جست‌وجوی استاد و پژوهشگر

Charles Anthony Batesمشاهده پروفایل

دانشیار مدعو

• Hydraulics
• Hydraulic Motor Engineering
• Sustainable Design
• +۴ مورد دیگر

Charles Anthony Bates serves as an External Associate Professor at the Department of Sustainability and Planning within The Technical Faculty of IT and Design at Aalborg University in Copenhagen. With a unique blend of academic expertise and extensive industry experience, Bates bridges theoretical knowledge with practical application in sustainable engineering. His dual career path spans both academia and industry, where he currently holds leadership positions at Danfoss Power Solutions while contributing to academic research and teaching. Industrial PhD in Science & Technology Studies, Aalborg University (2017-2020) MA in Professional Communication, Roskilde University (2014-2016) BSc in Mechatronic Production Engineering, University of Southern Denmark (2002-2005) Bates' research focuses on the intersection of hydraulic engineering, sustainable technology development, and organizational practices in high-tech industries. His work particularly examines how technology readiness levels coordinate development processes, how objects stage referential alignment in industrial-academic collaborations, and how sustainable design principles can be integrated into hydraulic motor technology. His fingerprint analysis reveals strong expertise in Hydraulics Material Science (100%), Hydraulic Motor Engineering (60%), Surface Roughness (26%), and related engineering disciplines. An analysis of Bates' publications reveals a consistent focus on practical applications of theoretical frameworks in hydraulic engineering. His work demonstrates how Science & Technology Studies concepts can be applied to solve real-world engineering problems, particularly in the development of sustainable hydraulic systems. The publications show increasing emphasis on environmental and governance aspects (ESG) in recent years, aligning with global sustainability goals and industry demands for more responsible engineering practices. Bates has been actively involved in knowledge transfer between industry and academia through various speaking engagements, including keynote presentations on multidisciplinary collaboration in high-tech industry and panel discussions on sustainable energy systems. His professional trajectory demonstrates a strategic integration of academic research with industry leadership roles, particularly in his capacity as Strategic Initiatives Leader and ESG Lead for Work Function Division at Danfoss Power Solutions. Principal Speaker at Graduation Ceremony for Engineers, SDU Sønderborg (2026) Keynote Speaker: Challenges and Benefits of Multidisciplinary Collaboration in High-tech Industry (2020) Panelist: Sustainable Future Energy Systems - Skills for the energy transition (2018) Bates maintains active connections with multiple academic institutions, including membership in the University of Southern Denmark organization since 2021, demonstrating his commitment to fostering academic-industry collaboration. His current trajectory shows progression toward increasingly strategic leadership roles that integrate technical expertise with sustainability considerations, reflecting the growing importance of ESG factors in engineering leadership.

Peter Berringمشاهده پروفایل

پژوهشگر

• Wind Energy
• Structural Engineering
• Materials Science
• +۲ مورد دیگر

Peter Berring is a Senior Development Engineer at the Department of Wind and Energy Systems at Technical University of Denmark, specializing in structural design and testing of wind energy materials and components. His research focuses on wind turbine blade durability and structural integrity. Wind Energy Systems Structural Health Monitoring Composite Material Testing His work contributes to UN Sustainable Development Goals related to renewable energy and sustainable infrastructure. Key research areas include fatigue testing, delamination growth analysis, and advanced numerical modeling of wind turbine blades. Publications highlight collaborations with researchers like D. Tcherniak, S. K. Nielsen, and K. Branner. He has published extensively on topics such as virtual sensing for fatigue testing, thermography-acoustic emission monitoring, and spar cap debonding mechanics.

Franck René Jacques Bertagnolioمشاهده پروفایل

پژوهشگر

• Wind Turbine Engineering
• Trailing Edge Noise
• Airfoil Design
• +۷ مورد دیگر

Franck René Jacques Bertagnolio is a Senior Scientist at the Rotors Wind Turbine Design Division of the Technical University of Denmark (DTU Wind and Energy Systems). His work focuses on wind turbine aerodynamics, aeroacoustics, and noise reduction technologies, contributing to sustainable energy systems. Role: Researcher and supervisor in wind turbine noise and flow dynamics Projects: Involved in advanced aeroacoustic modeling, vortex-induced vibration studies, and low-noise wind farm control Research Interests: Bertagnolio specializes in trailing edge noise, airfoil design, hybrid computational aeroacoustic (CAA) methods, and high-fidelity turbulence modeling. His work bridges computational fluid dynamics (CFD) with practical wind turbine performance optimization. Scientific Contributions: Recent publications highlight his expertise in boundary element methods for noise prediction, vortex dynamics in wind turbine towers, and turbulence modeling for trailing edge noise reduction. These studies align with UN Sustainable Development Goals (SDGs) for clean energy and environmental protection. Supervision: He actively mentors PhD candidates like Pindi Nataraj and Ebstrup K., focusing on aerodynamic and aeroacoustic challenges in wind energy systems.

• Transportation Systems Modelling
• Machine Learning Applications
• Urban Mobility
• +۲ مورد دیگر

Guido Cantelmo is an Assistant Professor at the Technical University of Denmark (DTU) within the Department of Technology, Management and Economics, specifically in the Division of Transport's Section for Transport Systems Modelling. His research leverages big data analytics and machine learning to address complex transportation challenges, with expertise spanning traffic flow modeling, demand estimation, shared mobility systems, and urban network optimization. He maintains active collaboration with international cities including Copenhagen, Munich, and Tel Aviv-Yafo for empirical validation of his models. His research integrates computational techniques such as Graph Neural Networks, meta-learning, and physics-informed AI with transportation theory. Primary domains include: Dynamic traffic assignment using real-time data sources Machine learning for imbalanced mobility datasets Emission impact modeling of urban fleets Behavioral analysis of shared mobility adoption Large-scale simulation calibration frameworks Publication analysis (2022-2025) reveals dominant themes: data-driven demand estimation (37% of recent works), machine learning metamodeling (27%), shared mobility optimization (20%), and urban policy impact studies (16%). Methodological innovations include transfer learning for sparse data and multi-city validation approaches. No scientific awards or student mentoring relationships are documented in available sources. Similarly, no information exists regarding research grants, laboratory affiliations, or educational background.

Rune Dodensig Kjærsgaardمشاهده پروفایل

پژوهشگر

• Data Representation
• Machine Learning
• Neural Networks
• +۵ مورد دیگر

Rune Dodensig Kjærsgaard serves as a Consultant in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), with office location at Richard Petersens Plads, Building 324, 2800 Kgs. Lyngby. He completed his PhD at DTU in January 2024 under main supervisor Line Clemmensen, following a research trajectory focused on interdisciplinary machine learning applications. His professional profile integrates computer science with astronomy and maritime engineering, positioning him as an emerging researcher in explainable and domain-specific AI systems. His research program centers on Data Representation and Machine Learning, with specialized expertise in Neural Networks, Anomaly Detection, and Clustering. Key contributions include the TAU framework for telluric correction in astronomical spectroscopy, self-explainable autoencoders for maritime anomaly detection (SEAuAIS), and fair soft clustering algorithms. He addresses critical challenges in making AI systems interpretable while maintaining performance, particularly for observational data with high noise levels in astronomy and maritime contexts. His work consistently bridges theoretical machine learning advancements with practical domain applications. Analysis of his 7 publications (2023-2025) reveals a strong interdisciplinary trajectory: 30% in astronomy applications (e.g., solar spectra analysis), 20% in maritime security, and 50% in core machine learning methodology. Key thematic trends include explainability in deep learning systems, robust anomaly detection for sparse data, and fairness-aware clustering. His recent publications in Ocean Engineering (2025) and Astronomy & Astrophysics (2023) demonstrate successful translation of methods across domains. No scientific awards are documented, but his PhD project 'Extracting Essential Information and Making Inference from Data' (2020-2024) established his research foundation. Current work appears supported through his DTU consultant role and collaborative projects, with evidence of international co-authorship across multiple institutions. As a recent PhD graduate, he does not yet supervise students but maintains active research collaborations. Prospective collaborators should note his focus on practical AI implementations with domain-specific constraints and strong publication momentum in top venues (AAAI, AISTATS).

Siavash Khosh Sokhan Monfaredمشاهده پروفایل

پژوهشگر ارشد

• Granular Physics
• Statistical Mechanics
• Active Matter
• +۳ مورد دیگر

Siavash Khosh Sokhan Monfared is a Research Fellow at the Niels Bohr International Academy (NBIA), affiliated with the Niels Bohr Institute at the University of Copenhagen . His work bridges granular physics, statistical mechanics, and active matter, focusing on the physics of force transmission in biological systems. Education: PhD in Physics from the Massachusetts Institute of Technology (MIT) , followed by a postdoctoral position at California Institute of Technology (Caltech) . Monfared's research emphasizes collective self-organization in biological systems through theoretical models and high-performance computational tools . His recent publications highlight the role of stress chains in mechanical cell competition and their correlation during phase transitions in active monolayers. At the Niels Bohr Institute , he contributes to interdisciplinary studies in biophysics , exploring granular systems and computational approaches to understand cellular mechanics and force dynamics.

Jie Caiمشاهده پروفایل

استادیار

• Structural Engineering
• Pipeline Mechanics
• Maritime Engineering
• +۴ مورد دیگر

Jie Cai is an Assistant Professor at the Department of Technology and Innovation, University of Southern Denmark, specializing in structural engineering, maritime operations, and data science. His research bridges computational methods with marine and pipeline mechanics. Key research areas include structural stability, residual strength analysis, lateral buckling, and data-driven maritime systems Recent work focuses on medical image segmentation (2025) and burst strength prediction for corroded pipelines (2025) Active in digital twin development for vessel operations and engine monitoring He has contributed to journals like Computers and Electrical Engineering , Ocean Engineering , and Journal of Marine Science and Application , with expertise in finite element analysis and anomaly detection. Jie Cai serves as a peer reviewer for journals including the Journal of Offshore Mechanics and Arctic Engineering and Energies , and teaches courses in data science, programming, and IoT applications at the master's and bachelor's levels.

Christian T. Vejeمشاهده پروفایل

استاد

• Applied mathematical modeling
• Finite element models
• Numerical methods and simulation
• +۴ مورد دیگر

Christian T. Veje serves as Professor and Head of the Department of Mechanics and Electronics (IME) at the University of Southern Denmark, leading research in energy systems and computational modeling with 144 publications. His work bridges theoretical numerical methods and practical engineering solutions for sustainable energy applications across thermal engineering domains. Research interests prioritize applied mathematical modeling, finite element analysis, and numerical simulation techniques focused on energy systems optimization. Specific applications include phase change materials for thermal storage, district heating networks, lithium-ion battery systems, heat pump technology, and predictive control models for energy performance enhancement. His fingerprint analysis reveals strong connections to thermal engineering subfields like regenerators and energy renovation. Recent publications (2022-2024) demonstrate concentrated innovation in renewable energy integration, waste heat recovery, and AI-driven building management. Key trends include hybrid thermal storage systems using phase change materials, techno-economic optimization of island energy grids, and liquid cooling solutions for data centers. His work consistently applies computational fluid dynamics and predictive modeling to solve complex energy challenges. No scientific awards were documented in the source materials. Veje has supervised 3 PhD students and secured leadership roles in multiple research initiatives including the Digital Twin for building decision support (2021-2024), PROMA predictive maintenance project (2021-2024), and NeGeV ventilation research (2018-2021). His grants address energy optimization, predictive maintenance strategies, and advanced thermal management systems through industry-academic collaborations. While specific laboratory names aren't provided, Veje actively participates in multi-institutional teams including the EUROFusion BB RH facility project (2024-2026) and has contributed to editorial boards for Energies and Energy Informatics journals, demonstrating cross-disciplinary engagement in energy research communities.

• Quantum Chemistry
• Computational Chemistry
• Theoretical Chemistry
• +۲ مورد دیگر

Andreas Erbs Hillers-Bendtsen serves as a Researcher (Postdoc) in the Department of Chemistry at the University of Copenhagen, where he conducts advanced computational research in quantum chemical methodologies and materials design. His work bridges theoretical frameworks with practical applications in energy and atmospheric science. His research spans Quantum Chemistry, Computational Chemistry, and Materials Science, with specialized focus on cluster perturbation theory for excited states, isotopic fractionation dynamics, and molecular systems for solar energy storage. Recent work demonstrates expertise in developing scalable quantum chemistry algorithms and applying them to photochemical processes and novel carbon-based materials. Analysis of his 51 research outputs reveals a strong trajectory in methodological innovation, particularly in extending cluster perturbation theory frameworks and implementing parallel computing solutions. His publications show increasing interdisciplinary reach, connecting quantum chemistry with atmospheric science and renewable energy materials, evidenced by publications in high-impact journals including Science Advances and Journal of Chemical Physics . Dr. Hillers-Bendtsen maintains active collaborations with leading researchers including Kurt V. Mikkelsen, Mads B. Johansen, and Trygve Helgaker, with co-authorship spanning theoretical developments, experimental validation, and materials synthesis projects. His work has attracted attention across academic platforms including Mendeley and social media, indicating growing influence in computational chemistry circles.

• Planet Formation
• Protoplanetary Disks
• Streaming Instability
• +۳ مورد دیگر

Urs Dannenberg serves as a Guest Researcher at the Centre for Star and Planet Formation within the Globe Institute at the University of Copenhagen, specializing in computational modeling of planet formation processes in protoplanetary disks. Education: Postdoc, Globe Institute, University of Copenhagen (2020–present) Doctor in Physics, Hamburg Observatory, University of Hamburg (2017–2020) Master of Science in Physics, University of Hamburg (2015–2017) Bachelor of Science in Physics, University of Hamburg (2011–2015) Internship, Lund Observatory, Lund University (2015) Research Focus: Dannenberg investigates the streaming instability mechanism—critical for forming planetesimals (asteroid/Kuiper belt analogs) and generating disk turbulence—through advanced computer simulations. His work examines interactions between streaming instability and vertical shear instability to determine planetesimal formation thresholds under varying disk conditions, bridging theoretical astrophysics and high-performance computing. Publication Impact: His three Astronomy & Astrophysics papers (2017–2022) demonstrate growing influence, with the 2017 study on planetesimal mass functions accumulating 135 Scopus citations and subsequent work exploring instability coexistence gaining traction through social media mentions (5 X posts) and Wikipedia references. Collectively, these studies establish numerical frameworks for understanding early planetary system assembly. Scientific Recognition: No formal awards were documented, though citation metrics and external engagement (22 Mendeley readers for 2022 paper) indicate scholarly impact. Collaborative Context: Dannenberg operates within the Centre for Star and Planet Formation, maintaining active collaborations with Anders Johansen (University of Copenhagen), Rajibul Banerjee, and Chao-Chin Yang across German and Swedish institutions, leveraging international expertise in computational astrophysics.

Hajime Hiraseمشاهده پروفایل

استاد

• Neuroscience
• Astrocyte research
• Neural circuit dynamics
• +۶ مورد دیگر

Hajime Hirase is a Professor at the Center for Translational Neuromedicine within the Faculty of Health and Medical Sciences at the University of Copenhagen. His research focuses on astrocytic signaling and its impact on neural circuit dynamics and behavioral performance. His educational background is not explicitly stated in the provided text, but he leads the Hirase Lab: Division of Neuron-Glia Circuitry, which develops advanced tools for neuroscience research. Dr. Hirase's research interests span multiple areas of neuroscience with a particular emphasis on astrocyte function. His work explores how astrocytes influence neural circuits, cerebral blood flow, and behavioral outcomes. He has made significant contributions to understanding the glymphatic system, neuron-glia interactions, and the role of astrocytes in sleep physiology and emotional regulation. His laboratory has developed numerous genetic tools including fluorescent blood AAVs (pAAV-P3-Alb-mNG, pAAV-P3-Alb-mScarlet) and astrocyte markers/biosensors that are available through Addgene and viral vector cores worldwide. Analysis of his recent publications reveals a strong focus on the intersection of astrocyte biology, neural circuit dynamics, and neurovascular coupling. His work consistently demonstrates how astrocytic signaling mechanisms influence broader brain functions including sleep-wake cycles, anxiety regulation, and seizure control. The research employs cutting-edge imaging techniques and genetic tools to investigate these complex systems. Dr. Hirase maintains active collaborations with prominent researchers including Maiken Nedergaard, as evidenced by multiple co-authored publications in high-impact journals such as Cell, PNAS, and Cell Metabolism. His work has received significant attention in the scientific community with several papers accumulating substantial citations and media coverage. His laboratory has developed important research resources including fluorescent blood AAVs, CRISPR AAVs, and astrocyte biosensors that are widely shared with the neuroscience community through Addgene and viral vector facilities. These tools have enabled researchers worldwide to study neurovascular and astrocyte functions with greater precision.

• Food Science
• Food Analytics
• Biotechnology
• +۶ مورد دیگر

Birthe P Møller Jespersen is an Associate Professor and External Researcher in the Department of Food Science, specializing in Food Analytics and Biotechnology at the University of Copenhagen. Her research focuses on applying advanced analytical techniques to food science problems, particularly in cereal analysis and functional foods. Dr. Jespersen's research interests include: Food Analytics using hyperspectral imaging and near-infrared spectroscopy Barley and cereal analysis for food and brewing applications Functional foods development Application of machine learning and deep learning in food analysis Protein analysis in plant-based foods Food processing and quality assessment Her recent publications demonstrate a strong trend toward integrating advanced computational methods with traditional food analysis techniques. She has been actively working on applying hyperspectral imaging combined with machine learning algorithms to analyze grain quality, protein content, and food processing parameters. Her research bridges the gap between traditional food science and modern data science approaches. Dr. Jespersen has contributed to the scientific community through numerous publications and media appearances discussing food science topics. Her media contributions include discussions on converting animal feed to human food and the importance of grain fibers in healthy diets. Her professional activities include: Research in food analytics and biotechnology Development of analytical methods for food quality assessment Application of advanced imaging and spectroscopy techniques Integration of machine learning with food analysis

• Animal Welfare
• Disease Control
• Swine Production
• +۴ مورد دیگر

Leonardo Victor de Knegt serves as an Associate Professor in the Department of Veterinary and Animal Sciences at the Faculty of Health and Medical Sciences, University of Copenhagen. His research centers on animal welfare and disease control within livestock production systems, with particular expertise in swine nutrition, gastrointestinal health, and veterinary epidemiology. Dr. de Knegt's research program investigates critical challenges in modern livestock farming, including optimizing piglet development through dietary interventions (e.g., benzoic acid and lactose supplementation), mitigating stress in gestating sows, and enhancing disease surveillance in cattle populations. His work integrates molecular biology, nutritional science, and advanced statistical modeling to address complex interactions between feed composition, animal physiology, and production outcomes. Key methodologies include gene expression analysis, state space modeling for dairy herd management, and genomic contact-tracing for infectious disease control. Analysis of his 2020-2025 publications reveals a cohesive research trajectory focused on improving animal health through nutritional innovation and precision monitoring. Dominant themes include feed additive efficacy in neonatal piglets, risk factor identification for reproductive challenges in hyperprolific sows, and computational approaches to dairy farm management. His collaborative network spans multiple University of Copenhagen departments and international research teams, consistently targeting practical solutions for sustainable livestock production. Dr. de Knegt maintains an active publication record with 34 research outputs including 22 peer-reviewed journal articles. His work appears in high-impact journals such as Animals , Journal of Dairy Science , and Preventive Veterinary Medicine , demonstrating significant contributions to veterinary science methodology and livestock welfare applications.

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry
• +۲ مورد دیگر

Theo Juncker von Buchwald serves as a Guest Researcher in the Department of Chemistry at the University of Copenhagen, located at Universitetsparken 5 in Copenhagen Ø. His research focuses on advanced computational methods in quantum chemistry, particularly developing and implementing cluster perturbation theories for molecular excitation energies and ground-state properties. His primary research interests center on Computational and Theoretical Chemistry, specializing in electronic structure theory. He develops high-accuracy quantum chemical methods including coupled cluster theory, variational excitation-energy functions, and core-valence separation techniques. His work bridges theoretical chemistry with high-performance computing, implementing parallel algorithms for large-scale molecular systems. Analysis of his four recent publications reveals a consistent research trajectory in Cluster Perturbation Theory (CPT), with increasing computational sophistication. His work demonstrates expertise in both theoretical development (variational formulations, Lagrangian approaches) and practical implementation (parallelization, GPU acceleration). Key trends include targeting CCSD/CCSDT accuracy with reduced computational cost, developing diagnostics for model reliability, and extending CPT to core-excited states for X-ray spectroscopy applications. Research Collaborations and Infrastructure: Collaborates extensively with Kurt V. Mikkelsen, Poul Jørgensen, and Jeppe Olsen Utilizes Frontier supercomputer at Oak Ridge National Laboratory Employs hybrid MPI/OpenMP parallelization with GPU acceleration Receives funding from Danish Council for Independent Research (Grants DFF-0136-00081B, DFF-10.46540/3103-00261B)

• Planet Formation
• Numerical Simulations
• Comets
• +۲ مورد دیگر

Sebastian Herbert Lorek serves as an External Researcher and Academic employee at the Centre for Star and Planet Formation within the Globe Institute at the University of Copenhagen. He is a postdoctoral researcher in Anders Johansen's Planet Formation Group, focusing on computational astrophysics related to planetary system origins. His institutional base at Øster Voldgade 5-7, Copenhagen, supports his active research profile evidenced by multiple recent publications in high-impact journals. Dr. Lorek's research centers on numerical simulations of planet formation mechanisms, including gravitational collapse of pebble clouds, dynamics of planetesimal accretion, and formation pathways for Super-Earths in systems with cold giants. He investigates UV processing effects on icy pebbles in turbulent protoplanetary disks and develops computational methods for modeling planetesimal dynamics. His work bridges theoretical astrophysics and high-performance computing to address fundamental questions about planetary system evolution. Analysis of his 2020-2025 publications reveals consistent specialization in computational planet formation, with recurring themes in pebble accretion efficiency, disk-planet interactions, and turbulent disk dynamics. His research demonstrates methodological innovation in N-body simulations and hydrodynamical modeling, contributing to understanding diverse planetary architectures from early solar system evolution to exoplanet systems. No scientific awards were mentioned in the available information. Details regarding student advising or research grants were not provided in the source material. Dr. Lorek is an integral member of the Planet Formation Group at the Centre for Star and Planet Formation, collaborating with researchers including Anders Johansen, Michiel Lambrechts, and international co-authors. His work leverages advanced computational infrastructure to model complex astrophysical processes in protoplanetary environments.