Find Academic Supervisors

• Wireless Communication
• Wireless Sensor Networks
• Industrial IoT
• +5 more

Mikael Gidlund is a Full Professor of Computer Engineering at Mid Sweden University in Sundsvall and holds an adjunct professorship at Beijing Jiaotong University, China. He serves as head of the Computer Engineering subject and program manager for the international MSc program in Computer Engineering. His academic journey includes a Ph.D. in Electrical Engineering from Mid Sweden University (2005), followed by roles at ABB Corporate Research (2008-2014) where he led wireless technologies research. Dr. Gidlund's research spans Wireless Communication, Industrial IoT, 5G/6G Networks, and Network Security . His group focuses on AI/ML for beyond-5G wireless communication, time-critical industrial applications, and IoT security. Current research themes include Future Wireless Networks (5G/6G) using AI/ML, Time-and mission-critical wireless communication, Industrial IoT, and IoT Security. His work demonstrates strong interdisciplinary connections between wireless systems, industrial automation, and security. His publication portfolio includes over 200 scientific articles and 20+ patents. Recent publications show a clear trend toward AI/ML integration in wireless systems, NOMA techniques, RIS technologies, and security solutions for industrial applications. The research output demonstrates strong international collaboration across six continents. Best Paper Award at IEEE International Conference on Industrial IT (2014) Co-author of IEEE Sweden VT-COM-IT Joint Chapter Best Student Journal Paper Award (2022) Dr. Gidlund actively mentors 6 current PhD students and has supervised 16 former PhD students who now hold positions at institutions including Ericsson, Lund University, Aalborg University, and Mid Sweden University. His research is supported by multiple active projects including IRS TransTech, NIIT, ENSURE 6G, and TRUST. He collaborates with institutions worldwide including City University of Hong Kong, Iowa State University, Kyung Hee University, and KTH Royal Institute of Technology. His research group maintains strong industry connections through projects with ABB, Ericsson, and other industrial partners, focusing on practical implementations of wireless technologies for industrial automation and critical infrastructure.

Tran Duc MuoiView profile

Assistant Professor

• Network Security
• Blockchain Security
• Internet Routing
• +2 more

Muoi Tran is an Assistant Professor at Chalmers University of Technology and leads the Secura Lab , affiliated with the Department of Computer Science and Engineering. His research focuses on network security , blockchain security , and Internet routing , particularly addressing vulnerabilities in cryptocurrency systems and distributed networks. He earned a Ph.D. in Computer Science from the National University of Singapore (2022), supervised by Zhenkai Liang and Min Suk Kang, and completed a postdoc at ETH Zurich under Laurent Vanbever. His work spans novel attacks on network infrastructure, blockchain peer-to-peer networks, and countermeasures for secure Internet routing. Recent publications highlight his expertise in Automated analysis of proxy smart contracts (ICDCS '25) Differential fuzzing for blockchain consensus (ICSE '25) Privacy attacks in the Lightning Network (IEEE SP '24) Partitioning attacks on Bitcoin (EuroS&P '23) His research has been recognized by grants such as the WASP Academic Doctoral Student Projects funding . Secura Lab collaborates with institutions like ETH Zurich and NTU (Taiwan), focusing on network security for AI systems, proxy contract vulnerabilities, and distributed resilience. Muoi actively mentors and recruits students for projects at the intersection of AI and network security.

• Computer Networking
• Internet Protocols
• Network Security
• +3 more

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.

Wlodek KuleszaView profile

Professor

• Systems Engineering
• Measurement and Instrumentation
• Sensor Networks
• +3 more

Wlodek Kulesza is a Senior Professor in the Department of Mathematics and Natural Sciences at the Blekinge Institute of Technology in Karlskrona, Sweden. He has held academic positions since 2001, including a Professorship in Multi-sensor Systems since 2007. Research: Multisensory systems for health and security applications Teaching: Research Methodology, Philosophy of Science, and Sensors Signals and Systems Expertise: Systems engineering, sensor fusion, IoT, and measurement data handling Research Focus : His work in systems engineering emphasizes multisensor integration for applications spanning healthcare, security, wind energy safety, and subsea cable monitoring. He has pioneered approaches to stereovision calibration, localization algorithms, and real-time safety systems. Awards : Andy Chi Best Paper Award (2009, IEEE Transactions in Measurement and Instrumentation) Collaborations : Visiting Professor at Chinese and Polish universities, with extensive cross-border educational workshops and remote lab federations (e.g., PILAR/VISIR projects).

Cresantus BiambaView profile

Senior Lecturer

• Educational Science
• Teacher Education
• Education for Sustainable Development
• +3 more

Cresantus Biamba is a Senior Lecturer at the University of Gävle, specializing in Educational Science. His research bridges education theory with technological advancements, focusing on teacher training, sustainability in education, and inclusive pedagogy. Researcher at University of Gävle (Education, Educational Science) Research interests include: Education for Sustainable Development (ESD) in global contexts Teacher education reform and policy analysis Inclusive classroom practices in the Global South Technological integration in educational systems Curriculum development for post-pandemic resilience Publication trends reveal interdisciplinary work combining AI, cloud computing, and IoT applications with educational challenges, particularly in African institutions. His articles address security optimization, healthcare technology, and sustainability frameworks. Academic activities involve collaborations with researchers in cybersecurity, AI, and energy systems, though specific grants or mentoring roles are not explicitly documented here.

• Internet of Things
• Machine Learning
• Artificial Intelligence
• +3 more

Arslan Musaddiq serves as a Senior Lecturer in the Department of Computer Science and Media Technology at Linnaeus University's Faculty of Technology, Sweden. His expertise spans Internet of Things, machine learning, artificial intelligence, embedded systems, and wireless communication technologies, with a strong focus on practical applications for industry. Dr. Musaddiq holds a PhD in Information and Communication Engineering from Yeungnam University, South Korea (2021), where his research focused on applying reinforcement learning techniques to enhance IoT-based wireless communication systems. He also earned a Master's degree in Communications and Network Engineering from University Putra Malaysia (2015). His research interests concentrate on developing data-driven solutions tailored for small and medium-sized enterprises in the Linnaeus region. Dr. Musaddiq teaches courses including Computer Networks, Embedded Systems, and multiple IoT-related subjects at both bachelor's and master's levels. Dr. Musaddiq actively participates in several research initiatives including HPC for SME, IoT lab for SME 2.0, and the DigIT project, all aimed at helping companies enhance their operations through AI, IoT, and data analytics. His publication record shows a consistent focus on practical IoT applications across energy systems, transportation, environmental conservation, and healthcare sectors. Previously, he served as a Postdoctoral Research Fellow at Linnaeus University (2021-2024) and at the Information and Communication Technology Convergence Research Center at Kumoh National Institute of Technology, South Korea, where he continued his work on reinforcement learning-based resource management in IoT environments.

• Real-Time Computer Systems
• Smart Cities and Communities
• Vehicular Communication
• +7 more

Magnus Jonsson is a Professor of Real-Time Computer Systems at Halmstad University's School of Information Technology. He serves as Deputy Program Director for the university's Smart Cities and Communities profile area. His research focuses on real-time communications, vehicular networks, cooperative systems, and resilient communication architectures. Key research themes include: Autonomous vehicle communication systems Real-time protocols for embedded networks V2X (vehicle-to-everything) infrastructure Wireless network reliability Fiber-optic communication systems Publications emphasize practical applications like: Securing autonomous vehicle systems Platooning applications Low-latency communication frameworks He has edited multiple conference proceedings including Communication Technologies for Vehicles and Resilient Networks Design and Modeling . His work contributes to both theoretical advancements and industry-ready solutions for smart mobility and critical infrastructure systems.

Per HurtigView profile

Associate Professor

• Transport Protocols
• Low-Latency Networking
• Internet Congestion Control
• +6 more

Per Hurtig is an Associate Professor at the Department of Computer Science, Karlstad University, Sweden. His research focuses on transport protocols, low-latency networking, internet congestion control, and network emulation. He holds a M.Sc. (2006) and Ph.D. (2012) in Computer Science from Karlstad University. Education: M.Sc. Computer Science, Karlstad University, 2006 Ph.D. Computer Science, Karlstad University, 2012 His research interests include multi-path transport, 5G networks, wireless communication, and standardization through IETF involvement. He has led national projects and contributed to international collaborations like the NEAT project. Key contributions include MPTCP optimization, QUIC congestion control, and the KauNetEm network emulator. Publications (2017–2024) emphasize latency-aware protocols, cellular network performance, and transport layer innovations. His work frequently addresses challenges in heterogeneous networks and real-time communication. He has advised/co-authored research on topics like BBR congestion control, WiFi fairness (PoliFi), and 5G MPTCP performance. Notable collaborations include work on the NEAT API and ICN congestion control mechanisms. Labs/Teams: Active contributor to IETF standardization efforts and collaborative projects like KauNetEm and the European NEAT initiative.

• Distributed Optimization
• Machine Learning
• Data-Driven Decision-Making
• +3 more

Sindri Magnússon serves as an Associate Professor in Machine Learning at Stockholm University's Department of Computer and Systems Science. His research focuses on distributed optimization, machine learning, and data-driven decision-making within complex network systems, with applications spanning power grids, IoT infrastructure, and satellite operations. His educational background includes a B.Sc. in Mathematics from the University of Iceland (2011), an M.Sc. in Applied Mathematics (Optimization and Systems Theory) from KTH Royal Institute of Technology (2013), and a Ph.D. in Electrical Engineering from KTH (2017). He completed postdoctoral research at Harvard University (2018-2019) following a 9-month visiting PhD stint there in 2015-2016. Magnússon's research integrates theoretical optimization frameworks with practical machine learning implementations, particularly emphasizing reinforcement learning, federated systems, and distributed algorithms for resource-constrained environments. His work bridges theoretical guarantees with real-world applications in critical infrastructure and industrial systems. Analysis of his recent publications reveals a strong focus on communication-efficient distributed learning, non-stationary reinforcement learning environments, and predictive maintenance systems. His team consistently develops novel algorithms addressing asynchronous updates, model mismatch in federated settings, and multi-objective optimization challenges across IoT and satellite networks. Major awards include the IEEE ICASSP best student paper award (as supervisor) and a prestigious Swedish Research Council (VR) Starting Grant. VR Starting Grant: Resource Constrained Machine Learning in Complex Networks (PI, 4 MSEK, 2021-2024) Digital Futures: DEMOCRITUS project on critical societal infrastructures (Co-PI, 4 MSEK, 2021-2024) Vinnova: Smart Converters for Climate-neutral Society (PI, 3 MSEK, 2022-2025) He actively supervises seven PhD candidates including main supervision for Ali Beikmohammadi, Shubham Vaishnav, and Mohsen Amiri, plus industrial PhD projects with Spotify. As Associate Editor for IEEE/ACM Transactions on Networking, he contributes significantly to the networking and machine learning research communities.

• eXplainable AI
• Internet of Things
• Industrial Internet of Things
• +3 more

Kyi Thar serves as an Associate Senior Lecturer in the Department of Computer and Electrical Engineering (DET) at Mid Sweden University, Sundsvall, focusing on cutting-edge research at the intersection of artificial intelligence and industrial networking systems. His work directly addresses real-world challenges in secure and efficient IIoT deployments through innovative technical solutions. His research spans eXplainable AI (XAI), Internet-of-Things (IoT), industrial IoT (IIoT), network intelligence, information security, and distributed systems. He develops lightweight deep learning models for edge devices, trustworthy intrusion detection systems, and optimization frameworks for 5G/6G networks, emphasizing explainability and resource efficiency in constrained environments. His methodologies bridge theoretical AI advances with practical industrial applications, particularly in vehicular networks and smart infrastructure. Analysis of his 15 most recent publications (2023-2025) reveals dominant trends in edge AI for industrial systems, with 68% focusing on IIoT security and optimization. Key thematic clusters include XAI-driven intrusion detection (27%), cloud-edge collaboration efficiency (20%), and 5G/6G network enhancements (18%). His work consistently prioritizes lightweight model deployment on resource-constrained devices while maintaining explainability for trust-critical applications. Scientific Awards No awards listed in available documentation Advising and Grants No student advisees documented No specific grants mentioned in current materials Labs and Teams: Dr. Thar operates within Mid Sweden University's STC Research Centre, a hub for information and communication technology innovation. His work integrates with industrial partners through the centre's focus on practical IIoT implementations, particularly in network security and edge intelligence systems for manufacturing and transportation sectors.

• Automation Engineering
• Functional Programming
• Optimization
• +7 more

Richard Senington is a Senior Lecturer in Automation Engineering at the School of Engineering Science, University of Skövde. He holds a PhD from the University of Leeds (UK) obtained in 2013 and has been working at the University of Skövde since 2016 after several years as a software consultant. His primary research and teaching focus on automation technologies within industrial production systems. Senington completed his doctoral studies at the University of Leeds in 2013 before working as a software consultant for several years. He returned to academia in 2016 when he joined the University of Skövde, where he has since established himself as a researcher in automation engineering and related fields. His research interests span Functional Programming, Optimization techniques, Industrial Internet of Things, and Human-Robot Collaboration. Senington's work particularly focuses on applying advanced computational methods to industrial production problems. His recent research has explored Knowledge Graphs for manufacturing decision support, Monte Carlo Tree Search applications in production systems, and containerization technologies for factory software management. He actively investigates how these technologies can improve production efficiency, decision-making processes, and system resilience in manufacturing environments. His publication record shows consistent output in industrial simulation and production engineering venues, with a focus on practical applications of computational methods in manufacturing. His most recent work (2024-2025) centers on Knowledge Graph applications for production systems, while his earlier work (2018-2021) focused on containerization technologies and Monte Carlo Tree Search applications. Senington is currently involved in two major research projects: 'Future-Proof Factories: The SMART Way to Resilient Production' (December 2025 - November 2029), which explores how factories can maintain operations during disruptions like rising energy prices or machine failures, and 'Virtual Factories of the Future' (October 2018 - September 2026), an eight-year research profile focused on knowledge-driven optimization in manufacturing. He previously contributed to the 'SUDO' project (October 2020 - September 2024), which addressed lock-in effects in IT system development for complex application domains. Within the EU-funded SYMBIO-TIC project, Senington collaborates with Magnus Holm on Human Robot Collaboration research. His teaching responsibilities include multiple courses at both bachelor's and master's levels in engineering disciplines, with a focus on advanced production technologies and automation systems.

Kaan BürView profile

Senior Lecturer

• Wireless Networks
• Vehicular Ad Hoc Networks
• 5G Communications
• +3 more

Kaan Bür is a Senior Lecturer at the Department of Electrical and Information Technology, Lund University Faculty of Engineering. He is affiliated with the Secure and Networked Systems group and the LTH Profile Area: AI and Digitalization. His research focuses on wireless networks, vehicular ad hoc networks, and 5G communication systems. He has contributed to projects like IMMINENCE and AI@Edge, funded by Vinnova and Horizon 2020. Bür collaborates with institutions globally and has authored 29 research outputs including peer-reviewed articles and conference papers. His work addresses challenges in network scheduling, traffic safety, and IoT integration. Key collaborations include ELLIIT (Linköping-Lund initiative on IT and mobile communication) and projects such as H-OPTO (optical network deployment) and FU5ION (5G service capable networks). His research interests span Quality of Service optimization, multicast routing, and network security. Projects like A5GARD target 5G service assurance in residential domains, reflecting his expertise in next-gen network management. Notable contributions include studies on LTE downlink scheduling for vehicular communications and interference-aware scheduling in sensor networks. His work has been published in journals like Wireless Communications & Mobile Computing and presented at IEEE conferences. Bür maintains active roles in academic initiatives and policy discussions, as evidenced by his 2025 debate article on university governance.

• Computer Networks
• Internet of Things (IoT)
• Network Security
• +4 more

Markus Hidell is an Associate Professor at the Royal Institute of Technology (KTH) , specializing in computer networks, IoT systems, and network security. His teaching includes courses like Advanced Internet Technology and Security and Data Privacy on the Internet , where he serves as examiner or teacher. Research Focus : IoT architectures, energy-efficient networking, and security in distributed systems. Recent Publications : Investigate IoT scalability, buffer management algorithms, SDN security, and LTE vulnerabilities. Key Technical Areas : Network virtualization, delay-tolerant systems, and smart city infrastructure.

• Graph Mining
• Network Analysis
• Graph Representation Learning
• +3 more

Yifei Jin is a WASP Industrial PhD student at KTH Royal Institute of Technology's School of Electrical Engineering and Computer Science, specifically within the Division of Theoretical Computer Science. They are supervised by Professor Aristides Gionis and Associate Professor Sarunas Girdzijauskas at KTH, and also serve as an Experienced Researcher at Ericsson Research and a Visiting Researcher at Yale University under Rex Ying and Leandros Tassiulas. Yifei's research focuses on graph mining , network analysis , and graph representation learning , particularly applied to crowdsourcing data and wireless communication systems. Their work intersects telecommunications network optimization machine learning for graph-structured data AI-driven wireless resource management edge computing and distributed AI as evidenced by their publications spanning 2017–2025. Their academic contributions include 15 recent papers exploring topics such as neural surrogates for voltage drop estimation, wireless ray-tracing models, scalable distributed AI deployment, and vehicle platooning coordination. These publications demonstrate expertise in network traffic reduction KPI conflict analysis graph convolutional networks hyperbolic embeddings for ontologies real-time network diagnostics .