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پژوهشگر
Luka Radic is a Researcher in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His work bridges theoretical and applied research in machine learning, with a focus on quantum machine learning , large language models , and fairness in AI systems.
دانشیار
Ken Pfeuffer is an Associate Professor in the Department of Computer Science at Aarhus University, affiliated with the Faculty of Science. His research focuses on Human-Computer Interaction (HCI) , particularly in Virtual Reality (VR) , Augmented Reality (AR) , and Extended Reality (XR) systems. He leads projects like the Interdisciplinary Center for Extended Reality (ICXR) and the XCB Lab , exploring multimodal interaction techniques, eye tracking, and user authentication in immersive environments. His work emphasizes gaze-based interaction , multimodal input fusion , and user interface design for AR/VR applications. Recent studies investigate consumer behavior in virtual retail environments and the integration of touch, gaze, and gesture inputs for natural user experiences. Pfeuffer collaborates on adaptive UI toolkits and practical methods for mobile eye-tracking systems, prioritizing real-world usability and accessibility. Key contributions include Depth3DSketch for VR sketching, PinchCatcher for multi-selection, and EyeGuide for gaze-assisted 3D sketching. His research bridges theoretical HCI principles with industry applications, addressing challenges in immersion , accuracy , and user safety in XR systems.
استادیار
Mads Røge Eldrup is an Assistant Professor at the Department of the Built Environment, Aalborg University, within the Faculty of Engineering and Science. His research focuses on coastal engineering, wave dynamics, and structural resilience of marine infrastructure. He leads the Ocean and Coastal Engineering Research Group and contributes to the BLUE – Marine & Maritime Research initiative. Research interests include breakwater stability, nonlinear wave modeling, physical model testing, and numerical simulation techniques. Key projects involve the RESCUER initiative (2024-2028) addressing resilient coastal solutions. He has authored/co-authored 46 publications since 2014, with recent work on NL-SORS wave decomposition, submerged bar dynamics, and rock armour stability. He actively participates in international conferences and workshops, including sessions on Smoothed Particle Hydrodynamics and nonlinear wavemaker theory. Collaborations span institutions globally, focusing on coastal resilience and hydraulic engineering challenges.
Per Lynggaard is a Professor of Electronics at the Technical University of Denmark (DTU) , leading the B.Eng. program in Electronics. Previously, he held an Associate Professor role at Aalborg University, combining academic excellence with a robust industrial career in technical-scientific research and development. Education: M.Sc. in Electrical Engineering and Information Technology (EE and IT) Ph.D. in Electronics from Aalborg University Research Interests: Focus on Integrated Circuit Design, Wireless Sensor Networks (WSN), Machine Learning, IoT, and Smart City Technologies . His work emphasizes energy-efficient systems, cybersecurity in IoT, AI-driven interference mitigation, and sustainable energy harvesting solutions. He has contributed to UN Sustainable Development Goals through projects addressing smart infrastructure and environmental monitoring. Projects & Collaborations: Leads and participates in EU-funded initiatives such as InnoTech (2023–2025) for green transition solutions and TransportTech (2023–2026) for Industry 4.0 logistics. Active in cybersecurity research via projects like Jamming Against Critical Wireless Communication , aiming to protect critical infrastructure. Awards: Recognized with multiple honors and rewards during his industrial career, though specific names are not listed. His work has been cited widely, with notable impact in IoT security and energy-efficient systems. Advising & Grants: Supervises Turnip T.N. in a PhD project on 6G security protocols. Engaged in securing funding for projects like F2D2: The Community for Dynamic Data (2021–2030), focusing on dynamic data systems and cybersecurity. Labs & Teams: Collaborates in interdisciplinary teams such as the InnoTech TaskForce and F2D2 Community , advancing IoT and AI integration. His research bridges academia and industry, with outputs spanning smart cities, healthcare IoT, and sustainable energy systems.
Chris Valentin Nielsen is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on metal forming, joining processes, and tribology, with expertise in formability, tool development, and numerical modeling. His work contributes to UN Sustainable Development Goals related to sustainable manufacturing. He supervises PhD students in projects such as sustainable busbars for electric vehicles and adjustable tool design for high-volume production. His research interests include metal forming (e.g., deep drawing, ironing), joining technologies (resistance welding, laser welding), and advanced manufacturing methods like additive manufacturing. He employs finite element modeling and experimental analysis to bridge fundamental and applied research. Collaborations span global institutions, addressing challenges in material behavior, process optimization, and tool durability. Recent publications explore topics such as dieless Nakajima testing for additive materials, punch design improvements, and asperity deformation mechanics. His work emphasizes sustainability, robust production systems, and eco-friendly lubrication solutions. Projects involve interdisciplinary teams, integrating numerical simulations with industrial applications to enhance manufacturing efficiency and material performance.
استادیار
Mark Bo Jensen is an Assistant Professor (Tenure track) at the Department of Engineering Technology and Didactics, Energy Technology and Computer Science at the Technical University of Denmark (DTU). His work bridges engineering and cognitive sciences through the emerging field of Perception Engineering. His research focuses on Extended Reality (XR) and Virtual Reality (VR) technologies to model and understand human perception and cognition. With over 10 years of expertise in real-time computer graphics, he develops immersive systems for applications in data visualization, medical testing, and geometric morphometrics. His recent publications highlight a strong trend in leveraging VR for precise human interaction tasks, such as anatomical landmark annotation and visual field testing, as well as advancing rendering techniques using diffusion models and mesh optimization. This reflects a multidisciplinary approach combining computer science, perception, and real-world applications. He has contributed to multiple research projects, including AL-EYE: The Visual Aid and Virtual Reality-Based Visualization of Geometric Data, where he served both as a PhD student and a project participant. These projects emphasize VR-based tools for data understanding and visualization. Assistant Professor (Tenure track), DTU PhD in Virtual Reality-Based Visualization of Geometric Data, completed June 2023 Project participant in AL-EYE: The Visual Aid (2025) While no formal advisees are listed, his role as a faculty member suggests future student supervision. He has collaborated extensively with researchers such as Jeppe R. Frisvad, Jakob Andreas Bærentzen, and Vedrana A. Dahl.
Andreas Bjerre-Nielsen is an Associate Professor at the Department of Economics and Copenhagen Center for Social Data Science (SODAS) within the Faculty of Social Sciences at the University of Copenhagen. His work bridges economics and data science to analyze education-related behavior and policies. Research Focus: School choice, digital technology in education, predictive analytics for interventions, and social network effects. Methodology: Combines econometrics with machine learning techniques to evaluate policy impacts. Research Trends: Recent publications emphasize algorithmic fairness in college admissions, socioeconomic impacts of school boundary policies, and behavioral insights from large-scale datasets. His 2025 Scientific Reports study reveals nation-scale social network dynamics. Awards and Grants: Tietgen Prize (2021) for young social science researchers 2024: Independent Research Fund Denmark grant for 'Coded Clues' project 2023: Major grant for school choice research Collaborations: Works with Danish Ministry of Children and Education through UDDanKvant unit, and collaborates with multidisciplinary researchers including Sune Lehmann and David Dreyer Lassen.
Peter Bach Andersen serves as Head of Section and Senior Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU). Based at Elektrovej 329A in Kgs. Lyngby, he leads research in electric vehicle integration and prosumer energy systems with an ORCID identifier 0000-0002-5202-3584. His work spans grid services, battery storage, and smart charging infrastructure within DTU's EV Lab ( www.evlab.dk ). Andersen's research focuses on electric vehicle grid integration , specializing in charging infrastructure planning, battery energy storage systems, and virtual power plant concepts. His fingerprint analysis reveals dominant expertise in Electric Vehicle Engineering (100%), Battery Engineering (13%), Ancillaries (12%), and Power Engineering (11%). Current projects emphasize flexibility quantification, grid service delivery through EV clusters, and Nordic grid characteristics. His work contributes significantly to UN Sustainable Development Goals related to clean energy and sustainable cities. His publication portfolio shows strong trends toward grid-interactive EV systems with recent emphasis on conditional connection agreements, fast-charging urban impacts, and data-driven battery health prognosis. The research demonstrates increasing focus on practical implementation challenges and market integration aspects of vehicle-grid systems. Andersen actively supervises four PhD students (Menchaca, Striani, Unterluggauer, Sevdari) across projects including charging infrastructure planning, EV clustering methods, and urban charging infrastructure impacts. He leads the FLOW project (2022-2026) investigating flexible energy systems for optimal EV integration while participating in multiple EU-funded initiatives. His research group maintains strong industry connections through DTU's EV Lab, focusing on real-world validation of grid services using commercial EVs and chargers.
Krist V. Gernaey is Professor in Industrial Fermentation Technology at the Technical University of Denmark's Department of Chemical and Biochemical Engineering. His research develops computational tools for bioprocess optimization across pharmaceutical, food, and chemical sectors. Research specializes in mechanistic modeling of fermentation processes, process analytical technology (PAT) implementation, and continuous production system design. Current investigations focus on uncertainty analysis methods, data-driven modeling, and novel bioreactor characterization from micro to production scale. Publications demonstrate applications in vaccine manufacturing, wastewater treatment, chromatography simulation, and sustainable chemical engineering. Recent work advances regulatory frameworks for in silico bioprocess models and AI integration in engineering education. Research collaborations span academic institutions and industry partners across Europe. Professional activities include conference organization and editorial responsibilities for chemical engineering journals.
Mauricio Bustamante is an Assistant Professor at the Niels Bohr Institute , University of Copenhagen, specializing in theoretical high-energy astrophysics, astroparticle physics, and neutrino phenomenology. His research bridges cosmic phenomena with fundamental particle physics, focusing on ultra-high-energy neutrinos, cosmic rays, gamma-ray bursts, and new physics beyond the Standard Model. PhD in Physics (2012-2014) M.Sc. in Physics (2007-2010) B.Sc. in Physics (2001-2006) His work explores neutrino oscillations, self-interactions, and decay in extreme astrophysical environments. He contributes to major international collaborations like GRAND (Giant Radio Array for Neutrino Detection) and IceCube-Gen2, developing simulation pipelines and forecasting detection methods for EeV-scale neutrinos. Recent publications highlight energy-dependent flavor transitions, Lorentz invariance testing, and constraints on long-range neutrino interactions via DUNE and T2HK experiments. He actively participates in peer review for journals such as Physical Review D , Physical Review Letters , and Astrophysical Journal , and has attended conferences like TeV Particle Astrophysics (2017). His research emphasizes detector design, cosmic ray reconstruction via graph neural networks, and multi-messenger astronomy.
François Raymond J Cornet is a Postdoctoral Researcher in the Department of Energy Conversion and Storage and a PhD Student in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His dual affiliation bridges energy conversion research and computational science, focusing on AI-driven molecular design. His research spans Organometallic Chemistry , Computational Chemistry , and Machine Learning , with specialization in catalyst design through diffusion models and inverse design methodologies. Key areas include metallocene chemistry, density functional theory applications, and generative modeling for chemical space exploration, targeting organometallic complexes like Vaska's complex. Cornet's publication trajectory reveals a concentrated effort in advancing equivariant diffusion models for molecular generation, particularly addressing small-data challenges in catalyst design. His work consistently integrates quantum chemistry with deep generative architectures, establishing new paradigms for inverse-design pipelines in computational chemistry. No scientific awards were documented in the source material. He recently completed the PhD project Machine learning for electronic scale inverse design of enzymatic catalysts (2021-2025) under supervisors M. N. Schmidt (primary), A. Bhowmik, and O. Winther, with examiners W. K. Boomsma and S. Olsson. Collaborators include P. Deshmukh, B. Benediktsson, and C. A. Naesseth across multiple publications. Research operations occur within DTU's interdisciplinary framework connecting the Department of Energy Conversion and Storage and Department of Applied Mathematics and Computer Science, leveraging computational infrastructure for molecular simulations and AI model training.
پژوهشگر ارشد
Sophia Natasha Wilson is a Research Fellow in the Department of Computer Science (DIKU) at the University of Copenhagen, specializing in machine learning applications across interdisciplinary domains. She is affiliated with the SCIENCE AI Centre and holds a cross-departmental position at the Niels Bohr Institute . Her research bridges theoretical machine learning with practical implementations in healthcare, quantum computing, and environmental sustainability. University of Copenhagen Department of Computer Science (DIKU) Niels Bohr Institute SCIENCE AI Centre Her research focuses include: Quantum-enhanced machine learning algorithms Explainable AI for healthcare applications Environmental sustainability in computing Emotion-aware language models Quantum computing hardware optimization Public health risk modeling Her recent publications demonstrate cross-disciplinary work in quantum machine learning (hybrid optical processors, qubit stabilization), health informatics (hypothyroidism analysis, nursing values evaluation), and ethical AI (sustainable AI, fairness in recommender systems). Technical work also appears in non-Euclidean generative models and real-time adaptive systems . Current projects include quantum dot array simulation (QDarts platform) and federated learning for personalized medicine . She contributes to the TreeSense center for remote sensing of global tree resources and works on climate-aware AI frameworks.
Asmus Skar Christiansen is an Associate Professor in Pavement Engineering at the Department of Environmental and Resource Engineering, Technical University of Denmark (DTU Sustain). He serves as Head of Study for the Nordic Master in Cold Climate Engineering programme and lectures on pavement engineering, Arctic road construction, and foundation design. His academic career at DTU spans from Postdoc researcher (2017-2019) to Assistant Professor (2020-2023) and current Associate Professor position since 2023. His research centers on pavement technology and geotechnics with specialization in: Development of advanced testing and modeling techniques for pavements Integration of modern sensing technologies in civil infrastructure Computational mechanics for soil-structure interaction Sustainable materials for cold climate engineering Recent work demonstrates a clear shift toward IoT-enabled monitoring systems and data-driven pavement assessment, with 80% of 2023-2025 publications focusing on sensor integration and machine learning applications. Notable scientific contributions include: Creation of open-source datasets (LiRA-CD, RIVA) for road condition modeling Development of thermomechanical models for heated pavements Innovations in waste soil reuse for infrastructure He actively supervises PhD candidates across multiple projects including GREENPIPE (self-sensing pipe systems) and urban pavement analysis, while maintaining industry consultancy through COWI A/S collaborations. Christiansen also contributes to sustainable infrastructure through DTU's alignment with UN SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities).
استادیار
Michael Sandberg is a Tenure Track Assistant Professor at the Department of Mechanical and Production Engineering Design and Manufacturing, Aarhus University (AU Engineering). His research bridges mechanical engineering and sustainable manufacturing technologies. Primary Affiliation: Aarhus University Department: Mechanical and Production Engineering Design and Manufacturing His work focuses on: Additive Manufacturing: Optimizing fiber orientation and process-induced stresses in 3D printing. Composite Materials: Studying compaction in pultrusion processes. Digital Twins: Advancing modeling techniques for industrial applications. Sustainable Design: Developing life-cycle engineering simulations for circular economy practices. Key trends in his publications include: Integration of digital twin platforms with industrial processes. Advancements in thermoset composite manufacturing. Innovations in large-scale additive manufacturing. Contact: ms@mpe.au.dk
Joe Alexandersen is an Associate Professor in the Department of Mechanical Engineering at the University of Southern Denmark (SDU), affiliated with the Institute of Mechanical and Electrical Engineering. His research spans structural optimization, heat transfer, fluid dynamics, and high-performance computing, with applications in heat sink design, microfluidic devices, and additive manufacturing. Research Interests Topology and shape optimization Conjugate heat transfer Navier-Stokes flow modeling Finite element methods High-performance computing Scientific Awards 2022 Fluids 2020 Best Paper Award 2017 DTU Young Researcher Award 2015 ISSMO/Springer Prize for Young Scientist Key Projects HiHeaT: Topology optimization for high heat flux components (2024–2027) Structural Analysis of Large Modular Vessels (2025–2027)
