T. N. (6G Authentication Protocol) and Master's student You, L. (Nature Assessment via Remote Sensing). His research is funded through projects like Machine Learning for Beehives Monitoring (2023-2026) and Jamming Against Critical Wireless Communication (2022-2023), with industry collaborations through InnoTech - TaskForce and F2D2: The Community for Dynamic Data. He is integral to DTU's Cybersecurity Labs and contributes to the Summer School in Cyber Security. His F2D2 project builds smart city cybersecurity frameworks through the Community for Dynamic Data initiative, addressing urban security challenges while advancing green transition technologies.

Christian Grinderslevمشاهده پروفایل

استادیار

• Wind Energy
• Computational Fluid Dynamics
• Wind Turbine Design
• +۳ مورد دیگر

Christian Grinderslev is an Assistant Professor at the Technical University of Denmark (DTU) within the Department of Wind and Energy Systems, specializing in aero- and fluid dynamics. His research focuses on rotor aerodynamics, fluid-structure interaction, and computational fluid dynamics (CFD) applied to wind turbine systems. He completed his PhD in 2021 under the project Fluid Structure Interaction for Wind Turbines in Atmospheric Flow , supervised by Niels N. Sørensen and others. Key research areas include vortex-induced vibrations (VIV) in wind turbine blades and rotors, aerodynamic modeling under non-uniform inflow conditions, and high-fidelity simulations of complex atmospheric flows. His work emphasizes validating computational models using field data and experimental validation. Grinderslev has contributed to international collaborations like IEA Wind TCP Task 29, advancing rotor aerodynamics and aeroelastic code comparisons. He is a core participant in the DigiWind project (2024–2027), aiming to develop digital solutions for wind energy systems. His publications span peer-reviewed journals and conferences, with a focus on advancing turbine design and performance under real-world flow conditions. Notable contributions include studies on VIV dynamics, CFD validation for MW-scale turbines, and fluid-structure interaction in complex flows. His research bridges theoretical models with practical applications, addressing challenges in turbine reliability and efficiency.

Lei Youمشاهده پروفایل

استادیار

• Mathematical Optimization
• Distributed Data Analytics
• Data-Driven Optimization
• +۹ مورد دیگر

Lei You is an Assistant Professor in Applied Mathematics at the Department of Engineering Technology, Technical University of Denmark (DTU), located in Ballerup, Denmark. With a Ph.D. in Computer Science specializing in Mathematical Optimization from Uppsala University (2019), Dr. You has established expertise in distributed data analytics, data-driven optimization, and machine learning interpretability. Dr. You's research focuses on the theories of interpretability and efficiency of machine learning models toward On-Device AI. Key areas of investigation include: Strategies to streamline complex models without performance loss Unraveling the intricate mechanisms of decision-making models Understanding the synergy between model simplification and explainability Distributed data analytics and federated learning systems Optimization techniques for wireless communication and edge computing Dr. You's recent publications demonstrate a strong focus on counterfactual explanations, optimal transport theory, neural network pruning, and multi-objective optimization for federated learning. The research spans applications from explainable AI to 6G-satellite systems and energy-efficient base station management. A notable trend is the integration of causal inference and distributional analysis in machine learning optimization problems, with significant contributions to federated learning efficiency and robustness. Scientific awards and recognition: Doctoral Dissertation Award for Operations Research in Telecommunications and Network Analytics awarded by INFORMS in 2020 Dr. You actively supervises student projects and research activities, with recent supervisions including work on remote sensing assessment, network pruning techniques, Microsoft Graph API optimization, and applications of large language models in business contexts. Current research projects include 'Machine Learning for Beehives Monitoring' and 'InnoTech - TaskForce,' focusing on practical applications of machine learning in environmental monitoring and digital transformation. Dr. You maintains active industry connections through previous roles at Bolt, Wolt (Doordash), and The Boston Consulting Group, ensuring research relevance to real-world challenges.

• Operations Research
• Transport Optimization
• Mathematical Optimization
• +۳ مورد دیگر

Jesper Larsen is a Professor and Head of the Management Science Division as well as Department Head of Education at the Department of Technology, Management and Economics (Technical University of Denmark). He holds a PhD in Operations Research from DTU (1999) and has been a faculty member since 2000. His roles include teaching Operations Research at undergraduate and graduate levels, supervising over 120 student projects, and leading initiatives like the BSc in Data Science and MSc in Business Analytics. Research interests focus on transport optimization and healthcare resource planning , with projects involving industry partners such as Danish State Railways and Novo Nordisk. He has authored over 50 publications and serves on editorial boards including OR Spectrum and TOP . Notably, he received the 2017 Hedorf Foundation Prize for transportation research. Educations: MSc Computer Science (University of Copenhagen, 1995), PhD Operations Research (DTU, 1999) Awards: 2017 Hedorf Foundation Prize Advising: Supervised over 10 PhD students and 120+ theses/projects Grants/Projects: Industry collaborations in transport (e.g., Deutsche Bahn) and healthcare (e.g., Rigshospitalet) He is actively involved in professional organizations such as the Executive Committee of EURO (European Association of OR Societies) and reviews for top journals and agencies globally.

Ming Chenمشاهده پروفایل

استاد

• Electrochemical Engineering
• Materials Science
• Renewable Energy Systems
• +۳ مورد دیگر

Ming Chen is a Professor at the Department of Energy Conversion and Storage at the Technical University of Denmark (DTU), specializing in solid state electrochemistry with a focus on electrochemical energy conversion and storage systems. His research emphasizes solid oxide electrolysis cells (SOECs), hydrogen production, and renewable energy integration. He leads multiple research projects on advanced materials, electrode design, and system durability. Key areas of research include solid oxide fuel cells (SOFCs), material degradation mechanisms, and scalable solutions for green hydrogen production. He has contributed to over 214 publications and holds leadership roles in projects involving PhD supervision and industrial collaborations. Notable recognition includes the Third Price EFC17 Best Paper Award (2017). Dr. Chen’s work addresses challenges in high-temperature electrochemical systems, corrosion-resistant materials, and operational strategies for energy storage. His lab focuses on nanostructured electrodes, trilayer cell designs, and mitigating degradation in SOECs under fluctuating conditions. He is actively involved in conferences and industry partnerships to advance clean energy technologies.

Morten Rieger Hannemoseمشاهده پروفایل

استادیار

• Computer Vision
• Medical Imaging
• 3D Reconstruction
• +۳ مورد دیگر

Morten Rieger Hannemose is an Assistant Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). His research focuses on computer vision, medical imaging, 3D reconstruction, and AI-driven healthcare solutions. He is actively involved in projects like 'Fighting Cancer with Generative AI' and 'Decision support AI for Skin Lesions,' supervising multiple PhD students in these domains. His work contributes to UN Sustainable Development Goals related to health and innovation. Research interests include neural networks, medical image analysis, and computational imaging. Notable achievements include developing methods for digitizing material appearances and estimating diagnostic difficulty in skin lesion diagnosis. He collaborates internationally on topics such as monocular 3D pose estimation and multimodal data fusion. Morten has supervised PhD students in areas like crowd counting through remote sensing, generative AI for cancer diagnostics, and diffusion models for image segmentation. His projects often bridge theory and application, such as creating the 'Sportspose' 3D sports pose dataset. His email is mohan@dtu.dk , and his website is mortenhannemose.github.io .