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Karsten Wedel JacobsenView profile

Professor

• Theoretical solid-state physics
• Computational materials design
• Electronic structure methods
• +3 more

Karsten Wedel Jacobsen is a Professor in the Department of Physics at the Technical University of Denmark (DTU), specializing in theoretical solid-state physics and computational materials design. His work focuses on quantum mechanical calculations for material design at the atomic scale, with applications in nanotechnology and energy-related materials. He has led major research centers like the Center for Atomic-scale Materials Design (CAMD) and contributed to open-source software like GPAW. He holds academic leadership roles, including directing CAMD and serving on DTU's educational committees. Education: PhD in Theoretical Physics (University of Copenhagen, 1987), M.Sc. in Physics (University of Copenhagen, 1984). Research Interests : Theoretical nanoscale physics, electronic structure methods, molecular electronics, and computational materials discovery. His research bridges quantum mechanics and practical applications, such as solar energy materials and catalyst design. Publications & Trends : Over 218 publications, with recent work emphasizing machine learning in materials design, high-throughput screening for 2D materials, and computational studies of catalytic interfaces. Key themes include atomic-scale simulations, defect engineering, and energy-related material discovery. Scientific Honors : Elected Member of The Danish Academy of Natural Sciences (DNA) (1994) Elected Member of Danish Academy of Technical Sciences (ATV) (2001) Reinholdt W. Jorch's Award (2004) Advising & Grants : Supervised 25 PhD students, including current advisees working on electrosynthesis, electrocatalysis, and machine learning in quantum materials. Active in research funding through grants like the Danish Research Councils and the Lundbeck Foundation. Leads interdisciplinary projects on computational modeling and open-source software development. Labs & Teams : Director of CAMD (2010–2012), a hub for atomic-scale materials design research. Collaborates globally through networks like CAMP and MIKA Advisory Board, advancing theoretical and computational methods in materials science.

Sebastian Alexander MödersheimView profile

Associate Professor

• Security Protocols
• Protocol Verification
• Privacy in Cybersecurity
• +3 more

Sebastian Alexander Mödersheim is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). He specializes in security protocols, formal verification, and privacy-preserving technologies. His research focuses on developing automated methods for analyzing and ensuring the security and privacy of cryptographic protocols, including topics such as privacy properties, protocol compositionality, and accountability mechanisms. His work contributes to UN Sustainable Development Goals by addressing privacy and security challenges in digital systems. Key research areas include formal methods for protocol verification, privacy models like Alpha-Beta Privacy, and secure authentication mechanisms. Mödersheim has authored over 59 publications, including peer-reviewed articles in prestigious conferences such as IEEE Computer Security Foundations Symposium (CSF) and journals like ACM Transactions on Privacy and Security. His recent work emphasizes privacy in authentication protocols, stateful protocol composition, and automated verification tools using theorem provers like Isabelle/HOL. He supervises PhD students in projects such as secure cloud-edge computing (TaRDIS), logical approaches to privacy, and formalization of security protocols. His contributions also extend to tools like AVISPA and AIF framework for protocol analysis.

Torben Elgaard JensenView profile

Professor

• Science & Technology Studies (STS)
• Cybersecurity
• Digitization
• +5 more

Torben Elgaard Jensen is a Professor at Aalborg University’s Department of Culture and Learning, affiliated with The Faculty of Social Sciences and Humanities. He leads the Techno-Anthropology Research Group and co-leads the MASSHINE initiative. His research focuses on innovation, knowledge construction, and user involvement across sectors, with recent emphasis on digitization, cybersecurity, and AI ethics. He has conducted ethnographic studies in engineering firms, startups, public organizations, and research groups. Key Research Areas: Science & Technology Studies (STS), Cybersecurity in SMEs, Digital Transformation, Ethnography, User-Centered Innovation Labs/Initiatives: Techno-Anthropology Lab, AI for the People, MASSHINE Notable Projects: 'Emergency AI' (2025–2026), 'Digitization of Everyday Life during the Covid-19 pandemic in Denmark' (ongoing since 2020), and 'Generative Ethnographic AI' (2023) His work bridges theoretical STS frameworks with empirical studies, emphasizing methodologies like the Slalom Method (blending digital and traditional ethnographic tools). He has received awards including the 2020 Ziman Award (for TANTlab) and the 2016 Freeman Award. His research outputs span journals, books, and policy-relevant reports, addressing topics such as algorithmic governance, cybersecurity dilemmas in SMEs, and participatory design strategies. Public engagement includes media commentary on AI ethics, cybersecurity, and digital societal impacts, as well as contributions to conferences and workshops on critical proximity in digital humanities.

Mohammad BokaeiView profile

Research Fellow

• Wireless Communications
• Deep Learning
• Speech Processing
• +3 more

Mohammad Bokaei is a PhD Fellow at the Department of Electronic Systems within The Technical Faculty of IT and Design at Aalborg University, Denmark. His research integrates deep learning with wireless communication systems, focusing on speech transmission under channel constraints. His core research interests include: Wireless Communications: Channel modeling and adaptive transmission techniques Deep Learning: Neural network applications for communication systems Speech Processing: Real-time transmission and enhancement algorithms Signal Processing: Theoretical frameworks for low-latency systems Joint Source-Channel Coding: End-to-end optimization approaches Matrix Completion: Low-rank recovery for harmonic signal analysis Analysis of his 2024 publications reveals concentrated innovation in deep learning-driven wireless speech systems. Key trends include channel-configurable architectures, Gaussian channel optimization, and latency-constrained joint transmission-enhancement frameworks. His work bridges theoretical signal processing with practical wireless applications, particularly for assistive communication devices. No scientific awards were documented in the source material. Details regarding student supervision or research grants were not provided in the available information. No specific laboratory affiliations or research teams were referenced in the scraped content.

• Microgrids
• Photovoltaic Systems
• Power Electronics
• +8 more

Abderezak Lashab is an Assistant Professor at Aalborg University's Department of Electric Power Systems and Microgrids within the Faculty of Engineering and Science. He specializes in microgrid technologies, photovoltaic systems, and power electronics. His research focuses on enhancing the stability, efficiency, and resilience of energy systems, particularly in renewable energy integration, smart grids, and electric vehicle infrastructure. Key projects include the HECATE initiative exploring hybrid electric regional aircraft distribution technologies. Affiliations: AAU Energy, Microgrids Research Group Research Interests: Microgrid control strategies, photovoltaic system optimization, battery storage solutions, and cybersecurity in energy networks. His work emphasizes practical applications such as disaster-resilient mobile microgrids and EV charging infrastructure sustainability. Publications (82+): Focus on advanced control algorithms, power electronics, and renewable energy systems. Recent trends highlight grid stability under high PV penetration and smart grid resilience. Grants: HECATE project (2023-2025) funded by Horizon JU Innovation Action Labs/Teams: Active contributor to AAU's energy research groups, collaborating on projects involving hybrid electric systems and IoT-enabled cybersecurity.

Sanjay ChaudharyView profile

Associate Professor

• Wind Power Systems
• HVDC Grids
• Microgrid Clusters
• +7 more

Sanjay Chaudhary is an Associate Professor at Aalborg University's Faculty of Engineering and Science, part of the AAU Energy research group. His work focuses on advanced power systems, including wind energy integration, HVDC grids, and microgrid stability. He leads or participates in major projects such as SUSTENANCE (EU-funded) and REMCE (Danida-funded), addressing renewable energy challenges in Denmark and Ethiopia. His research emphasizes grid-forming inverter control, EV grid interaction, and harmonic stability in multi-vendor wind farms. Research Interests: Wind Power Systems & Offshore Grids Inverter-Based Resource Stability Microgrid Clustering and Optimization Rural Electrification Solutions Electric Vehicle Charging Infrastructure Harmonic Mitigation in Power Systems Recent work highlights include: 2025: Published 6 key papers on EV grid challenges, microgrid optimization, and HVDC stability 2024: Led Ethiopian minigrid cluster research and developed droop control algorithms for EVs Grants & Collaborations: Principal Investigator for HVDC Green (2021-2025) connecting Indonesian islands Co-PI for SUSTENANCE (2021-2024) advancing carbon-neutral communities Active in CIGRE JWG C6/B4.37 standards development Labs/Teams: Core member of AAU Energy and contributor to BLUE – Marine & Maritime Research initiatives.

Rolf HvidtfeldtView profile

Associate Professor

• Interdisciplinary Science
• Science Communication
• Research Impact Strategies
• +3 more

Rolf Hvidtfeldt is an Associate Professor at Aalborg University’s Department of Communication and Psychology, part of the Faculty of Social Sciences and Humanities. He co-leads the Humanomics Research Group and co-directs the FRONTIER Center for Advanced SSH. With a PhD, MA, and BA in philosophy, his research focuses on interdisciplinary science, research impact strategies, and AI ethics. He advises large-scale interdisciplinary projects in fields like biology, computer science, and policy-making. His current AI projects include 'Algorithms, Data, and Democracy' and 'Responsible AI for Value Creation.' Education: PhD, MA, and BA in Philosophy, specializing in philosophy of science and interdisciplinary studies. Research Interests - Interdisciplinary collaboration and epistemic integration - Societal impact of research - AI ethics and policy - Hybrid modeling in science - Knowledge transfer across disciplines - Micro-impact assessment frameworks Grants & Projects Responsible AI for Value Creation (Grundfos Foundation, 2023–2027) Algorithms, Data, and Democracy (Velux Foundations, 2020–2021) Mapping Knowledge Dissemination in SSH (2016–2021) Awards : None explicitly listed, but recognized for contributions to interdisciplinary research frameworks. Teaching & Advising Leadership in interdisciplinary research training Advisory roles for funding agencies and public organizations Labs/Teams : Humanomics Research Group, AI for the People Centre, FRONTIER Center.

Lars BodumView profile

Associate Professor

• Geoinformatics
• Urban Sustainability
• 3D Geovisualization
• +5 more

Lars Bodum is an Associate Professor at the Department of Sustainability and Planning, part of The Technical Faculty of IT and Design at Aalborg University. His research focuses on geoinformation, urban development, and digital technologies, particularly 3D modeling, AI, and geovisualization for sustainable cities. He co-authored Denmark’s foundational GIS textbook and leads projects like the award-winning The Digital Underground , exploring subsurface infrastructure data. Education: PhD in Urban Planning (2000) and MSc in Chartered Surveyor (1990), both from Aalborg University’s Department of Sustainability and Planning. Research interests include data integration, Citizen Science, and Digital Twins. His work bridges academia with municipal and private sector applications, emphasizing practical solutions for infrastructure management and climate adaptation. Key projects include Effektiv anvendelse af 3D-scanninger (2024–2026) and NBRACER (2023–2027), focusing on climate resilience and nature-based solutions. He has received the 2021 Outstanding Review Award for peer review contributions. Labs/Teams: Danish Centre for Spatial Planning and the Centre for 3D GeoInformation. Collaborations span Denmark and international partners like the University of California, Davis.

Erik LundView profile

Professor

• Structural Optimization
• Finite Element Method
• Wind Turbine Design
• +7 more

Erik Lund is a Professor in the Department of Materials and Production at the Faculty of Engineering and Science, Aalborg University, Denmark. His work centers on computational mechanics and structural optimization, particularly in the context of wind turbine blade design and composite materials. PhD in Mechanical Engineering, Aalborg University (1994) His research focuses on Finite Element Method , Design Sensitivity Analysis , Structural and Topology Optimization , and Material Optimization for engineering systems. He has made significant contributions to the optimization of laminated composite structures and wind turbine components, integrating manufacturing constraints and fatigue considerations into design frameworks. Recent publications (2023–2025) highlight a strong trend in multi-material optimization , open-source modeling of offshore wind blades, and stress-constrained topology optimization . His work bridges theoretical mechanics and industrial applications, especially in renewable energy. He also explores methods for generating manufacturing instructions directly from structural designs, enhancing design-to-production workflows. Årets underviser på AAU Engineering (2020) Lund has supervised multiple PhD students (7 indicated in supervision metrics) and secured significant research grants, including projects like Future Core Materials for Wind Turbine Blades . He is active in research networks and has contributed to professional societies such as the International Society for Structural and Multidisciplinary Optimization (ISSMO) and the Danish National Committee of IUTAM. His work is highly collaborative, involving both academic and industrial partners. He leads and participates in advanced research projects that integrate computational modeling with real-world engineering challenges, particularly in sustainable energy systems. His lab or research group appears to focus on solid and computational mechanics, with an emphasis on applying numerical methods to optimize structural performance under complex constraints.

Laura d'AndreaView profile

Research Fellow

• Organic Chemistry
• Medicinal Chemistry
• Pharmacology
• +3 more

Laura d'Andrea serves as a Research Fellow in Aalborg University's Department of Chemistry and Bioscience within the Faculty of Engineering and Science, specializing in the Section of Applied Supramolecular Chemistry. Her research bridges organic synthesis and pharmacological applications through innovative chemical methodologies. Education: PhD in Chemistry, Aalborg University, 2023 (Thesis: Design and synthesis of beta-Arrestin-biased 5HT2AR agonists) Her primary research focuses on developing sustainable synthetic routes for bioactive compounds, with expertise in nitrostyrene reductions to phenethylamines and palladium-catalyzed cross-coupling reactions. She integrates computational approaches to optimize molecular design for receptor-specific pharmacological activity, particularly targeting 5-HT2A serotonin receptors. Analysis of her recent publications reveals consistent advancement in green chemistry techniques, including catalyst recycling systems and one-pot syntheses that minimize waste while producing neuropharmacologically relevant compounds. Her work demonstrates strong translational potential for pharmaceutical development. Dr. d'Andrea contributes to the active research project "Designing Molecules for Ease of Chemical Synthesis" (2023-2025) as a key participant, applying machine learning algorithms to predict synthetic accessibility of novel compounds under Principal Investigator Christian Steinmann.

Søren HøjsgaardView profile

Associate Professor

• Statistics
• Graphical Models
• Bayesian Networks
• +7 more

Søren Højsgaard is an Associate Professor in the Department of Mathematical Sciences at Aalborg University, Faculty of Engineering and Science. His work bridges statistical theory, computational methods, and pedagogical innovation, with a strong focus on graphical models, Bayesian networks, and computer algebra systems in R. His research interests lie at the intersection of statistics, machine learning, and software development. He is particularly known for developing R packages such as caracas , gRbase , and sparta , which facilitate symbolic computation and efficient inference in probabilistic models. His work supports both advanced research and accessible teaching in data science. The recent publications highlight a consistent trend toward integrating symbolic mathematics with statistical computing, improving scalability in Bayesian network predictions, and enhancing statistics education through tools like Quarto and R. His contributions span theoretical algorithms, software implementation, and educational applications. Active contributor to open-source statistical software Focus on model-based prediction and symbolic computation Emphasis on teaching innovation using computational tools He has been involved in academic outreach through conference presentations and media engagement, discussing topics ranging from R programming to workplace safety modeling. His leadership role in the Department of Mathematical Sciences was recently highlighted in university communications. Søren Højsgaard leads and contributes to projects that combine rigorous statistical methodology with practical implementation, supporting both research and education in modern data science.

Kirsten Mølgaard NielsenView profile

Associate Professor

• Control Systems
• Automation
• Renewable Energy
• +8 more

Kirsten Mølgaard Nielsen is an Associate Professor in the Department of Electronic Systems at Aalborg University, under The Technical Faculty of IT and Design. She is affiliated with the Automation & Control Green Lab, focusing on sustainable automation and control systems for energy and environmental applications. University: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Automation & Control Green Lab Email: kmn@es.aau.dk Phone: +4599408761 ORCID: https://orcid.org/0000-0002-2552-1764 Her research interests include control systems, automation, renewable energy (particularly wave and wind), digital hydraulics, smart grids, and wastewater treatment. She has contributed extensively to projects involving energy storage, process control, and sustainable engineering solutions. Her recent publications (2018–2022) demonstrate a strong trend in environmental and energy control systems, particularly in wastewater treatment plant optimization, sewer flow management, and refrigeration system control. These works highlight her expertise in applying advanced control strategies to real-world engineering challenges. She has participated in multiple research projects such as 'Digital Hydraulic Power Take Off for Wave Energy', 'IFIV: Intelligent Remote Control of Individual Heat Pumps', and 'Plug and Play Process Control (P³C)', showcasing her collaborative and interdisciplinary approach. Kirsten Mølgaard Nielsen has not received any explicitly mentioned scientific awards in the provided texts. There is no indication of student advising or grants, though her role in major research projects suggests leadership and mentorship within her team. She is actively involved in research and development within the Automation & Control Green Lab, contributing to advancements in sustainable energy and environmental control technologies.

• Coding Theory
• Algebraic Geometry Codes
• Finite Fields
• +7 more

Hans Olav Geil is a Professor and Pro-dean at the Faculty of Engineering and Science , Aalborg University , Denmark, affiliated with the Department of Mathematical Sciences . He is actively engaged in research, academic leadership, and educational innovation, particularly in coding theory and engineering education. University: Aalborg University School: Faculty of Engineering and Science Department: Department of Mathematical Sciences Email: prodekan-eng-udd@aau.dk ORCID: 0000-0002-9666-3399 Website: http://people.math.aau.dk/~olav Geil's research centers on algebraic coding theory , with significant contributions to affine variety codes , quantum codes , network coding , and finite fields . His work bridges theoretical mathematics and practical applications in data transmission and cryptography. He has developed methods for code construction, decoding, and performance bounds, particularly using Gröbner bases and algebraic geometry. His recent publications (2020–2023) show a dual focus: (1) advanced coding techniques like Steane-enlargement of quantum codes and nested code pairs, and (2) educational research on project-based learning (PBL) , digital transformation, and microcredentials at Aalborg University. This reflects his leadership in both technical research and pedagogical innovation. The body of his work, including over 79 publications, demonstrates consistent contributions to IEEE Transactions on Information Theory , Designs, Codes and Cryptography , and Finite Fields and Their Applications . His research often involves collaborations with experts in coding and cryptography. Geil has supervised several PhD students and is involved in multiple research projects. Though no specific awards are listed in the text, his editorial roles and sustained publication record indicate recognition in the academic community. He leads initiatives like the Vision-in-Practice Project , aiming to transform engineering education through structured frameworks and continuous improvement. His work supports interdisciplinary, problem-based learning models central to Aalborg University’s educational philosophy.

Sander de JongView profile

Research Fellow

• Artificial Intelligence
• Large Language Models
• Human-Computer Interaction
• +4 more

Sander de Jong is a Research Fellow in the Department of Computer Science at Aalborg University's Faculty of IT and Design, focusing on Human-Computer Interaction and Artificial Intelligence . Research Interests: His work explores the intersection of Large Language Models (LLMs) , Artificial Intelligence , and Psychology , with emphasis on: AI-assisted Collaboration: Cognitive and social awareness in group interactions. LLM-generated Advice: User perception and trust in automated systems. Ethical AI: Moral manifestations and bias mitigation in clinical decision support. Human-AI Dynamics: Theory of Mind and self-presentation strategies. Recent Trends: His 2023-2024 publications highlight applications of LLMs in collaborative settings, ethical challenges in AI, and decision-making frameworks. Key methodologies include semistructured interviews and exploratory studies .

Daniel FišerView profile

Associate Professor

• Multi-Agent Planning
• Symbolic Search
• Heuristic Functions
• +4 more

Associate Professor Daniel Fišer is affiliated with the Department of Computer Science at Aalborg University, part of The Technical Faculty of IT and Design. His research focuses on multi-agent planning, symbolic search, and heuristic function optimization. He has contributed to advancements in optimal planning algorithms, heuristic design, and automated planning competitions. Fišer’s work spans theoretical and applied aspects of artificial intelligence, including reinforcement learning and fuzzing biases for policy testing. His research has been recognized with the ICAPS 2023 Best Paper Runner-Up Award and the AAAI 2022 Outstanding Paper Award (Honorable Mention). Recent publications emphasize scalable oversubscription planning, higher-dimensional potential heuristics, and competitive benchmark evaluations in automated planning systems. His contributions bridge theoretical foundations and practical applications in AI planning domains.