Jonas Wolpers Reholt is an Instructor at the Department of Computer Science, University of Copenhagen, affiliated with the Algorithms and Complexity (AC) section. His work bridges theoretical computer science with practical applications, particularly in the realm of efficient computation and algorithmic paradigms. Role: Instructor University: University of Copenhagen Department: Algorithms and Complexity Email: jonas.reholt@di.ku.dk The AC section focuses on understanding computational efficiency through mathematical theory, with impacts on machine learning and applied domains. Jonas’s research aligns with themes like program analysis and reversible computing, as evidenced by his 2023 publication on static dereversibilization techniques. His recent work contributes to the theoretical foundations of reversible computation, with applications in software optimization and data structures. The publication appears in the Lecture Notes in Computer Science series, reflecting interdisciplinary collaboration and rigorous peer-reviewed scholarship. As a member of the AC section, Jonas engages in teaching and research alongside prominent figures like Professor Mikkel Thorup, who leads the section. The AC section also hosts major research centers such as BARC and DABAI, fostering innovation in algorithm design and big data analytics.
Lukas Thomas Schilling serves as an Instructor (mapped to Lecturer) at the Department of Computer Science (DIKU), University of Copenhagen, with contact email lusc@di.ku.dk and office at Universitetsparken 1, 2100 Copenhagen Ø. His research spans foundational computer science domains: Computer Science (broad theoretical and applied frameworks) Software Engineering (systems design, development methodologies) Algorithms (complexity analysis, optimization) Programming Languages (theory, implementation, type systems) Artificial Intelligence (core principles, ethical implications) Machine Learning (statistical models, data-driven systems) These interests align with DIKU's research sections including Programming Languages and Theory of Computation, and Software, Data, People, & Society, reflecting the department's emphasis on both theoretical rigor and societal impact in computing.
Anders la Cour-Harbo serves as an Associate Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design. His academic career spans over two decades with consistent publication output since 2000, demonstrating sustained research activity in unmanned aircraft systems and related technologies. His institutional affiliation places him within Denmark's prominent engineering research environment focused on practical technological applications. Professor la Cour-Harbo's research interests center on unmanned aircraft systems engineering, with particular expertise in drone applications for industrial settings. His work spans drone load systems, emergency landing technologies, predictive maintenance, and offshore operations. The research fingerprint shows strong emphasis on Unmanned Aircraft Engineering (100%), Load System Engineering (87%), and Unmanned Aircraft System Engineering (46%), reflecting his specialized focus areas. His projects consistently address real-world applications of drone technology, particularly in challenging environments like offshore wind farms. Analysis of his publication trends reveals a strategic focus on practical drone applications with increasing emphasis on safety systems, regulatory compliance, and industrial implementation. Recent publications (2023-2024) show strong industry relevance with applications in offshore wind turbine maintenance, predictive maintenance systems, and vision-based control technologies. His research bridges theoretical control systems with practical implementation challenges in drone operations. Teacher of the Year 2015 Teacher of the Year 2006 Professor la Cour-Harbo leads multiple significant research projects including SafeEye (Automated emergency landing for small unmanned aircraft), UAS-ability (research infrastructure for drone development), and OPAL (Offshore Delivery of Packages). He serves as chair for JARUS (Joint Authority for Rulemaking of Unmanned Systems), significantly influencing European drone legislation. His spin-off company Vixos demonstrates successful technology transfer from academic research to commercial application. The Harm threshold for unmanned aircraft in European legislation impact shows his direct contribution to shaping regulatory frameworks. His laboratory and research team focus on practical drone applications with infrastructure supporting airborne data collection and drone development. The UAS-ability project specifically created research infrastructure for drone development and airborne data collection. His collaboration network spans multiple countries, with significant European partnerships focused on advancing drone technology standards and applications. His work with JARUS places him at the forefront of international drone regulation development.
Luca Pezzarossa is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on real-time systems, embedded computer systems, digital microfluidics, compiler optimizations, and hardware accelerators. He leads projects such as the Edu4Chip: Joint Education for Advanced Chip Design in Europe initiative and supervises PhD students in areas like compiler optimizations for neural networks and speech enhancement algorithms. His academic journey includes contributions to interdisciplinary fields, combining computer engineering with biomedical applications such as biochip design and PCR optimization. He actively engages in open-source tool development, particularly using the Chisel framework for hardware design education and research. Key research themes include: Real-time systems and time-predictable architectures Compiler-driven optimizations for constrained devices Digital microfluidics for lab-on-a-chip systems Edge computing and TinyML applications Recent publications highlight innovations in microplastic detection on edge devices, dynamic channel pruning for speech enhancement, and parallel execution engines for digital microfluidics. His work aligns with sustainable development goals through environmental applications and energy-efficient technologies. Current projects involve: PhD Supervision: Andrea Cerioli (Compiler Optimizations), Riccardo Miccini (AI-to-Neural Network Mapping), Ehsan Khodadad (Time-predictable Systems) Research Grants: EU-funded Edu4Chip (2023–2025), multiple industry-academia collaborations Labs and teams: Leads the Embedded Systems Engineering group at DTU, focusing on interdisciplinary hardware-software co-design for real-world applications. Active in developing open-source frameworks for education and research.
Henrik Bredmose is a Professor at the Technical University of Denmark (DTU) within the Department of Wind and Energy Systems. His research focuses on water wave dynamics, applied mathematics, and numerical methods, with a specific emphasis on violent flows and offshore engineering challenges. He has held postdoctoral positions at the University of Bristol and DHI Water & Environment, contributing to both academic and industrial projects. Education: Mathematical Modelling of Nonlinear Irregular Water Waves (PhD, DTU, 1999-2002). Research interests include computational fluid dynamics (CFD), floating wind turbine hydrodynamics, extreme wave load prediction, and design wave methodologies. His recent work addresses aero-elastic stability of wind turbines, second-order force models for non-slender structures, and optimization of floating wind farm layouts. Key projects include FloatLab (2023-2027) and FloatStep, focusing on advanced hydrodynamic analysis and design tools for offshore wind energy systems. Collaborations span international teams, addressing challenges in wave-structure interaction and turbine dynamics. He advises PhD students on topics like floating wind farm modeling and monopile wave impact loads. His contributions include the DeRisk Database, providing extreme design wave data for offshore structures.
Rongling Li is an Associate Professor at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU). His research focuses on smart energy systems, smart cities, and building energy flexibility, emphasizing modeling and data-driven approaches. He leads projects like SEEDS and IEA EBC Annex 82, contributing to resilient low-carbon energy systems. He has supervised seven PhD graduates and currently advises two students on energy flexibility topics. Key affiliations include chairing the IEA EBC Annex 82 and serving on the Built4People board under Horizon Europe. His expertise spans energy resilience, building physics, and machine learning applications. Notable awards include the 2019 Best Presentation Award and a 2021 research fellowship at the University of Tokyo. His research portfolio includes 55 publications across journals like Applied Energy and Energy and Buildings. Current projects involve data-driven control for smart energy systems and energy management in sports facilities. He actively reviews PhD theses at institutions such as UC Dublin and Chalmers University.
Erik Demaine is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Theory of Computation (TOC) group. His roles combine computer scientist, mathematician, and artist. He holds appointments at MIT’s School of Engineering and is known for interdisciplinary work bridging computational geometry, algorithms, and art. Research Interests: Demaine focuses on algorithms, discrete and computational geometry (including folding and origami), data structures, complexity theory, combinatorics, computational biology (protein folding), and network computing. His work also explores computational archaeology and intersects with artistic mediums like sculpture and glassblowing. Awards: He received the MacArthur Fellowship for his contributions to computational geometry and folding theory. His favorite award humorously cites the 'Tetris Master' title, though it is not a formal scientific honor. Collaborations: He frequently collaborates with his father Martin Demaine on artistic projects, such as curved-crease sculptures in MoMA’s permanent collection and films like Lino Tagliapietra: Glass Magician . His research emphasizes 'supercollaboration' and is documented in his extensive CV available online.
Maryamsadat Tahavori is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Engineering Technology and Didactics Energy Technology and Computer Science. Her research focuses on sustainable energy systems, asset management, control systems, and fault diagnosis in robotics and district heating networks. She leads projects addressing district heating network optimization, prescriptive analytics, and soil sustainability through sensor technologies. Her academic contributions include advancements in model reduction techniques for bilinear systems and multi-objective optimization algorithms. She supervises PhD candidates like Jens Grønborg and collaborates internationally on initiatives like the IEA DHC Annex for district heating asset management. Key awards include IEEE Senior Member (2021). Her work bridges theoretical control systems with practical applications in energy infrastructure, agriculture, and autonomous systems. She actively participates in conferences, organizes academic events, and serves as an editor for the Sensors journal.
Søren Hansen is Associate Professor at DTU's Department of Electrical and Photonics Engineering, specializing in embodied AI and control systems. His research develops algorithms for autonomous robots operating in constrained environments like airports. Key Projects: ShippingLab Autonomy (maritime robotics), sensor-based fault diagnosis for UAVs, and real-time path planning for de-icing vehicles. Research combines probabilistic modeling with hardware implementation.
Evelien van der Hurk is an Associate Professor at the Department of Technology, Management and Economics within DTU Management at the Technical University of Denmark. Her research focuses on optimization, simulation, and decision-making in transportation systems and public health. She specializes in public transport planning, epidemic modeling, and resilient infrastructure design. Her work integrates operations research techniques with real-world applications, addressing challenges such as rolling stock rescheduling, disease spread mitigation, and autonomous transit systems. She has contributed to advancing methodologies like matheuristics for timetabling and simulation-optimization frameworks for immunization strategies. Key research themes include transportation network design, passenger behavior analysis, and robust scheduling under uncertainty. Her articles often bridge theoretical models with practical implementation, emphasizing societal impact in urban mobility and public health policy. No scientific awards or student advisement details are explicitly mentioned in the provided materials. Her research has been published in leading journals and conferences, reflecting her expertise in interdisciplinary systems optimization.
Kerstin von Borries is an Assistant Professor in the Department of Environmental and Resource Engineering at the Technical University of Denmark (DTU). Her research focuses on advancing quantitative sustainability assessment, particularly in chemical toxicity characterization through digitalization and machine learning. She leads and contributes to projects like Mistra SafeChem 2 and UNEP-GLAM, addressing safe and sustainable chemical design, risk screening, and global guidance frameworks. Her work integrates life cycle analysis, environmental toxicology, and computational methods to bridge data gaps in toxicity assessment. Education: Completed her Ph.D. in 2024 with a thesis titled "Advancing life cycle based chemical toxicity characterization through digitalization," supervised by Prof. Olivier Jolliet and Prof. Peter Fantke. Research Interests: Machine learning applications in toxicity prediction, uncertainty quantification, green chemistry, and sustainable by design methodologies. Key areas include chemical synthesis optimization, ecotoxicity assessment, and policy integration for safer chemical practices. Labs/Teams: Affiliated with the DTU USEtox Research Centre and contributes to the ParC research initiative. Active in collaborative networks addressing global chemical risk assessment and sustainability. Grants/Projects: Principal Investigator for Mistra SafeChem 2 (2024–2028) and UNEP-GLAM (2013–2028), co-supervisor for multiple Ph.D. projects, and involved in EU-funded initiatives like ParC.
Shahrzad M. Pour is a Researcher at the Department of Applied Mathematics and Computer Science Dynamical Systems at the Technical University of Denmark. Her work bridges computer science and transportation engineering, focusing on railway systems, road condition modeling, and climate change adaptation technologies. Expertise in railway engineering (100%) Specializes in traffic management systems (76%) Develops scheduling algorithms (70%) Active in road engineering (50%) Contributes to climate risk management frameworks Her research intersects with UN Sustainable Development Goals through innovative solutions for sustainable infrastructure and climate action. Recent publications highlight her work in urgent computing architectures, IoT platforms for road monitoring, and adaptive decision support systems. She contributes to open science through datasets like LiRA-CD (road condition modeling) and participates in interdisciplinary collaborations across Denmark and Europe.
Jakob Kjøbsted Huusom is a Professor at the Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU). His research emphasizes advanced process control, model development for the process industry, and sustainable technologies. He is affiliated with the KT Consortium PROSYS and the Process and Systems Engineering Centre (PROSYS), contributing to UN Sustainable Development Goals related to affordable energy and climate action. His work spans hybrid modeling approaches integrating AI with first-principles methods, optimization of industrial processes, and real-time adaptive systems. Current projects include MPC tuning algorithms, enzymatic biodiesel production control, energy-efficient distillation technologies, and electrification of industrial processes using renewable energy. As a supervisor, he guides multiple PhD students in topics such as risk monitoring, model-based digitalization, and Power-to-X applications. His research tools and methodologies address challenges in process identification, state estimation, and controller design, with a focus on scalability and real-world implementation. Collaborations include international teams in Julia-based simulation tools and hybrid neural network modeling. His contributions advance both theoretical frameworks and practical solutions for sustainable industrial systems.
Ole Sigmund is a Professor at the Technical University of Denmark within the Department of Civil and Mechanical Engineering. He is affiliated with the NanoPhoton – Center for Nanophotonics and actively involved in research related to topology optimization, structural mechanics, and nanophotonics. Accepting PhD Students ORCID: 0000-0003-0344-7249 Research Interests: His work spans structural design, inverse methods, and multiphysics systems. Key areas include metamaterials, additive manufacturing, and photonic device optimization. Recent Publications (2021-2025): Focus on topology optimization for mechanical stability, nanophotonics, and multi-physics applications. Projects: Over 80 projects, including vibroacoustic systems, nanocavity design, and thermo-mechanical regulators. Collaborates with researchers like J.P. Groen and F. Wang.
Zoi Kaoudi is an Associate Professor at the IT University of Copenhagen, affiliated with the Data, Systems, and Robotics school and the Data-intensive Systems and Applications department. Her research focuses on advancing data systems, knowledge graphs, and large-scale data analysis. She leads the Rank4QO project (2024–2027), funded by the Carlsberg Foundation, which explores query optimization using ranking algorithms. Her work emphasizes machine learning integration in data management systems, including frameworks like Apache Wayang, which unifies diverse data analytics platforms. Key collaborations include projects with Volkswagen Group and SAP, addressing dynamic graph processing and knowledge graph embeddings. Notable contributions include innovative approaches to parameter management (e.g., Good Intentions ), automated data science pipelines ( DORIAN ), and efficient graph processing algorithms. Her recent publications (2023–2025) highlight advancements in machine learning systems, distributed data processing, and adaptive optimization techniques. Current projects aim to bridge machine learning and data management through frameworks like Wayang and Dorian, with applications in air cargo revenue management and semantic web systems.
