Cicek Cavdar is an Associate Professor at the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology , Sweden. She leads the Intelligent Network Systems research group and specializes in Telecommunication Networks , with a focus on Beyond 5G/6G Mobile Networks , Energy Efficiency , and AI-Assisted Network Management . PhD in Computer Science (2009) from University of California, Davis and Istanbul Technical University Her research spans Cell-Free Massive MIMO , Reconfigurable Intelligent Surfaces (RIS) , UAV Communication Systems , and Green Network Technologies . She actively contributes to 6G Network Architecture and Non-Terrestrial Networks , including satellite and aerial systems. Recent publications highlight AI-driven network optimization for handover management, energy-aware resource allocation , and multi-agent reinforcement learning in complex communication environments. She teaches advanced courses in Communication Systems , Machine Learning , and Software Engineering at KTH.
Mariano Scazzariello is a Lecturer at KTH Royal Institute of Technology, Sweden, affiliated with the School of Electrical Engineering and Computer Science and the Department of Network and Systems Engineering. He teaches the course 'Network Systems with Edge or Cloud Datacenters (IK2227)'. His research focuses on advanced networking topics including machine learning in networks, high-speed packet processing, network emulation, and software-defined networking innovations. His work spans contributions to network emulation tools like Kathará and Megalos, stateful packet processing at terabit scales, and leveraging large language models (LLMs) for network configuration and vulnerability detection. Recent research emphasizes low-latency protocols (e.g., SRv6/DetNet integration) and GPU-centric networking on commodity hardware. Mariano’s publications (2020–2025) highlight expertise in network function virtualization, ASIC-based switching, and optimizing network configurations through AI-driven approaches. He has pioneered frameworks for evaluating routing protocols and virtualizing large network scenarios at scale.
Zhibo Pang is an Adjunct Professor at KTH Royal Institute of Technology's Department of Intelligent Systems (EECS) and Senior Principal Scientist at ABB Corporate Research Sweden. His work focuses on digital transformation in industry and healthcare, spanning robotics, AI, control systems, and wireless communication. He leads projects in embodied intelligence, Industry 4.0, and Healthcare 4.0, with 23 granted patents and over 120 journal papers. Education: PhD in Electronic and Computer Systems (KTH, 2013), MBA in Innovation & Growth (University of Turku, 2012). Key Roles: IEEE Technical Committee Chair, Editor of 6 IEEE journals, ABB Inventor of the Year (2016, 2018, 2021). Research Interests: Robotics safety, wireless automation, federated learning, digital twins, and IoT security. Recent Projects: Cloud-fog automation frameworks, robot skin systems for healthcare, and latency-aware industrial control. His work bridges academia and industry through cross-functional collaborations.
Erik G. Larsson is a Professor and Head of the Division for Communication Systems within the Department of Electrical Engineering (ISY) at Linköping University (LiU), Sweden. He joined LiU in September 2007 and has previously held academic and research positions at the Royal Institute of Technology (KTH), University of Florida, George Washington University, and Ericsson Research. Research Interests: Enabling technologies for 6G wireless communication Statistical inference and signal processing Network science and complex networks Decentralized and federated machine learning over networks Physical layer security and privacy Energy-efficient digital signal processing His research group, active in areas like RadioWeaves and massive MIMO, focuses on robust, efficient, and secure wireless connectivity. Recent publications highlight trends in decentralized learning, resource allocation in wireless networks, and the integration of AI into mobile networks, particularly through projects like 'Turning the Air into an AI Computer' funded by the Knut and Alice Wallenberg Foundation. Scientific Awards and Honors: IEEE Signal Processing Magazine Best Column Award (2012, 2014) IEEE ComSoc Stephen O. Rice Prize (2015) IEEE ComSoc Leonard G. Abraham Prize (2017) IEEE ComSoc Best Tutorial Paper Award (2018) IEEE ComSoc Fred W. Ellersick Prize (2019) IEEE SPS Donald G. Fink Overview Paper Award (2023) IEEE Fellow Member, Royal Swedish Academy of Sciences (KVA) Gyllene Moroten Best Teacher Award (2021) Advising and Grants: He has supervised numerous Ph.D. and Licentiate students, many of whom now hold positions at leading industry and academic institutions. His research is currently funded by major organizations including the Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research (SSF), ELLIIT, Security-Link, Swedish Research Council (VR), and EU Horizon 2020 (H2020-SNS-6GTandem). Previous sponsors include VR, KVA, NSF, ORAU, and multiple EU FP7 and H2020 projects (e.g., MAMMOET, REINDEER, 5G-Wireless). Leadership and Service: He has served as Associate Editor for IEEE Transactions on Communications and IEEE Transactions on Signal Processing, chaired technical committees and steering committees in IEEE Signal Processing Society, and held leadership roles in major conferences such as the Asilomar Conference on Signals, Systems and Computers. He was a Visiting Fellow at Princeton University in 2015.
Professor Ahmed Hemani is a faculty member at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology, affiliated with the Digital Futures Faculty. He holds the role of PI for the project 'New Chip Architectures for Industrial Vision' and leads research in reconfigurable computing, memristor-based systems, and hardware acceleration for AI and edge computing. His work bridges theoretical computer science with practical VLSI design and embedded systems development. He actively contributes to cross-disciplinary initiatives at Digital Futures, a joint center with Stockholm University and RISE Research Institutes of Sweden focused on digital innovation. His research emphasizes scalable FPGA/HPC architectures, low-power neuromorphic systems, and optimization techniques for custom silicon solutions. Current projects include a Lego-inspired edge AI framework and memristor-driven MIMO acceleration. Teaching responsibilities span advanced courses in SOC design, digital system verification, and embedded systems. He supervises advanced-level degree projects across computer engineering and ICT innovation specializations, emphasizing hands-on hardware-software co-design methodologies. Recent publications highlight innovations in memristor applications, FPGA-based acceleration, and reconfigurable architectures for neural networks and bioinformatics. His work addresses challenges in dark silicon utilization, energy-efficient computation, and high-performance embedded systems.
Monowar Bhuyan is an Associate Professor in the Department of Computing Science at Umeå University, Sweden, leading the Cyber Analytics and Learning Group within ADSLab. He holds a Ph.D. in Computer Science from Tezpur University and has held academic positions at Assam Kaziranga University and Umeå University. His research focuses on machine learning, anomaly detection, edge AI, and distributed systems security. He has secured over 35 MSEK in grants from WASP, STINT, and EU Horizon programs. Education Ph.D. in Computer Science and Engineering, Tezpur University (2014) M.Tech. in Information Technology, Tezpur University (2009) B.E. in Computer Science and Engineering, IETE (2007) Research Interests Distributed/Federated/Responsible Machine Learning Cybersecurity and Anomaly Detection in Edge Clouds AI for DDoS Defense and Cyber Resilience Edge AI and Serverless Computing Recent Contributions His recent work addresses secure federated learning, DDoS attack detection in cloud-edge systems, and responsible AI. Key publications include novel frameworks for VSI-DDoS detection and federated learning optimizations. Awards & Grants Best Paper Awards at ICONIP 2023 and ACM ICACCI 2012 WASP NEST Grant (AIR2 Project, 5 MSEK) EU Horizon Europe Grant (SovereignEdge.Cognit, 8.27 MSEK) Lab & Collaborations He leads the Cyber Analytics and Learning Group (ADSlab), collaborating with institutions like KTH, Linköping University, and Nara Institute of Science and Technology (NAIST). The lab focuses on AI-driven security solutions for distributed systems.
Zinat Behdad is a Researcher at the Division of Communication Systems within the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology , Stockholm, Sweden. Her work bridges wireless communications and sensing technologies. Education: Master of Science in Electronics and Communications Engineering, Isfahan University of Technology, Iran (2017) Research Interests: Wireless Communications Integrated Sensing and Communication (ISAC) Cell-Free Massive MIMO URLLC (Ultra-Reliable Low-Latency Communication) Energy Efficiency RF Energy Harvesting Article Trends: Her publications emphasize Cell-Free Massive MIMO systems, with a focus on integrated sensing and communication (ISAC) , mmWave technology , and energy efficiency . Key areas include target detection , power allocation , and URLLC optimization , reflecting her work on balancing sensing accuracy and communication reliability. The 2018 paper explores RF energy harvesting in IoT networks through cooperative strategies. Affiliation and Lab: She is based at the Division of Communication Systems , KTH EECS, working on advanced wireless technologies with applications in security, energy sustainability, and 5G/6G networks.
Anna Brunström is a Full Professor and Head of the Distributed Intelligent Systems and Communications Research Group (DISCO) at Karlstad University's Department of Computer Science. She holds a part-time role as a Researcher at the University of Malaga's Institute of Software Engineering and Technologies (ITIS). Her research focuses on computer networking, Internet architectures, low latency communication, and 5G/6G mobile systems. She leads the nationally funded DRIVE initiative and collaborates on European projects like 6G-PATH. She actively contributes to IETF standardization, notably as a former rmcat WG chair. Her work spans over 200 publications, emphasizing network measurement, latency optimization, and multipath protocols. Education: Ph.D. (1996) and M.Sc. (1993) from College of William & Mary, B.Sc. (1991) from Pepperdine University. Research Interests: Distributed systems, IoT networking (NB-IoT), satellite communication (Starlink), machine learning for positioning, and transport protocols (QUIC, MPTCP). Recent work includes latency-aware scheduling, 5G/6G performance analysis, and edge computing frameworks. Publications highlight trends in: 1) Satellite network throughput modeling, 2) 5G/6G architecture validation, 3) Machine learning applications for positioning and network analysis, 4) Cross-layer optimization of latency-critical services. Collaborations with industry and academia drive applied research in smart grids, healthcare, and automotive communication. Labs/Teams: DISCO group at Karlstad University, leading the DRIVE research profile and 6G-PATH consortium involvement.
Simone Ferlin is an Adjunct Senior Lecturer at Karlstad University and a Senior Performance Engineer. She holds a PhD in Computer Science from Simula Research Lab and Universitetet i Oslo (2017), focusing on robustness in multipath transport protocols like MPTCP. Her research spans network performance, security, and congestion control in mobile/5G networks and the Internet. She collaborates actively with academia and industry, co-supervising students in areas such as edge computing, container orchestration, and distributed systems. Affiliations: Department of Informatics, Karlstad University; Red Hat Research; Ericsson R&D. Education: PhD (2017), Simula/UiO; Master’s and Undergraduate studies emphasized networking and electronics. Her work includes projects like AIDA (AI-driven edge networking) and DRIVE (latency-sensitive mobile services). She has published over 50 papers on topics like QUIC, eBPF, and containerized microservices. Awards include the Best Paper at IEEE ICIN 2021 and ANRP 2025 Prize. Teaching responsibilities include Future Internet Design and Service Quality . Advising spans 15+ students across institutions like TU Berlin, KTH, and Unifesp. She chairs conferences (e.g., ACM SIGCOMM 2025) and serves on editorial boards (IEEE Communications Magazine). Key interests: network observability, low-latency protocols, and sustainability in networking.
Marco Chiesa is an Associate Professor at the KTH Royal Institute of Technology in the Intelligent Network System Lab (INSight) group under the Division of Software and Computer Systems . His research focuses on computer networking, particularly Internet protocols and architectures, with emphasis on security, privacy, network design optimization, and Software Defined Networking (SDN) approaches. Current research areas: SDN, IXPs, stateful packet processing, network monitoring Teaching roles: Advanced Internetworking (IK2215), Computer Hardware Engineering (IS1200), Network Systems with Edge or Cloud Datacenters (IK2227) Email: mchiesa@kth.se Recent publications highlight advancements in high-speed packet processing, network security, and SDN applications. Key trends include leveraging programmable switches for stateful operations, improving BGP hijacking detection, and optimizing network monitoring on multi-pipeline architectures.
Ki Won Sung is an Associate Professor at KTH Royal Institute of Technology, specializing in wireless communication systems and network optimization. His research focuses on 5G/6G technologies, integrated sensing-communication systems, cell-free massive MIMO, and stochastic network modeling. Research interests include: Wireless network architecture design and optimization Resource allocation in multi-user communication systems Integrated sensing and communication (ISAC) Stochastic modeling of ultra-dense networks Energy-efficient communication protocols Millimeter wave and massive MIMO systems His recent publications demonstrate strong emphasis on beyond-5G systems, particularly cell-free massive MIMO deployments and URLLC applications. Research trends show consistent focus on network optimization through advanced signal processing, geometric decomposition methods, and cross-layer protocol design. Teaching activities include course management and examination for multiple degree projects and core courses: Communication Systems (IK2200) Mathematical Statistics (IX1501) Mobile Networks and Services (IK2560) Radio Networks (IK2510) Stochastic Simulation (II2206) Wireless Systems (IK1330)
James Gross is a Professor at the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm. He leads research in mobile systems and networks, with a focus on 5G/6G, edge computing, and performance evaluation. He is Associate Director of KTH's Digital Futures center and a board member of the Innovative Centre for Embedded Systems. Previously, he directed the ACCESS Linnaeus Centre (2016–2019) and was Assistant Professor at RWTH Aachen University. PhD, TU Berlin (2006) Studies: TU Berlin, UC San Diego His research lies at the intersection of wireless networking, edge computing, and mathematical performance modeling. Key areas include ultra-reliable low-latency communications (URLLC), age-of-information, network calculus, and resource allocation. He applies these to 5G/6G, cyber-physical systems, and industrial IoT. His work combines theoretical modeling with real-world implementation and standardization impact. The recent publications highlight a strong focus on deterministic and reliable communications for future networks. Topics include hierarchical inference at the edge, age-of-information optimization, finite blocklength coding, and integration of TSN with wireless systems. There is a clear trend towards AI/ML for resource management and semantic communications, reflecting the evolution of intelligent edge networks. Best Paper Award, ACM MSWiM 2015 Best Demo Paper Award, IEEE WoWMoM 2015 Best Paper Award, IEEE WoWMoM 2009 Best Paper Award, European Wireless 2009 ITG/KuVS Dissertation Award, 2007 James Gross has supervised PhD students such as Samie Mostafavi and advises numerous master's projects. His research has been funded by national science foundations in Germany and Sweden, the ICT TNG SRA, Linnaeus ACCESS Centre, DFG-funded UMIC Centre, German Ministry of Science, and various industry partners. His work has led to patents and influenced wireless standards. He is involved in initiatives like the TECoSA project on trustworthy edge computing and organizes summer schools on Edge AI and 6G. His lab conducts experimental research on edge computing testbeds (e.g., Ainur, ExPECA) and wireless performance evaluation.
Johan Eklund is an Associate Professor in the Department of Computer Science at Karlstad University. He also serves as the Director of Undergraduate Studies and is finalizing his PhD thesis while working part-time as a lecturer. His research focuses on performance issues in computer communication, particularly latency reduction in real-time applications over IP networks, with a strong emphasis on transport layer protocols. He has collaborated extensively with regional industry through initiatives like 'Campus Connect.' Education: B.Sc. (2001) and M.S. (2004) in Computer Science from Karlstad University, followed by doctoral studies. Teaching responsibilities include 'Introduction to Programming and Data Processing' and supervision of bachelor's projects in Computer Science. Research interests span real-time systems, IoT communication, energy efficiency in networks, and transport layer optimization. His recent work includes evaluating NB-IoT energy efficiency and latency reduction in SCTP-based protocols. He has over 20 publications since 2004, with a focus on improving network performance and reducing energy consumption in modern communication systems. Notable collaborations include projects with SNITS (Swedish National Infrastructure for Computing) and industry partners. His work bridges academia and industry, addressing practical challenges in network design and implementation.
Aamir Mahmood is an Associate Professor at the Department of Computer and Electrical Engineering at Mid Sweden University and an Adjunct Professor at NUST, Pakistan. His research focuses on 5G/6G wireless communication , Industrial IoT , RF interference management , and time synchronization . Education: B.Sc. NUST (2002), M.Sc. and Ph.D. Aalto University (2008, 2014) Collaborations: Nokia Research Center, IEEE Sweden VT-COM-IT His recent work explores STAR-RIS for 6G IoT, NOMA for industrial networks, and deep reinforcement learning in MEC systems. Key trends include ultra-reliable communication for industrial automation and interference management in heterogeneous networks. Awards : IEEE WCNC’13 Best Paper Ericsson Research Foundation Grant Nokia Foundation grant STINT grants IEEE Sweden VT-COM-IT Best Student Journal Paper Award Swedish Institute funding Interreg Aurora funding Awarded 80+ peer-reviewed publications and active in IEEE leadership roles.
Hasan Basri Celebi is a researcher at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science (EECS), active in the field of wireless communication systems. His work focuses on ultra-reliable low-latency communication (URLLC) for mission-critical IoT applications, with a particular emphasis on decoding complexity constraints and computational efficiency in next-generation networks. PhD in Electrical Engineering from KTH (2021) Key research areas: Channel coding, Finite blocklength regime, Industrial IoT, Signal processing, Biomedical sensor development Celebi's publications span telecommunications journals and conferences, addressing theoretical limits in low-latency communication and practical implementations for complexity-constrained receivers. His interdisciplinary work includes developing medical devices like transcutaneous bilirubinometers and optical probes for diffuse spectroscopy applications. A notable grant from the Swedish Foundation for Strategic Research (SSF) supported his work on low-complexity receivers.
