جست‌وجوی استاد و پژوهشگر

Peter Behrensdorff Poulsenمشاهده پروفایل

پژوهشگر

• Solar Cell Engineering
• Photovoltaics
• Drone Engineering
• +۵ مورد دیگر

Peter Behrensdorff Poulsen serves as Solar Photovoltaic Systems Group Leader at the Department of Electrical and Photonics Engineering, Technical University of Denmark (DTU). His work spans photovoltaic research, solar-powered lighting systems, and drone-based inspection technologies within DTU's College of Engineering. His research focuses on Solar Cell Engineering , Photovoltaic Modules , and Drone Applications for renewable energy systems. Key areas include bifacial photovoltaics, electroluminescence imaging diagnostics, building-integrated photovoltaics, and ultra-efficient solar-powered lighting solutions. His work significantly contributes to UN Sustainable Development Goals related to affordable clean energy and sustainable cities. Recent publications reveal strong trends in AI-driven PV diagnostics , bifacial module performance in northern climates, and dark-sky compatible lighting systems . His research bridges fundamental photovoltaic science with practical applications in urban infrastructure and environmental sustainability. Best Poster Award at 44th IEEE Photovoltaic Specialists Conference Best Poster Award at 48th IEEE Photovoltaic Specialists Conference Characterizing the Performance of Daylight Filters for Electroluminescence Imaging Poster Award at 35th European Photovoltaic Solar Energy Conference Poster Prize at Sustain 2017 Poulsen leads multiple research grants including the Ultra-efficient Dark Sky-compatible Solar-powered Outdoor Lighting project (2024-2026) and previously managed the DronEL project (2017-2019) for drone-based PV inspection. His work connects photovoltaic engineering with practical lighting applications through the Lighting Color and Radiation Laboratory. He actively collaborates with industry partners on building-integrated photovoltaics and solar-powered infrastructure solutions, with notable projects including the Plateau Sun Hub public charging stations and Black Si BIPV panel development.

Allan Hanburyمشاهده پروفایل

استاد

• Information Retrieval
• Data Mining
• Natural Language Processing
• +۱۳ مورد دیگر

Allan Hanbury is a Full Professor for Data Intelligence at the Faculty of Informatics, TU Wien, and a faculty member at the Complexity Science Hub Vienna. He leads the Data Science Research Unit and serves as the Faculty Representative for financial affairs and internationalization. He holds a PhD in Applied Mathematics from Mines ParisTech and a Habilitation in Practical Informatics from TU Wien. PhD in Applied Mathematics, Mines ParisTech, 2002 Habilitation in Practical Informatics, TU Wien, 2008 Bachelor’s and Master’s in Physics and Applied Mathematics, University of Cape Town His research focuses on information retrieval, data mining, natural language processing, and information extraction, with applications in healthcare, legal, and patent domains. He has coordinated major EU projects including Khresmoi, VISCERAL, KConnect, and DoSSIER, the latter training 15 PhD students. He is co-founder of contextflow, a spin-off commercializing radiology search technology. His recent publications (2024–2022) highlight a strong trend in systematic literature review automation, neural re-ranking, large language models, and domain-specific information extraction. Key themes include improving citation screening, patient-trial matching, evaluation metrics, and dataset creation for offensive language and legal text. His work combines technical innovation with real-world impact in medical, legal, and scientific communication contexts. Allan Hanbury has received no explicitly mentioned scientific awards in the provided text. He actively supervises numerous PhD and master’s students and leads large research projects such as DoSSIER, Transparent Automated Content Moderation, and PLFDoc, funded by FWF, WWTF, and EU. His group develops tools for evidence synthesis, clinical data extraction, and legal document analysis. He also contributes to AI and data strategy in Austria and Europe. He leads the Data Science Research Unit at TU Wien and is involved in multiple interdisciplinary projects including BRISE (building regulation analysis), CDL-RecSys, and TACo, focusing on legal and scientific document processing. His work bridges academia and industry through spin-offs like contextflow and collaborations with Deutsche Telekom, Siemens, and FMA.

Michael Sandbergمشاهده پروفایل

استادیار

• Additive Manufacturing
• Composite Materials
• Digital Twins
• +۳ مورد دیگر

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

Xiao Chenمشاهده پروفایل

پژوهشگر

• Composite Structures
• Wind Energy Systems
• Structural Integrity
• +۷ مورد دیگر

Xiao Chen is a Researcher at the Technical University of Denmark (DTU), specializing in advanced testing and digitalization of composite and offshore steel structures for wind energy systems. With a PhD from Nagoya University (2011), his work focuses on structural integrity, fatigue analysis, and Digital Twins for wind turbine blades. PhD in Engineering, Nagoya University (2011) Senior Researcher (2019–present) and Researcher (2017–2018) at DTU Associate Professor (2016–2017) and Assistant Professor (2013–2015) at Chinese Academy of Sciences His research explores nonlinear buckling, fracture mechanics, and Industry 4.0 technologies for structural health monitoring. Recent publications highlight AI-driven damage detection, thermographic analysis, and finite element modeling of composites. He leads projects like QualiDrone and AQUADA-GO, funded by EUDP and VILLUM FONDEN. Key article trends include composite fatigue , digital twins , drone-based inspection , and machine learning for structural monitoring. He received the 2022 Best Presentation Award at an international conference. Projects: Villum Experiment Project DiscoverBlaDE AQUADA-GO QualiDrone DARWIN RELIABLADE RELIfe

• Pharmaceutical Physical Chemistry
• Drug Characterization
• Drug Delivery Systems
• +۷ مورد دیگر

Jesper Østergaard serves as Professor of Pharmaceutical Physical Chemistry within the Department of Pharmacy at the Faculty of Health and Medical Sciences, University of Copenhagen. With over 20 years of continuous service at the institution, he progressed through the academic ranks from Assistant Professor (2003-2006) to Associate Professor (2006-2018) before attaining full Professorship in 2019. His academic journey began with a PhD in pharmaceutical sciences from the University of Copenhagen in 2003. Professor Østergaard's research focuses on advancing fundamental understanding of drug development processes, particularly transport, dissolution, release phenomena, and chemical stability/kinetics. His work emphasizes the interplay between physical chemical properties of drug substances and excipients with transport processes and kinetics related to drug delivery. He has developed novel analytical approaches for physical chemical characterization, including techniques for measuring diffusivity, molecular interactions, and partitioning. His research has significant implications for subcutaneous and intramuscular injectable formulations, with a key focus on developing biopredictive in vitro release testing platforms that emulate in vivo conditions. Current research directions include physicochemical profiling using Taylor dispersion analysis and affinity capillary electrophoresis, design and characterization of injectable depot formulations, development of in vitro release testing methods for long-acting injectables, and application of UV-Vis imaging for drug dissolution and release testing. His publication record demonstrates consistent output across these areas, with recent work emphasizing dissolution dynamics, biorelevant testing methods, and advanced analytical techniques. As an educator, Professor Østergaard is course responsible for the compulsory bachelor courses Pharmaceutical Physical Chemistry I and II, teaching approximately 200 pharmacy students annually. He also supervises master's students in pharmaceutical physical and analytical chemistry, continuing his commitment to training the next generation of pharmaceutical scientists.

Chenjuan Guoمشاهده پروفایل

دانشیار

• Machine Learning
• Data Engineering
• Spatio-temporal Data Analysis
• +۴ مورد دیگر

Chenjuan Guo is an Associate Professor at the Department of Computer Science, Aalborg University, within The Technical Faculty of IT and Design. She is affiliated with the Data Engineering, Science and Systems group and the AI for the People initiative, and is part of the Daisy - Center for Data-intensive Systems. Her research focuses on machine learning, data engineering, spatio-temporal data analysis, and time series forecasting. Key projects include the Villum Foundation-funded 'Explainable AI for Complex Microbial Community Interactions and Predictions' (2021-2024) and the Astra project on time series analytics in spatial networks (2018-2021). Her research interests span representation learning, autoencoders, path representation, outlier detection, trajectory data analysis, and time series modeling. She has supervised 3 PhD students and contributed to over 60 publications, with a recent emphasis on transformer-based forecasting, neural architecture search, and continuous learning frameworks for spatio-temporal data. Her work bridges theoretical advancements with practical applications in environmental science, cloud computing, and urban mobility systems. Key achievements include developing frameworks like AutoCTS++ for automated time series forecasting and LightGTS for lightweight models. She actively collaborates internationally, contributing to conferences like ECML PKDD and CVPR. Her research is supported by grants from the Villum Foundation and other institutions.

Daniel Hardtمشاهده پروفایل

دانشیار

• Computational Linguistics
• Natural Language Processing
• Artificial Intelligence
• +۴ مورد دیگر

Daniel Hardt serves as Associate Professor in the Department of Management, Society and Communication at Copenhagen Business School. His interdisciplinary research bridges computational linguistics, artificial intelligence, and social analysis, with particular focus on natural language processing applications and theoretical linguistic phenomena. His primary research domains include Computational Linguistics (specializing in ellipsis resolution and sluicing phenomena), Natural Language Processing (developing methods for psychographic classification and sentiment analysis), and Artificial Intelligence (examining large language model capabilities and limitations). Recent work analyzes travel behavior during crises, gender effects in evaluations, and GDPR policy comprehension through NLP techniques. His publications span top venues including Linguistic Inquiry , Tourism Management , and ACL proceedings. Hardt actively engages with practical business applications through 27 media contributions discussing AI implementation, ChatGPT transparency, and data-driven leadership strategies. His academic service includes organizing events like the 2019 "Fake News" conference at CBS and presenting at international venues including JSAI 2024. With 28 supervised academic works documented, he maintains substantial mentoring activity while contributing to public discourse on digital transformation challenges.

Matteo Acclavioمشاهده پروفایل

استادیار

• Proof Theory
• Logic in Computer Science
• Concurrency Theory
• +۵ مورد دیگر

Matteo Acclavio is an Assistant Professor in Computer Science at the School of Engineering and Informatics, University of Sussex, affiliated with the Foundations of Software Systems (FoSS) research group. A logician specializing in proof theory and its applications to computer science, his work bridges mathematical logic with concurrency theory and process calculi. Education: PhD in Mathematics, Aix-Marseille University, France Master in Discrete Mathematics and Foundations of Theoretical Computer Science, Aix-Marseille University Master in Mathematics, Roma Tre University, Italy Bachelor in Mathematics, Roma Tre University His research focuses on graphical proof systems, linear logic, modal logic, and concurrency theory. Publications highlight contributions to deep inference, sequent calculus, and the intersection of logic with distributed systems. Recent work explores logical frameworks for concurrency, such as choreographic programming, and graphical models for proof systems. He teaches courses like Operating Systems and maintains active collaborations in theoretical computer science.

Zhanhao Zhangمشاهده پروفایل

پژوهشگر ارشد

• Model Predictive Control
• Process Control
• Time-Delay Systems
• +۳ مورد دیگر

Zhanhao Zhang is a Postdoc researcher at the Department of Applied Mathematics and Computer Science (DTU Compute) of the Technical University of Denmark, affiliated with the Scientific Computing Center for Energy Resources Engineering. His work centers on developing advanced control strategies for industrial processes with emphasis on sustainability and computational efficiency in energy-intensive sectors. His research specializes in Model Predictive Control (MPC) for time-delay systems, numerical discretization methods, and real-time implementation of cyber-physical control systems. Key application domains include zero-emission industrial processes, cement production blending operations, and oil/gas zero-discharge systems, where he bridges theoretical control algorithms with practical industrial constraints through close industry collaboration. Analysis of his 2022-2024 publications reveals consistent innovation in extending MPC methodologies to handle complex industrial realities like time delays and discontinuities while targeting environmental sustainability. His work demonstrates strong integration of computational mathematics with process engineering to solve critical challenges in carbon-intensive industries. Zhang completed his PhD project "Model Predictive Control for Zero Emission Industrial Processes" (2021-2024) under Professor John Bagterp Jørgensen at DTU, resulting in his doctoral thesis and multiple high-impact publications. This industry-collaborative project focused on developing control frameworks for decarbonizing industrial operations. As an active member of DTU's Scientific Computing Center for Energy Resources Engineering, he contributes to interdisciplinary research that applies high-performance computing and mathematical modeling to optimize energy resource extraction, processing, and utilization while reducing environmental impact.

Claus Bossenمشاهده پروفایل

استاد

• Data-driven Healthcare
• Participatory Design
• Electronic Health Records
• +۴ مورد دیگر

Claus Bossen is a Professor at the Department of Digital Design and Information Studies within Aarhus University's School of Communication and Culture. His research bridges participatory design, healthcare digitization, and data work. Primary Affiliation: School of Communication and Culture, Department of Digital Design and Information Studies Research Focus: Data-driven healthcare, information infrastructures, and participatory design Email: clausbossen@cc.au.dk Research Interests span critical areas in healthcare digitization, including: Emergence of data work professions Human-AI collaboration in clinical documentation Design of healthcare information systems Infrastructure governance and quality improvement Digitization's impact on non-clinical staff Participatory design scaling mechanisms Recent Publications (2024-2025) show a trajectory toward: Global-local data integration challenges Professional adaptation in data-intensive settings Digitization's soco-technical implications Empowerment through data work practices Emergency healthcare system analysis Human-AI collaboration frameworks Current Projects include: LIVSTEGN: Monitoring technologies for safe dementia care Making Data Work Visible: Professional changes in healthcare Acute healthcare treatment pathways

Helle Damgaard Zachoمشاهده پروفایل

استاد بالینی

• Nuclear Medicine
• Prostate Cancer
• Ovarian Cancer
• +۳ مورد دیگر

Helle Damgaard Zacho is a Clinical Professor at Aalborg University's Faculty of Health Sciences and Senior Physician at Aalborg University Hospital's Department of Clinical Physiology and Nuclear Medicine . Her work bridges clinical practice with advanced nuclear medicine research. Primary Affiliation: Aalborg University Hospital Academic Role: Clinical research and education at Faculty of Health Sciences Research Focus: PET/CT imaging for cancer diagnostics Zacho leads or co-leads multiple high-impact projects including FAPI/PSMA PET/CT studies for prostate, ovarian, and gastric cancers . Her fingerprint highlights expertise in: Prostate Cancer (100%) Positron Emission Tomography-Computed Tomography (84%) Bone Metastasis (50%) Gallium 68 applications (65%) Deep learning in radiology Cancer staging methodologies Her recent publications focus on optimizing FAPI and PSMA PET/CT for metastatic cancer detection, with active clinical trials in ovarian and prostate cancer diagnostics. While no formal awards are listed, her 147+ publications and 8 ongoing projects demonstrate substantial research output. Media coverage highlights her team's potential 'super-weapon' for cancer diagnostics (2023-2024), including national press attention for Denmark's best clinical trial 2025. She serves as a peer reviewer for journals like World Journal of Gastroenterology and participates in major urological cancer conferences.

Jette Ernstمشاهده پروفایل

دانشیار

• Digitalization and robotization in hospitals
• Professional identity and boundary constructions in healthcare
• Performance management and work monitoration
• +۳ مورد دیگر

Jette Ernst is an Associate Professor at Roskilde University's Department of Social Sciences and Business, specializing in organizational sociology and management studies. Her research focuses on the social and cultural dimensions of organizational change, particularly in healthcare settings, addressing topics like digitalization, robotics, professional identity, and power dynamics. She holds a PhD and multiple advanced degrees in business and communication studies. Education: PhD, Cand.Negot, Master of Science in Business (Language and Culture with English specialization). Research interests emphasize how automation and organizational restructuring impact healthcare work, employee responses, and professional boundaries. She employs qualitative methods including ethnography and discourse analysis, drawing on Bourdieu's practice theory and framing theory. Key themes include robotization in hospitals, merger processes, and performance management. Notable projects include leading the Independent Research Fund Denmark-funded 'Robot technology in hospitals' (2023-2026) and Helsefonden's 'Human and robot exchanges in Danish hospitals' (2020-2022). Recent publications explore temporal strategies in automation and labor dynamics in automated healthcare systems. Awards: Best Developmental Paper Award (2024), EGOS 'That's Interesting' Award (2017), Emerald/EFMD Doctoral Research Award (2018) Teaching: Courses in organization theory, leadership, HRM, and research methodology Supervision: Active mentor for academic theses at all levels Labs/Teams: Crossroads of Care and Social Reproduction (CARE) research group

Magnus Rotvit Perlt Hansenمشاهده پروفایل

دانشیار

• Information Systems
• Design Science
• Technology Management
• +۳ مورد دیگر

Magnus Rotvit Perlt Hansen is an Associate Professor at the Department of People and Technology, Roskilde University, specializing in Sustainable Digitalization. His research focuses on design science, information systems, and organizational change, with a particular emphasis on circular design principles, blockchain applications, and technology adoption in SMEs. He has contributed to projects such as 'Game For Green' and 'Blockchain-based digital rights management systems.' Key projects include the five-year 'Game For Green' initiative (2023–2026), exploring gamification for sustainable behavior, and the 'Blockchain-based digital rights management' project targeting the music industry. His work bridges theoretical frameworks (e.g., kernel theory) with practical interventions, such as RPA in SME growth. Hansen has participated in conferences like the European Conference on Information Systems and organized workshops on digitalization. His research outputs include 55 publications across journals, proceedings, and books, with a focus on peer-reviewed contributions. Notably, he has engaged in media discussions on digitalization and received grants for collaborative projects. His activities include peer reviewing, academic organizing, and interdisciplinary collaborations. While no scientific awards are mentioned, his extensive project involvement and publication record highlight his academic contributions to design science and digital innovation.

Rasmus Leck Kæselerمشاهده پروفایل

استادیار

• Biomedical Engineering
• Robotics
• Machine Learning
• +۳ مورد دیگر

Rasmus Leck Kæseler is an Assistant Professor in the Department of Health Science and Technology at Aalborg University, affiliated with The Faculty of Medicine. His work focuses on neurorehabilitation robotics, particularly developing assistive technologies for severely disabled individuals through innovative interfaces like tongue-computer systems and brain-computer interfaces. Key projects include the CRERoB initiative (Center for Rehabilitation Robotics - phase II) and the MultiRob project, which explore multimodal control systems for robotic arms. He collaborates extensively on interdisciplinary research involving mechanical engineering, electrical engineering, and clinical applications. Research interests span neural signal processing (e.g., SSVEP classification), adaptive exoskeleton design, and user-centered interface development for individuals with spinal cord injuries or ALS. Recent publications emphasize improving assistive robotic systems through semi-automation and studying long-term user adaptation patterns. Rasmus participates in academic activities such as the 'Forskningens Døgn' public engagement event and workshops on generative AI in education. He holds positions in the Center for Rehabilitation Robotics and contributes to conferences like the IEEE Engineering in Medicine and Biology Society.

Ole Madsenمشاهده پروفایل

استاد

• Robotics
• Automation
• Industry 4.0
• +۶ مورد دیگر

Ole Madsen is a Professor at the Department of Materials and Production within The Faculty of Engineering and Science at Aalborg University . His research focuses on Robotics and Automation , particularly in 5G Smart Production , AI for Manufacturing , and Industry 4.0 applications. He also holds a part-time position at Adding Robotics , applying his expertise in robot integration for industrial and healthcare settings. Research Interests : Robotics, Automation, AI, Sensor Systems, Modular Manufacturing, Welding Technology, Digital Twins, Human-Centered Robotics, Industry 4.0 His work spans 35+ years with over 205 publications , emphasizing smart production systems and robot-assisted processes . Key contributions include Swarm Production Architectures , 5G-Enabled Robotics , and Human-Robot Collaboration frameworks. He has supervised 10 PhD students and led major projects like RAU (Robot-Assisted Ultrasound) and GINP: Robotics & AI Innovation Network . Scientific Awards : SCAP2020 Best Presentation Award (2020) Ole's 31 projects include AP2030: Aseptic Factory 2030 (pharma production), AddSmart (robotics R&D), and 5G-Enabled Autonomous Systems . His 127 press/media mentions highlight advancements in robotic welding , industrial metaverse , and swarm production . He maintains an ORCID: 0000-0003-2133-2541 with extensive publication records across Swarm Robotics , Modular Manufacturing , and AI-Driven Production .