جستجوی استاد راهنمای دانشگاهی

Stephen Alstrup is a Professor in the Algorithms and Complexity section at the Department of Computer Science (DIKU), University of Copenhagen, Faculty of Science. His research bridges theoretical computer science with practical applications in modern computational challenges. His primary research interests include: Algorithm design and analysis Graph algorithms and data structures Big Data processing techniques Streaming algorithms and Internet distribution Theoretical foundations with practical implementations Alstrup's work demonstrates how theoretical algorithm research can lead to real-world applications, as evidenced by his development of Octoshape technology for large-scale Internet streaming. His research spans from fundamental theoretical problems to applications in Big Data, cloud computing, and information retrieval systems. He has published extensively with 93 research outputs including journal articles, conference proceedings, and books. His recent work focuses on graph spanners, semantic hashing, recommendation systems, and universal graph structures, showing continued productivity in theoretical computer science. Alstrup actively engages with industry and media, contributing to discussions about Big Data applications, technology innovation, and how businesses can collaborate with universities to access cutting-edge knowledge and funding opportunities. His work has been featured in 10 media contributions discussing practical applications of algorithms in education, municipal IT projects, and business innovation.

• Algorithms
• Algorithmics
• Big Data
• +۷ مورد دیگر

Yan Kyaw Tun is a Tenure Track Assistant Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design, located in Copenhagen, Denmark. His research lies at the intersection of wireless communications, edge computing, and artificial intelligence, with a strong focus on next-generation networks (5G/6G), UAV-assisted systems, and intelligent resource management. His educational background includes a Ph.D. in Computer Engineering from Kyung Hee University, South Korea, where he was awarded the Best Ph.D. Thesis Award in 2021, and a Bachelor of Engineering in Marine Electrical Systems and Electronic Engineering from Myanmar Maritime University. Dr. Tun's research interests span Edge Computing , Multi-Access Edge Computing (MEC) , Resource Allocation , Unmanned Aerial Vehicles (UAVs) , Reinforcement Learning , Energy Efficiency , and Integrated Sensing and Communication (ISAC) . His work leverages AI and optimization techniques to enhance the performance of wireless networks, particularly in space-air-ground integrated systems and satellite-HAP environments. The recent publications highlight a clear trend toward intelligent and sustainable networking: the integration of STAR-RIS (Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces), Federated Learning for satellite-HAP systems, and AI-driven optimization for UAV trajectories and beamforming. These works are published in high-impact venues such as IEEE Transactions on Mobile Computing and IEEE ICC , showcasing his leadership in cutting-edge communication technologies. His scientific accolades include: IEEE ComSoc Outstanding Young Researcher Award for EMEA Region (2024) Best Ph.D. Thesis Award (2021) Student Best Paper Award at APNOMS 2019 Korea Network Operation and Management Conference Award (2020) Korea Computer Congress 2018 Award Dr. Tun is actively engaged in the academic community as an advisor and grant participant. Though no direct advisees are listed, his involvement in large collaborative projects—evidenced by co-authorship with senior researchers like Prof. Choong Seon Hong—indicates mentorship and team leadership. He has served on the editorial boards of IEEE Internet of Things Journal , IEEE Open Journal of the Communications Society , and IEEE Network , and has secured research support through participation in IEEE-organized workshops and special issues. He is a key organizer of upcoming workshops, including the 'Sustainable AI for Next-Generation Wireless Communications and Networking' at IEEE GLOBECOM 2025 and the 'Digital Twin Networks' workshop at IEEE/CIC International Communications in China 2025, reflecting his role in shaping future research directions in intelligent and green networking.

• Edge Computing
• Multi-Access Edge Computing
• Resource Allocation
• +۱۲ مورد دیگر

Lars Dittmann is a Professor at the Department of Electrical and Photonics Engineering at the Technical University of Denmark (DTU), leading the Networks Technology and Service Platforms section. His work bridges advanced networking technologies with real-world applications in healthcare and transportation. Academic Role: Professor, Head of Section University: Technical University of Denmark (DTU) Department: Networks Technology and Service Platforms Research Interests: Professor Dittmann specializes in Software-Defined Networking (SDN) , 5G and IoT technologies , and energy-efficient network design , with a focus on applications in telemedicine and transportation systems . His work integrates machine learning for privacy-preserving traffic analysis and explores optical networks for high-bandwidth scenarios. Scientific Contributions: His recent publications emphasize green cellular networks using SDN/NFV/C-RAN, IoT benchmarking for coverage and mobility, and secure edge architectures for railways. Collaborative projects like the Future Patient telerehabilitation program highlight his interdisciplinary impact. Supervision: He supervises PhD candidates such as Radheshyam Singh, focusing on SDN-based IoT security and 5G network optimization. Labs & Projects: Leads initiatives like EXplorative network PLAnnINg and Broadband Trial Integration , addressing challenges in network reliability , emergency communication , and optical data center scaling .

• Software-Defined Networking (SDN)
• Network Function Virtualization (NFV)
• 5G Networks
• +۶ 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.

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

Jan Baumbach is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he leads cutting-edge research at the intersection of computer science, bioinformatics, and biomedical data science. His work integrates machine learning, network biology, and systems medicine to address complex challenges in health and disease. His research interests include Bioinformatics , Machine Learning , Gene Regulatory Networks , Drug Repositioning , Biomedical AI , and Computational Biology . He applies advanced computational methods to analyze large-scale biological data, with applications in cancer, metabolic diseases, dermatology, and infectious diseases. The 15 most recent publications highlight a strong trend toward biomedical artificial intelligence , network-based analysis , and translational bioinformatics . His work spans from foundational machine learning in healthcare to clinical applications in osteoarthritis, bone regeneration, and skin biology. A consistent theme is the integration of multi-omics data and the development of privacy-preserving federated learning frameworks for distributed healthcare systems. Jan Baumbach has been principal investigator on several major research projects, including: EU Horizon2020: Privacy-preserving federated machine learning in distributed healthcare Danish National Research Foundation: ATLAS Center for Functional Genomics of Tissue Plasticity Villum Foundation: Big Data Bioinformatics (Young Investigator Programme) Carlsberg Foundation: Computational profiling of bacterial volatile metabolomes (ProVol) He has supervised 13 PhD students and has an extensive publication record of 262 works. His research has been featured in high-profile media outlets, emphasizing the societal impact of drug repositioning and AI in medicine. He leads a research group focused on computational systems biology , with strong collaborations across Europe in the fields of genomics, metabolomics, and clinical data science.

• Bioinformatics
• Machine Learning
• Computational Biology
• +۷ مورد دیگر

Elizabete Munzlinger is a Research Fellow (industrial PhD) at the IT University of Copenhagen specializing in Data Science, concurrently employed as an Industrial PhD candidate at GN Audio A/S (Jabra) since October 2023. Her work bridges academic research and industry applications in human-computer interaction and AI-driven interface design. Education: Master of Science in Computer Science and Electronic Engineering, Aeronautics Institute of Technology (ITA), completed May 2008. Thesis: "Multimodal and Multi-User Extensions of Graphical and Voice Interfaces based on Speech Technologies and Interactions Models." Bachelor in Computer Science, Universidade do Oeste de Santa Catarina (UNOESC), completed July 2005. Thesis: "The Use of Computers in the Domotic to Help Disabled People." Research Focus: Munzlinger pioneers cross-cultural interaction systems through multimodal interfaces, specializing in hand gesture recognition for virtual/hybrid meetings. Her work integrates machine learning with cultural anthropology to develop universally accessible communication tools, emphasizing accessibility for diverse user populations and voice interface optimization. Research Trends: Recent publications demonstrate a strategic shift toward globally applicable gesture vocabularies addressing cultural diversity in virtual collaboration. Her work synthesizes taxonomy classification, semantic similarity analysis, and foundation models to overcome cross-cultural communication barriers in distributed teams, with strong emphasis on practical Edge AI deployment. Scientific Recognition: Best Poster Extended Abstract Award (July 4, 2024) for gesture-based HCI research at international conference Grant Leadership: Principal Investigator for the Innovation Fund Denmark project "HAND: Identifying Universal Communal Hand Gestures for Virtual and Hybrid Meeting Interaction" (2023-2026; 36 months). This €1.2M initiative develops standardized gesture systems for global virtual collaboration, focusing on cultural adaptation and real-time implementation. Professional Engagement: Active contributor to CVPR 2024 tutorial on Edge AI deployment, demonstrating expertise in translating theoretical AI models into production-ready systems. International collaborations span Denmark, USA, and Brazil through the HAND project consortium.

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Morten Tønsberg Limborg serves as an Associate Professor at the University of Copenhagen's Globe Institute, specifically within the Section for Hologenomics. With extensive international experience as a molecular and evolutionary biologist, he focuses on applying advanced molecular tools to study evolutionary and demographic patterns in marine and salmonid fish species. His research integrates cutting-edge biotechnology to develop sustainable aquaculture practices through microbiome optimization. Dr. Limborg's research interests span molecular biology, evolutionary genetics, and hologenomics with particular emphasis on fish microbiomes and sustainable aquaculture. His work bridges traditional evolutionary biology with contemporary genomic approaches to address pressing issues in marine conservation and food production. He pioneers the application of metagenome sequencing to enhance healthy microbiomes in fish and other production animals, representing a novel intersection of evolutionary biology and sustainable agriculture. His recent publications demonstrate a clear trajectory toward integrating hologenomic approaches across multiple biological systems. The research shows increasing sophistication in analyzing host-microbe interactions, with applications spanning from fundamental evolutionary questions to practical aquaculture solutions. His work consistently connects molecular tools with real-world sustainability challenges, particularly in developing greener production regimes for aquatic species. Dr. Limborg actively participates in scientific communication through the Microbial Connections Podcast series, demonstrating his commitment to making complex hologenomic concepts accessible to broader audiences. His collaborative approach is evident through numerous co-authored publications with international researchers across multiple institutions. His laboratory work focuses on hologenomic approaches to understand host-microbiome interactions, particularly in fish species. The research group utilizes advanced sequencing technologies and computational approaches to analyze complex biological systems, with particular attention to how microbiomes influence host health and evolution. Current projects include investigating how sugar kelp can boost gut health in Atlantic salmon and developing frameworks to study microbiome variation in animal ecology.

• Molecular Biology
• Evolutionary Biology
• Hologenomics
• +۵ مورد دیگر

Mieszko Jan Ferens Michalek is a Researcher at Aalborg University's Department of Electronic Systems within The Technical Faculty of IT and Design. His work focuses on cybersecurity, machine learning, and edge computing with applications in IoT and cloud-edge networks. Education: Master in Telecommunication Engineering (2022), University of Valladolid Bachelor in Telecommunication Engineering Technologies (2020), University of Valladolid Research Interests: Explores machine learning for secure IoT systems, PUF-based hardware authentication, adversarial attack modeling, and simulation environments for cloud-edge networks. Specializes in integrating quantum-resistant cryptography into IoT infrastructure through projects like QUCISAFE. Projects: QUCISAFE (2025-2027) : Develops post-quantum cryptography and QKD for critical infrastructure in cloud-edge-IoT systems. IoTalentum (2020-2025) : Advances IoT training and machine learning for secure IoT ecosystems. Key Contributions: Developed predictive adversarial systems to model attackers targeting PUFs, created the STEROCEN simulation tool for cloud-edge resource management, and proposed MetaLung architecture for secure metaverse healthcare systems.

• Computer Science
• Artificial Intelligence
• Internet of Things
• +۵ مورد دیگر

James Maguire is an Associate Professor at IT University of Copenhagen, affiliated with the Technologies in Practice research group and Center for Climate IT. His work bridges anthropology and computational studies, focusing on the intersection of climate and digital infrastructures, energy systems, and data governance. PhD in Anthropology-STS from IT University of Copenhagen (2017) MSc in Anthropology from University of Copenhagen (2011) BA in Anthropology & Philosophy from National University of Ireland (2006) Maguire's research explores the societal implications of digital industrialization, biotechnology, and energy systems. Key themes include the Anthropocene, climate crisis mitigation, and the governance of big data. His recent work examines digital mistrust, cloud computing ethics, and speculative solutions for environmental challenges. His publications span topics like digital infrastructure , climate policy , and energy planning . Notable collaborations include projects funded by the European Commission and Velux Foundation, with interdisciplinary teams across Denmark and international partners. Maguire contributes to public discourse through media outlets like RESET climate magazine and has participated in committee work for academic recruitment. His work emphasizes ethnographic methods and critical analysis of technological interventions in global crises.

• Climate Change
• Digital Infrastructures
• Energy Studies
• +۷ مورد دیگر

Baoze Wei is an Associate Professor at Aalborg University's Department of Electric Power Systems and Microgrids, part of the Faculty of Engineering and Science. His research focuses on advanced control strategies for power electronics, microgrid stability, and energy management systems. He leads and collaborates on projects such as the Digital Twin-based Reliability Framework for Aviation Systems and Holistic Optimization of Green Fuel-Powered Microgrids. Key contributions include work on distributed energy systems, fault-tolerant architectures, and predictive maintenance for power electronics. His research emphasizes practical applications in renewable integration, smart grids, and industrial electrification. Wei has supervised one PhD student, Q. He, and contributed to projects funded by entities like Horizon JU and Huawei. Notable collaborations include work on hybrid-electric aircraft systems (HECATE) and advanced control algorithms for distributed converters. His research spans technical areas such as voltage source inverters, uninterruptible power systems (UPS), and DC shipboard microgrids. His publications reflect expertise in model predictive control, energy trading strategies, and condition monitoring. Current research trends include data-driven lifetime prediction for power electronics components and optimization of multi-energy systems. He actively participates in international conferences, contributing to both theoretical advancements and real-world system implementations.

• Microgrid Control
• Power Electronics
• Renewable Energy Integration
• +۵ مورد دیگر

Cedomir Stefanovic is a Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design. His research focuses on edge computing, wireless networking, 5G/6G technologies, IoT, smart grids, and bionic limbs. He leads projects like CLIMB (Cloud-connected bionic limbs) and 5G-connected assistive robots, emphasizing assistive robotics and medical technology integration. His work spans random access protocols, latency optimization, and energy-efficient communication systems. With 129 publications (2025: 12; 2024: 8; 2023: 12), his research addresses challenges in industrial IoT, smart grids, and UAV-assisted communication. He has supervised 3 PhD students and actively collaborates internationally. Notable contributions include advancements in deterministic multiple access patterns, AoI-aware scheduling, and bionic limb connectivity. His research is published in IEEE journals and conferences. He hosts guest lecturers and has been featured in media discussions on wireless innovation and smart energy systems. Education: While specific academic credentials are not detailed, his role as a Professor at Aalborg University indicates advanced degrees in electrical engineering or computer science. Research Interests: 5G/6G and IoT networking Edge computing and latency-critical systems Wireless communication protocols (e.g., tree algorithms, NOMA) Smart grid optimization and microgrids Bionic limbs and assistive robotics Age of Information (AoI) minimization strategies Publications: Over 129 papers (2025:12; 2024:8; 2023:12), emphasizing trends in 5G-enabled prosthetics, deterministic access patterns, and industrial IoT optimization. Recent work explores UAV-assisted sensing, D2D communication for smart grids, and deep learning for industrial systems. Funding & Projects: CLIMB (2022–): PI for cloud-connected bionic limbs WindMill (2019–): Machine learning for windmill communication INCOMING (2020–2022): Massive-scale communication innovation Labs/Teams: Edge Computing and Networking group, Classique-Center for Classical Communication in the Quantum Era.

• Wireless Communication
• 5G/6G Networks
• Internet of Things (IoT)
• +۷ مورد دیگر

Israel Leyva Mayorga is an Associate Professor at Aalborg University within the Department of Electronic Systems , part of the Technical Faculty of IT and Design. His research focuses on satellite communications, non-terrestrial networks (NTNs), and IoT connectivity in 5G/6G systems. Key research interests include LEO satellite constellations , random access protocols , energy-efficient wireless systems , and edge computing . He leads or collaborates on projects like SATNEX V WI Y4.6 (ESA) and WITS: Wireless access for heterogeneous IoT Services , addressing challenges in mesh satellite communications and IoT service integration. Awarded the Novo Nordisk Foundation's Prize for Excellence in Technical Science Teaching (2025) and Outstanding PhD thesis (2020) , his work bridges academia and industry, with media coverage on topics like Arctic connectivity and satellite mega-constellations. He serves as an editor for IEEE Wireless Communications Letters and is a member of the one6G consortium. His research outputs span 58 publications , emphasizing satellite routing optimization, IoT traffic management, and energy-autonomous nodes in vehicular networks. Current projects explore semantic image encoding for Earth observation and reconfigurable intelligent surfaces in wireless access.

• Satellite Communications
• Non-Terrestrial Networks (NTNs)
• Internet of Things (IoT)
• +۷ مورد دیگر

Hossam Mohamed Farag is a Tenure Track Assistant Professor in the Department of Electronic Systems at Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on edge computing, 5G networks, industrial IoT, and wireless sensor networks, with an emphasis on optimizing network protocols and resource allocation for mission-critical and smart grid applications. Research Interests: Edge computing and network architecture 5G and beyond communication systems Smart grid communication protocols Machine learning for network optimization Device-to-device (D2D) communication Recent Work Trends: His 2023-2024 publications emphasize Age-of-Information (AoI) aware protocols, multi-access techniques (NOMA/RSMA), and deep learning-driven solutions for industrial IoT and smart grid challenges. Notable contributions include AoI-aware routing strategies for neighborhood area networks and backlog-aware D2D protocols for wireless sensor networks. He leads the 2023-2026 PhD project on 5G-connected assistive robots, collaborating with experts in bionics and robotics. This project explores 5G-enabled assistive technologies for healthcare and human-robot interaction. Key Collaborations: Works with institutions like Aalborg University's Department of Electronic Systems and external partners on 5G, IoT, and edge computing initiatives.

• Industrial Internet of Things
• Wireless Sensor Networks
• 5G Networks
• +۵ مورد دیگر

Sokol Kosta is an Associate Professor in the Department of Electronic Systems at the Technical Faculty of IT and Design, Aalborg University, Copenhagen, Denmark. His research focuses on edge computing, mobile cloud computing, cybersecurity, privacy, and the societal impact of digital technologies, particularly in public service media and data protection regulation. He is affiliated with the Cyber Security Group and contributes to initiatives such as 'AI for the People'. His research interests include edge and fog computing, computation offloading, Internet of Things (IoT), Internet of Floating Things, GPGPU acceleration, blockchain-based systems, privacy-preserving technologies, GDPR compliance, and public service media digital transformation. His work bridges technical innovation with policy and societal implications. His publications span from 2010 to 2025, with a strong presence in high-impact venues such as IEEE INFOCOM, IEEE Transactions on Mobile Computing, and The Web Conference. The articles reflect a consistent focus on mobile and edge computing systems, performance modeling, security, and privacy, increasingly incorporating societal and policy dimensions, especially post-GDPR. Trends include computation offloading optimization, decentralized systems, and empirical studies on web tracking and data governance. He has received 14 prizes and recognitions for his research contributions, though specific awards are not detailed in the provided text. He has supervised PhD students, including Jannick Kirk Sørensen, and has been involved in significant research projects such as the 'European Open Web Privacy Measurement' project (2017–2020), which examined GDPR's impact on third-party web services. He has presented his work internationally, including at The Web Conference 2019 in San Francisco, and has been featured in media coverage discussing data privacy compliance of Danish public websites. His lab and team activities are centered around the Cyber Security Group and collaborative projects involving distributed computing, edge AI, and privacy measurement.

• Edge Computing
• Mobile Cloud Computing
• Cybersecurity
• +۱۷ مورد دیگر

Lei You is an Assistant Professor in Applied Mathematics at the Department of Engineering Technology, Technical University of Denmark (DTU), located in Ballerup, Denmark. With a Ph.D. in Computer Science specializing in Mathematical Optimization from Uppsala University (2019), Dr. You has established expertise in distributed data analytics, data-driven optimization, and machine learning interpretability. Dr. You's research focuses on the theories of interpretability and efficiency of machine learning models toward On-Device AI. Key areas of investigation include: Strategies to streamline complex models without performance loss Unraveling the intricate mechanisms of decision-making models Understanding the synergy between model simplification and explainability Distributed data analytics and federated learning systems Optimization techniques for wireless communication and edge computing Dr. You's recent publications demonstrate a strong focus on counterfactual explanations, optimal transport theory, neural network pruning, and multi-objective optimization for federated learning. The research spans applications from explainable AI to 6G-satellite systems and energy-efficient base station management. A notable trend is the integration of causal inference and distributional analysis in machine learning optimization problems, with significant contributions to federated learning efficiency and robustness. Scientific awards and recognition: Doctoral Dissertation Award for Operations Research in Telecommunications and Network Analytics awarded by INFORMS in 2020 Dr. You actively supervises student projects and research activities, with recent supervisions including work on remote sensing assessment, network pruning techniques, Microsoft Graph API optimization, and applications of large language models in business contexts. Current research projects include 'Machine Learning for Beehives Monitoring' and 'InnoTech - TaskForce,' focusing on practical applications of machine learning in environmental monitoring and digital transformation. Dr. You maintains active industry connections through previous roles at Bolt, Wolt (Doordash), and The Boston Consulting Group, ensuring research relevance to real-world challenges.

• Mathematical Optimization
• Distributed Data Analytics
• Data-Driven Optimization
• +۹ مورد دیگر