Jan Madsen is a Professor at DTU Compute, Technical University of Denmark, and Head of the Embedded Systems Engineering section. His research focuses on system-level modeling and design of embedded computing systems, particularly cyber-physical systems, microfluidic biochips, and synthetic biology applications. Develops design automation tools and methodologies for embedded systems Supervises numerous PhD students and leads major research projects Research Interests Key areas include: Embedded systems-on-a-chip Cyber-Physical Systems (Internet-of-Things) Microfluidic Lab-on-Chip devices Synthetic biology with molecular computing Design, modeling, and optimization of complex systems Scientific Awards DATE Fellow (2019) IEEE CEDA Outstanding Recognition (2019) DTU Scientific Advise Award (2013) Best Paper Awards at MECO (2013) and CASES (2009) Jorck’s Foundation Research Award (1995) Publications His 14+ journal papers and 115+ conference papers demonstrate expertise in: SystemC-based modeling frameworks Energy-aware sensor networks Self-healing eDNA architectures Microfluidic biochip synthesis RTOS modeling and MPSoC exploration
Remus Teodorescu is a Professor at AAU Energy , Aalborg University , specializing in Power Electronics System Integration and Materials . His work bridges Lithium-Ion Batteries , Modular Multilevel Converters , and Smart Battery Systems . Education : Not explicitly mentioned in the text. Research Interests focus on Battery Management Systems , AI-Driven Energy Optimization , and Power Electronics for renewable energy integration. Key projects include Digital Twin for Lithium-Ion Batteries and BMS-DC for Data Centers . Recent Publications (2025) emphasize Finite Set MPC , Gradient Descent Optimization , and AI in Battery Parameter Estimation . His 2024 work explores Physics-Informed Neural Networks and Fault-Tolerant Converters . Scientific Awards : Villum Foundation Grant (313 million kroner, 2021) Named world's best in electrical engineering (2023) Advising includes supervising PhD projects on AI-Accelerated Battery Twins and Data-Driven SOH Estimation . Collaborations span Energy Cluster Denmark and Villum Fonden .
Qiongxiu Li is a Tenure-Track Assistant Professor in the Cyber Security group at Aalborg University's Copenhagen campus, part of the Technical Faculty of IT and Design. Her research focuses on cybersecurity, distributed optimization, privacy/security, and federated learning. She has authored/co-authored 38 papers in top-tier venues including IEEE Transactions on Information Forensics and Security, ICLR, and EUSIPCO. Education: PhD in Privacy and Security from Aalborg University (2018-2021). Notable achievements include winning the EUSIPCO 2020 3MT Contest and co-delivering a tutorial on privacy-preserving distributed optimization at EUSIPCO 2024. She actively reviews for conferences like NeurIPS, ICLR, and journals such as TPAMI and TIFS. Research Themes: Privacy-preserving distributed algorithms, federated learning security, differential privacy, and adversarial machine learning. Recent Trends: Focus on securing AI systems (e.g., LLM vulnerabilities, federated clustering privacy), quantization for privacy, and theoretical bounds in decentralized learning. Awards: 2020 EUSIPCO 3MT Winner (outstanding finalist in EURASIP's annual doctoral research competition). Grants/Projects: Co-PI of the AI:SECURITY project (2025-2029) addressing AI security threats like phishing and malicious actors. Labs/Teams: Leads the Cyber Security group at Aalborg's Copenhagen campus, focusing on theoretical and applied research in secure distributed systems.
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 .
Hao Hu is a Senior Researcher at the Department of Electrical and Photonics Engineering at the Technical University of Denmark (DTU). He leads the Photonic Integrated Circuit based Systems Group and is active in the field of silicon photonics for optical communications. His research focuses on integrated photonic systems, including optical phased arrays, LiDAR, and neural network applications. Research Interests: Hao Hu's work spans optical beam steering , integrated photonics , silicon photonics , and optical wireless communications . He explores energy-efficient photonic components and optical computing platforms for machine learning, contributing to advancements in LiDAR and optical signal processing. Recent Publications: His recent articles highlight innovations in digital optical computing , thermo-optic phase shifters , and solid-state beam steering , reflecting expertise in silicon photonics and machine learning applications. The ACS Photonics 2025 article emphasizes ultra-low loss design methodologies, while the Journal of Lightwave Technology 2025 paper addresses 2D beam steering for LiDAR systems. Students: Hao Hu supervises multiple PhD students, including T. E. Rude, X. Zhu, Y. Han, X. Long, and P. Nay, across projects like integrated optical phased arrays and silicon photonics for neural networks.
Shashi Raj Pandey serves as Assistant Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design, Denmark. His research is anchored in the Connectivity section and Connectivity Classique-Center for Classical Communication in the Quantum Era, with office location at Fredrik Bajers Vej 7C, C1-111, 9220 Aalborg Øst. His core research spans Network Economics, Game Theory, and Wireless Networks, with specialization in Decentralized Machine Learning and Semantic/Goal-oriented Communications. Current work integrates Digital Twin technologies with 6G systems for industrial automation and earth observation, emphasizing resource-efficient protocols for Internet of Things and edge intelligence applications. Recent publications (2024-2025) reveal a clear trajectory toward AI-6G convergence, featuring semantic communications for satellite imaging, game-theoretic network resource allocation, and digital twin implementations for autonomous systems. Key themes include communication efficiency in distributed learning and physical-digital world integration. Notable recognitions include: Best PhD Thesis Nominee (2021) Excellent Paper at Korea Software Congress, KIISE 2021 Student Best Paper Award at APNOMS 2019 Best Paper at Korea Software Congress, KIISE, 2018 Brain Korea 21st Century Plus Fellowship Academic service includes external PhD examination for EU SNS projects and peer review for premier conferences (AAAI, ICLR, ICML). His lab work within the Connectivity Classique-Center explores classical communication frameworks applicable to quantum-era networks, with focus on semantic information theory and decentralized network architectures.
Petar Popovski is a Professor at the Department of Electronic Systems within the Technical Faculty of IT and Design at Aalborg University, Denmark. His research focuses on next-generation wireless communication systems, with a strong emphasis on ultra-reliable low-latency communication (URLLC), Internet of Things (IoT), multiple access, and 6G technologies. He leads several high-impact research projects, including the Classique - Center for Classical Communication in the Quantum Era funded by the Danish National Research Foundation and WATER (Wireless Architectures for intelligent and Trusted connectivity in the posT-5G ERa) supported by Villum Fonden. His research interests span key areas in modern communication theory and systems, including random access , non-terrestrial networks , satellite communication , and machine learning for reliable communication . He is actively involved in advancing the integration of sensing and communication, digital twin technologies, and quantum-era classical communication frameworks. The recent publications highlight a strong trend toward deterministic and reliable access in wireless networks, integration of sensing and communication for industrial automation, and novel physical-layer techniques using reconfigurable intelligent surfaces. These works are published in top IEEE journals such as IEEE Transactions on Communications , IEEE Transactions on Haptics , and IEEE Transactions on Vehicular Technology . Award highlights include the Best Student Paper Award (2021) , recognizing his mentorship and collaborative research excellence. Prof. Popovski serves as a principal investigator (PI) and supervisor in multiple research projects, securing significant funding from national and international bodies such as the Danish National Research Foundation and the European Space Agency (ESA). He hosts visiting researchers regularly and contributes to scientific leadership through editorial roles and conference participation. He is a key figure in the Connectivity section at Aalborg University and leads cutting-edge research in future wireless systems, contributing to both theoretical foundations and practical implementations in smart infrastructure, space communication, and dependable 6G networks.
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.
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 .
Klaus Ingemann Pedersen is a Professor in the Department of Electronic Systems at the Technical Faculty of IT and Design, Aalborg University, Denmark. His research focuses on wireless communication networks and dependable wireless communications with substantial contributions to 5G-Advanced and 6G technologies. His research interests include: Wireless Communication Networks Dependable Wireless Communications 5G-Advanced Technology 6G Networks Radio System-Level Simulations Ultra-Reliable Low Latency Communication Heterogeneous Networks Professor Pedersen's recent work demonstrates cutting-edge research in next-generation wireless systems, with particular emphasis on deep reinforcement learning applications, link adaptation techniques, and system-level simulations. His publications show consistent high-impact output with 152 total publications spanning from 2012 to 2025, reflecting ongoing productivity and relevance in the rapidly evolving field of wireless communications. His notable achievements include: 5G-prisen (The 5G Award) received on October 23, 2019, shared with E. Mogensen and I.R. Larrad Professor Pedersen has supervised 8 PhD students according to institutional records. His research has practical applications in wireless communication, as evidenced by his involvement in patented technology 'Method and apparatus for wireless communication' which delivers social impact and quality of life improvements. His work shows strong international collaboration across multiple countries as indicated by the research network visualization.
Per Lynggaard is a Professor of Electronics at the Technical University of Denmark (DTU) , leading the B.Eng. program in Electronics. Previously, he held an Associate Professor role at Aalborg University, combining academic excellence with a robust industrial career in technical-scientific research and development. Education: M.Sc. in Electrical Engineering and Information Technology (EE and IT) Ph.D. in Electronics from Aalborg University Research Interests: Focus on Integrated Circuit Design, Wireless Sensor Networks (WSN), Machine Learning, IoT, and Smart City Technologies . His work emphasizes energy-efficient systems, cybersecurity in IoT, AI-driven interference mitigation, and sustainable energy harvesting solutions. He has contributed to UN Sustainable Development Goals through projects addressing smart infrastructure and environmental monitoring. Projects & Collaborations: Leads and participates in EU-funded initiatives such as InnoTech (2023–2025) for green transition solutions and TransportTech (2023–2026) for Industry 4.0 logistics. Active in cybersecurity research via projects like Jamming Against Critical Wireless Communication , aiming to protect critical infrastructure. Awards: Recognized with multiple honors and rewards during his industrial career, though specific names are not listed. His work has been cited widely, with notable impact in IoT security and energy-efficient systems. Advising & Grants: Supervises Turnip T.N. in a PhD project on 6G security protocols. Engaged in securing funding for projects like F2D2: The Community for Dynamic Data (2021–2030), focusing on dynamic data systems and cybersecurity. Labs & Teams: Collaborates in interdisciplinary teams such as the InnoTech TaskForce and F2D2 Community , advancing IoT and AI integration. His research bridges academia and industry, with outputs spanning smart cities, healthcare IoT, and sustainable energy systems.
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 .
Amir Babaki is an Assistant Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark. His research focuses on power electronics, wireless power transfer, and high-efficiency converter design for electric vehicle applications. University: University of Southern Denmark School: Institute of Mechanical and Electrical Engineering Rank: Assistant Professor Email: amirbabaki@sdu.dk Research Interests Babaki's work centers on power electronics, specifically front-end converters, wireless power transfer (WPT), and high-frequency resonant converters. His research explores efficiency optimization in dynamic WPT systems for electric vehicles (EVs), including control strategies for power factor correction and voltage regulation. He also investigates integrated magnetic structures for misalignment tolerance and develops predictive control methods without communication or model dependencies. Research Projects He contributes to projects like HiCoMMID (2021-2024) on motor integrated drives and HPC (2024-2027) for ultra-high efficiency DC-DC converters in high-power charging. These projects intersect with automotive engineering, energy efficiency, and converter design optimization. Teaching Babaki supervises Master's theses and teaches courses in power electronics and electrical engineering, including PE2 and ELTR3 modules related to converter technologies and wireless power systems.
Paul Pop is a Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). He holds the position of Professor within the Embedded Systems Engineering group at DTU Compute. His academic journey includes a Ph.D. in Computer Systems from Linköping University, Sweden (2003), followed by roles as an Assistant Professor there before joining DTU in 2006. Dr. Pop's research focuses on systems engineering methodologies for embedded and cyber-physical systems, with emphasis on modeling, analysis, optimization, and real-time guarantees. His work addresses challenges in time-sensitive networking (TSN), automotive systems, industrial automation, and fog computing. Key application areas include safety-critical systems, mixed-criticality architectures, and sustainable industrial IoT solutions aligned with UN SDGs. He leads major research projects such as G3C (Green Computing & Communication Continuum), TRANSACT (Safety-Critical Cyber-Physical Systems), and AgroRobottiFleet (Agricultural Robotics). His contributions span 194 publications in journals/conferences and 31 active/completed projects, emphasizing interdisciplinary collaboration. Dr. Pop advises doctoral students in embedded systems and serves as Principal Investigator on EU-funded initiatives. His technical expertise includes TSN configuration tools (TSNConf), fog computing platforms (FORA), and microfluidic biochip design. He actively contributes to industry standards through IEEE 802.1 TSN working groups and collaborates internationally with institutions like Nordic Innovation and EU Horizon programs.
Preben E. Mogensen is a Professor at Aalborg University's Department of Electronic Systems within The Technical Faculty of IT and Design. His research focuses on wireless communication networks, 5G/6G technologies, and their applications in smart production and robotic systems. He leads and collaborates on projects involving cellular networks, unmanned aerial vehicles (UAVs), and interference coordination. Research interests include cellular network optimization, machine learning-driven beam selection, and vehicular communication systems. His work addresses challenges in path loss analysis, antenna design, and edge-cloud integration for real-time robotic control. Recent projects include 5G-enabled autonomous robotics and cognitive radio concepts for beyond-femtocells. Mogensen has received the 2019 5G-prisen award recognizing contributions to Danish telecommunications advancements. He has published over 520 research outputs, with a focus on high-impact journals and conferences. Active collaborations span academia and industry, including work on 5G Smart Production and community-driven IoT solutions. He hosts guest researchers and advises on projects involving 5G implementation in factories and emergency response systems. His lab environments include facilities for testing advanced radio resource management and network synchronization in industrial settings.
