جستجوی استاد راهنمای دانشگاهی

Kirsten Marie Ørnsbjerg Jensenمشاهده پروفایل

دانشیار

• Materials Chemistry
• X-ray and Neutron Scattering
• Nanomaterials Synthesis
• +۳ مورد دیگر

Kirsten Marie Ørnsbjerg Jensen is an Associate Professor at the Department of Chemistry, University of Copenhagen, affiliated with the Faculty of Science. Her research focuses on Materials Chemistry and X-ray/Neutron Scattering, aiming to develop 'materials by design' for applications in catalysis, solar cells, and energy technologies. PhD in Chemistry from Aarhus University (2013) Postdoctoral research at Columbia University (2013–2015) Research interests center on atomic structure-property relationships in nanomaterials, with recent work exploring: Synthesis of lanthanide hydroxides Electrocatalyst stability enhancements Solvent-guided nanoparticle growth Dynamic metal-organic frameworks High-entropy alloy formation Her 2024–2025 publications emphasize computational modeling, X-ray diffraction, and open-source tools for materials analysis. No scientific awards are explicitly mentioned in the provided text.

• Programming Languages
• Compilers
• Type Systems
• +۴ مورد دیگر

Nikolaj Hey Hinnerskov is a PhD Fellow in the Programming Languages and Theory of Computation (PLTC) section at the Department of Computer Science, University of Copenhagen. His research is embedded within DIKU's PLTC group, focusing on foundational and applied programming language systems. His core research spans: Programming Language Theory and Type Systems Compiler Design for Array-Based Languages Automatic Differentiation Techniques GPU-Accelerated Algorithm Development Rank-Polymorphic Function Inference Time Series Analysis Optimization Recent work demonstrates a strong convergence of programming language theory and high-performance computing, particularly in advancing compiler techniques for functional array languages like Futhark and optimizing scientific computations on GPUs. His publications address critical challenges in type inference, automatic differentiation, and parallel time-series decomposition. No scientific awards are documented in available sources. As a doctoral researcher, he operates under faculty supervision without independent advisees or grant leadership. His contributions align with DIKU's PLTC projects, including language design and performance optimization initiatives. He actively collaborates within the PLTC research ecosystem, contributing to GPU-based computational methods and programming language innovations alongside DIKU faculty and international researchers.

Antonio Ragoمشاهده پروفایل

مدرس

• Computational Science
• Lattice Gauge Theory
• Quantum Chromodynamics
• +۵ مورد دیگر

Antonio Rago is a Lecturer in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he contributes to computational science with a focus on lattice field theories and high-performance computing. His research bridges theoretical physics and advanced computational techniques. Research Interests: His work centers on lattice gauge theory , particularly SU(2) and QCD simulations using Wilson fermions. He specializes in GPU-accelerated algorithms and the HiRep framework for scaling simulations across thousands of GPUs. His interests also extend to fermion formulations, chiral symmetry, and numerical stability in lattice field theories. The recent publications show a strong trend toward scalable computational methods in fundamental physics, emphasizing GPU parallelism, algorithmic efficiency, and non-perturbative quantum field theory. His media contributions reflect growing engagement with science policy, particularly advocating for national AI and supercomputing infrastructure. Scientific Contributions: Active in advancing lattice QCD with novel fermion discretizations. Core developer in HiRep for distributed GPU simulations. Advocate for national investment in academic AI computing. Advising and Grants: While no formal students are listed, his research output suggests mentoring within collaborative projects. He participates in large-scale computational initiatives, likely supported by Danish or EU research grants, though specific funding sources are not disclosed in the text. Labs and Teams: Works within a computational physics group at SDU, collaborating with researchers across Europe on lattice field theory projects. His team leverages GPU clusters for large-scale simulations, focusing on algorithmic scalability and physical observables in gauge theories.

Emad Samuel Malki Ebeidمشاهده پروفایل

استاد

• Robotics
• Embedded Systems
• Smart Grids
• +۳ مورد دیگر

Emad Samuel Malki Ebeid is a Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark, specializing in robotics, drone technology, and power line inspection systems. His work bridges embedded systems, FPGA acceleration, and smart grid applications. PhD in Computer Science, University of Verona (2014) Postdoc in Electrical and Computer Engineering, Aarhus University (2016) Research interests focus on robotics , UAV autonomy , and power line inspection , with a strong emphasis on embedded systems and magnetic gripper design . Articles highlight trends in mmWave radar , GPU/FPGA acceleration , and drone swarm coordination for infrastructure maintenance. Scientific contributions include: IEEE Senior Member PI and Coordinator roles in EU Horizon Europe projects (Robots4Green, SPADE) Development of AERIAL-CORE and Drones4Safety frameworks Supervision of PhD students V. D. Hoang , N. H. Malle , and F. F. Nyboe Lab and team involvement spans the Aalborg Robotics 10-year seminar and special sessions at the Euromicro DSD conference. Media features include TV 2 News and 2200 News (2025) on drone-based power line maintenance.

• 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