Computer Engineering Professors and Supervisors in Denmark | ApplySharif

Active facets:

Find Academic Supervisors

Find and connect with academic supervisors, professors, and scholars for your research journey.

Showing 31-45 of 1,845 supervisors

Profile data may be stale. It is sourced from public faculty pages.

Ditte Hededam WelnerView profile

Researcher

Technical University of DenmarkDenmark

Ditte Hededam Welner is a Senior Researcher & Group Leader at the Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark. Her research focuses on Enzyme Engineering and Structural Biology, particularly the development of enzyme biocatalysts for sustainable industrial production of natural products like aromas, dyes, and pharmaceuticals. She leads efforts to replace petroleum-based chemical synthesis with eco-friendly bio-based processes, emphasizing glycosyltransferase (GT) engineering to enhance substrate specificity, efficiency, and stability. Education: Biochemistry, University of Copenhagen (2000–2011). Research Interests: Glycosylation mechanisms, high-throughput enzyme discovery/evolution, structural biology techniques (X-ray crystallography, NMR), and biocatalysis applications in sustainable chemistry. Her work contributes to UN SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production). Recent publications highlight advancements in alginate degradation mechanisms, sucrose synthase engineering, and glycosyltransferase applications in biocatalytic routes for indigo/indican production. She supervises multiple PhD projects on enzyme optimization, machine learning for enzyme engineering, and sustainable bioprocessing. Professional Activities: Peer review for journals like Nature Catalysis and Metabolic Engineering , conference organization, and editorial contributions. Active in promoting open-access science and sustainable biotechnology. Labs/Teams: Leads the Enzyme Engineering and Structural Biology group at DTU, collaborating with industry and academic partners globally to advance biocatalytic solutions for environmental challenges.

Official University Profile

Grethe WintherView profile

Professor

Technical University of DenmarkDenmark

Grethe Winther is a Professor and Head of Section in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), specializing in Materials and Surface Engineering. Her research is centered on the analysis and modeling of microstructure and mechanical properties of metals, with a strong emphasis on dislocation structures, deformation textures, and recrystallization processes. Her research interests include: Dislocation structures and boundary analysis in deformed metals Crystal plasticity modeling using synchrotron data (3DXRD) Orientation relationships in recrystallization Prediction of mechanical properties in industrial metal forming Multiscale modeling of plastic deformation and surface roughening The recent articles (2025) highlight a consistent focus on advanced characterization techniques like dark-field X-ray microscopy and discrete dislocation dynamics simulations. These works explore the formation of geometrically necessary boundaries, dislocation cell evolution, and multiscale surface deformation, reflecting a strong integration of experimental and computational methods in materials science. Key themes include plastic deformation mechanisms, microstructure evolution, and predictive modeling in metallic systems. Grethe Winther actively supervises multiple PhD projects, including those on dislocation dynamics, X-ray microscopy, and ductile failure simulations. She collaborates extensively with researchers such as H.F. Poulsen and C.V. Nielsen. Her work is supported by ongoing research projects at DTU, focusing on fundamental and applied aspects of metal deformation and microstructure. She is affiliated with the Materials and Surface Engineering section at DTU, where she leads research efforts combining advanced experimental techniques with theoretical modeling to understand and predict metal behavior under deformation.

Official University Profile

Katrin VorkampView profile

Professor

Aarhus UniversityDenmark

Professor Katrin Vorkamp holds a position at the Department of Environmental Science, specializing in Environmental Chemistry and Toxicology at Aarhus University. Her research focuses on understanding the transport, exposure pathways, and impacts of persistent pollutants such as PFAS, POPs, and mercury in Arctic and Antarctic ecosystems, with a particular emphasis on wildlife and human health implications. She has contributed to projects addressing climate change effects on contaminant dynamics, policy-oriented monitoring frameworks (e.g., Water Framework Directive), and innovative methods like passive sampling and non-target screening. Her work spans interdisciplinary collaborations, including the AMAP Core 2025-2027 project tracking pollution in Greenland biota and the ArcSolution initiative exploring a One Health perspective in Arctic pollution. She also leads the NAMMINE project on non-target analysis in Nordic marine mammals. Key themes in her research include understanding local vs. long-range pollutant sources, climate-contaminant interactions, and developing early warning systems for emerging chemicals. Publications highlight her expertise in biochar applications for waste valorization, contaminant trends in Adélie penguin eggs, and computational tools for risk assessment. Her projects often bridge environmental science with policy, aiming to inform sustainable solutions for pollution challenges in sensitive ecosystems.

Official University Profile

Philip BilleView profile

Professor

Technical University of DenmarkDenmark

Philip Bille is a Professor and Head of the Algorithms, Logic and Graphs section at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), College of Engineering. His research centers on the design and analysis of efficient algorithms, particularly for string processing, compressed data, and data structures. His research interests lie at the intersection of theoretical computer science and practical applications. He focuses on algorithms , data structures , string indexing , pattern matching , and compressed computation . His work enables efficient querying and processing of large-scale, repetitive data, with applications in bioinformatics, intrusion detection, and green computing. The recent publications reflect a strong trend in developing space-efficient and fast algorithms for modern computational challenges. Key themes include compressed data structures , sliding window indexing , finite automata compression , and energy-aware matrix operations . These works demonstrate expertise in balancing theoretical rigor with practical performance. Philip Bille actively supervises multiple PhD students and leads several research projects. He contributes to advancing sustainable computing aligned with UN SDGs. His work integrates algorithmic theory with real-world efficiency. Supervises PhD projects on hierarchical compression, adaptive computation, and vector processor algorithms. Involved in research on green computing, compressed formats, and efficient data models. He is affiliated with the Algorithms, Logic and Graphs group at DTU, a hub for theoretical and applied algorithmic research. The team explores fundamental problems in data representation and processing, pushing the boundaries of what is computationally feasible in terms of time and space.

Official University Profile

Niels Martin LarsenView profile

Associate Professor

Aarhus School of ArchitectureDenmark

Niels Martin Larsen is an Associate Professor at the Aarhus School of Architecture, affiliated with Research Laboratory 2: Technology, Building Cultures and Settlement. He holds a PhD in algorithmic design and has been part of academic staff since 2009. His roles include teaching and research in technology-driven architectural design. Education and Career: PhD student at Aarhus School of Architecture (2009–present) Master's and Bachelor's teaching assistant (2002–2008) Worked at architectural firms including Stuff Aps and 3XNielsen A/S (1999–2008) Graduated from Aarhus School of Architecture (1992–1998) with an internship at Enrique Miralles in Barcelona (1996) Research Interests: Focus on technology and digital design , including algorithmic design, architectural geometry, and sustainable materials. Recent work explores building reuse, digital fabrication, and timber structures. His projects bridge computational methods with practical architectural applications. Awards: 2012: Best Paper Award at Advances In Architectural Geometry for 'Engineering of complex geometry' Grants and Projects: Key roles in projects like 'Recycling on the Land Register' (2023–2025) and 'Material Imagination: Reconnecting with the Matter of Architecture' (2017–2021). Collaborates on Nordic networks for digital fabrication and timber innovation. Labs/Teams: Active in Research Laboratory 2, focusing on technology-driven solutions for building cultures and habitation.

Official University Profile

Bissan GhaddarView profile

Professor

Technical University of DenmarkDenmark

Bissan Ghaddar is a Professor in the Department of Technology, Management and Economics at Technical University of Denmark (DTU). Her work focuses on robust optimization, edge computing, and sustainable energy systems, contributing to UN Sustainable Development Goals related to affordable and clean energy. She supervises PhD projects on sector coupling in energy models and quantum computations for power systems. Her research interests include optimizing energy consumption in electric vehicle routing and application placement in edge computing under uncertainty. She has published influential papers in journals like Transportation Research Part C and Omega , addressing latency and efficiency challenges in dynamic systems. Current projects include modeling large-scale sectoral energy systems using smart-linking approaches (2024–2027) and secure power system operation leveraging quantum computations (2021–ongoing). She collaborates internationally with experts in operations research and telecommunications.

Official University Profile

Martin Nordal PetersenView profile

Associate Professor

Technical University of DenmarkDenmark

Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .

Official University Profile

Kantaro FujiwaraView profile

Associate Professor

IT University of CopenhagenDenmark

Kantaro Fujiwara serves as Associate Professor at the Graduate School of Medicine, The University of Tokyo, with concurrent appointments at the International Research Center for Neurointelligence (IRCN) and the Department of Mathematical Informatics, Graduate School of Information Science and Technology. He also manages the Data Science Core infrastructure for IRCN. His academic background includes a Ph.D. in Information Science and Technology from the University of Tokyo (2008), followed by postdoctoral research at the University of Tokyo (JSPS) and University of Cambridge, then assistant professorships at Saitama University and Tokyo University of Science before joining the University of Tokyo faculty. Dr. Fujiwara's research bridges computational neuroscience and neural data analysis through mathematical modeling of neural networks, development of neural data analysis methodologies, and exploration of brain-inspired machine learning. His work extends to biological information processing with specific applications in pancreatic beta cell modeling for diabetes research, establishing connections between theoretical frameworks and experimental neuroscience. His publication record (2017-2023) reveals consistent interdisciplinary contributions applying echo state networks, recurrence analysis, and nonlinear dynamics to neural data classification, physiological signal processing, and disease modeling. These works demonstrate strong integration of computer science, neuroscience, and biomedical engineering methodologies to solve complex neurobiological problems. As Data Science Core Manager at IRCN, he oversees computational infrastructure and software resources that enable advanced neurointelligence research across the University of Tokyo ecosystem, providing critical support for data-intensive neuroscience projects.

Official University Profile

Christian Erik KampmannView profile

Associate Professor

Copenhagen Business SchoolDenmark

Christian Erik Kampmann is an Associate Professor at the Department of Strategy and Innovation, Copenhagen Business School. He holds a Ph.D. in Management from MIT and an engineering background from DTU, bridging technical rigor with socio-economic research. Education: MIT (Ph.D. in Management), DTU (Engineering) Research Interests focus on system dynamics as applied to sustainable energy transitions, electric mobility, and green urban mobility. His methodological work enhances structural dominance analysis and eigenvalue techniques for complex system modeling. Recent publications address feedback loop gains, market misperceptions of feedback, and comprehensive analytical approaches for policy modeling, reflecting his interdisciplinary focus on sustainability challenges. Teaching includes courses on system dynamics, sustainable business strategy, and quantitative business research, with supervision of theses on electric mobility and product-service sustainability. External engagements involve board membership (Magasin du Nord, 2018-2020) and computer modeling consultancy (Zerolytics, Whitebox).

Official University Profile

Sneha DasView profile

Assistant Professor

Technical University of DenmarkDenmark

Sneha Das is an Assistant Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), specializing in Speech and Language Technology, Machine Learning, and Privacy-Preserving AI. Her research bridges technical innovation with applications in mental health and physiological signal analysis. Her work focuses on Speech Emotion Recognition , Distributed Speech Processing , and Explainable AI , with recent publications exploring model interpretability, speaker anonymization, and physiological data analysis for emotion detection. She actively supervises PhD students in projects involving AI for mental health and hydroacoustic modeling of fish behavior. Key Research Areas: Speech Emotion Recognition (SER) Privacy and Fairness in Speech Processing Transfer Learning with Physiological Time Series AI Applications in Health and Aquaculture Notable achievements include earning a DSc (Tech) degree for her thesis on robust distributed speech processing. She also contributes to educational activities, including teaching applied statistics and R programming to PhD students.

Official University Profile

Anne Elisabeth HaxthausenView profile

Associate Professor

Technical University of DenmarkDenmark

Anne Elisabeth Haxthausen is an Associate Professor at the Software Systems Engineering section within DTU Compute , Technical University of Denmark . Her work focuses on formal methods, railway control systems, and safety-critical software engineering. Founder and leader of the DTU Railway Verification Group Member of European Technical Working Group on Formal Methods in Railway Control Editorial board member for Springer Formal Aspects of Computing Journal Active in the Overture Language Board Her research emphasizes formal verification of railway interlocking systems, particularly through compositional approaches and automated tools. She has contributed to projects like RobustRailS, Overture, and RAISE, focusing on model-based development and verification. She serves as a tutor for bachelor students and contributes to the advisory committee for DTU's Computer Science and Engineering MSc program. Her recent publications explore challenges in verifying autonomous and AI-driven railway technologies.

Official University Profile

Pernille BjørnView profile

Professor

University of CopenhagenDenmark

Pernille Bjørn is a Professor in Computer Supported Cooperative Work (CSCW) at the Department of Computer Science , University of Copenhagen (DIKU), where she has been since May 2015. Her research investigates collaborative work practices to design cooperative technologies, focusing on domains like healthcare, global software development, startup companies, and digital fabrication. Faculty of Science, University of Copenhagen Human-Centred Computing Section Research Interests : Bjørn’s work spans CSCW , Human-Computer Interaction , and Digital Fabrication , with applications in healthcare systems, cross-cultural software development, and inclusive technology design. She explores collaborative virtual reality training, FemTech, and crisis computing. ACM Distinguished Member (2024) Publications : Published in top venues like ACM Transactions on Computer-Human Interaction , CSCW , and CHI , her recent work examines hybrid work asymmetry, neurodiverse accessibility, and art-driven collaborative research.

Official University Profile

Alfred TaudesView profile

Professor

University of CopenhagenDenmark

Alfred Taudes is a Full Professor at the Department of Information Systems and Operations, Institute for Production Management, Vienna University of Economics and Business (WU Vienna). He holds a doctoral degree and a Habilitation from WU Vienna in Business Administration and Management Information Systems, and a Magister degree from Vienna University. He has held assistant professorships at WU and visiting professorships at Augsburg, Münster, Essen, and Tsukuba University, Japan. He joined WU permanently in 1993 and served as head of the Department of Information Systems and Operations from 2010 to 2016. His research spans Operations and Supply Chain Management , Marketing Engineering , Knowledge Management , and the impact of Big Data and Blockchain on production systems. Using Complexity Science and Cryptoeconomics , he investigates digital production, integrated value chains, and market designs. He teaches undergraduate and graduate courses including Operations Strategy, Data Science, and IT seminars in WU’s International Supply Chain Master program, and has also taught at Japanese universities. His recent publications focus on blockchain privacy (e.g., CoinJoin analysis), CBDCs, MiCAR regulation, decentralized federated learning, and digital custody, reflecting a strong trend toward cryptoeconomics and blockchain-based systems in operations and finance. These works appear in top journals and conferences in information systems, security, and operations research. Cooperation Officer of the Year 2013/14 Distinguished Paper Award WI 2009 VHB Best Paper Award Nomination VHB Best Paper Award Dr. Wolfgang Houska - Recognition Award Alfred Taudes has coordinated major research projects such as the WWTF-project “Integrated Demand and Supply Chain Management” and the Special Research Area Adaptive Models in Economics and Management Science. He currently leads the research group on Cryptoeconomics at WU and chairs the scientific board of the Austrian Internet Offensive . His leadership extends to project management in initiatives like the Austrian Blockchain Center and research on decentralized finance and digital assets. He is actively involved in academic service, including organizing conferences like DEXA 2022, serving on editorial boards, and advising on research policy. His lab and research group focus on blockchain applications, digital transformation in operations, and the societal implications of big data.

Official University Profile

Kim BjergeView profile

Associate Professor

Aarhus UniversityDenmark

Kim Bjerge serves as Associate Professor and Group Leader in Aarhus University's Department of Electrical and Computer Engineering, specializing in computer vision and machine learning applications for ecological monitoring. His research bridges engineering and environmental science to develop innovative solutions for insect biodiversity assessment and sustainable agriculture. His core research interests include computer vision, deep learning, and edge computing systems for real-world ecological monitoring. Dr. Bjerge develops time-lapse camera pipelines and deep learning models specifically for insect population tracking in natural environments, with emphasis on agricultural applications like black soldier fly farming and biodiversity conservation. His work integrates signal processing techniques with biological data to create field-deployable monitoring systems. Recent publications reveal a strong trend toward practical implementations of computer vision in entomology, particularly focusing on edge processing for camera traps, automated trait prediction in insect farming, and biodiversity monitoring systems. Key research areas include nocturnal insect monitoring, floral environment analysis, and developing specialized datasets like AMI for insect identification in wild settings. He leads multiple significant research projects funded through competitive grants: MAMBO: Modern Approaches to Monitoring Biodiversity (2022-2026) FLYgene: Sustainable Insect Production for Livestock Feed (2022-2026) Automatisk monitering af nataktive insekter: Automatic nocturnal insect monitoring (2024-2029) Pilotprojekt for automatisk registrering af invasive plantearter: Invasive species monitoring (2020-2021) As head of the Signal Processing and Machine Learning research group, Dr. Bjerge directs interdisciplinary teams developing computer vision solutions for biological monitoring systems. His laboratory focuses on creating robust field-deployable technologies including scanner-based arthropod imaging systems, time-lapse camera networks for floral environments, and edge AI processors for real-time insect monitoring in agricultural settings.

Official University Profile

Sithik AliyarView profile

Researcher

Technical University of DenmarkDenmark

Sithik Aliyar is a Postdoctoral Researcher at the Department of Wind and Energy Systems, Flows Wind Turbine Design Division, at the Technical University of Denmark (DTU). He specializes in computational fluid dynamics (CFD) and offshore wind turbine dynamics, focusing on wave interactions with floating structures. Institution: Technical University of Denmark (DTU) Department: Flows Wind Turbine Design Division, Wind and Energy Systems Research Focus: Floating wind turbines, extreme sea states, harmonic separation, and numerical algorithms His work combines advanced CFD simulations with experimental validation to analyze floating wind turbine stability under directional waves. Recent contributions include the FloatStepper algorithm for robust wave response modeling and studies on SPAR platform upending risks. Publications highlight collaborations with experts like H. Bredmose and J. Roenby, with research outputs spanning Renewable Energy , Royal Society Open Science , and international conferences on ocean engineering. Key metrics include open-access citations, computational fluid dynamics, and floating wind turbine dynamics.

Official University Profile