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
Hossam Hassanein is a Professor and Director of the School of Computing at Queen's University. He received his B.Sc. in Electrical Engineering from Kuwait University in 1984, M.Sc. in Computer Engineering from the University of Toronto in 1986, and Ph.D. in Computing Science from the University of Alberta in 1990. He joined Queen's University School of Computing in 1999 and has established himself as a leading researcher in telecommunications and networking. Dr. Hassanein's research interests span wireless sensor networks, mobile ad hoc networks, edge computing, Internet of Things (IoT), radio resource management, and data-centric networks. His seminal contributions include pioneering work on WSN planning, load-balanced routing protocols, and energy-efficient network designs. He has championed research in IoT, developing frameworks for smart spaces that use contextual information to enhance IoT applications in healthcare, transportation, and infrastructure. His recent publications (2023-2025) demonstrate a strong focus on cutting-edge areas including extreme edge computing, vehicular networks, and AI/ML integration in networking. Research trends show increasing emphasis on practical applications in telesurgery, digital twins, and industrial IoT, addressing challenges in resource allocation, task offloading, and real-time processing in constrained environments. Dr. Hassanein has received numerous recognitions for his work: Fellow of the IEEE Queen's University School of Graduate Studies Award for Excellence in Graduate Student Supervision (2015) Multiple best paper awards from top international conferences As founder and director of the Telecommunications Research Lab (TRL), Dr. Hassanein has supervised over 75 students who have made substantial contributions in academia and industry. The TRL is one of Queen's largest research groups with extensive international collaborations. Dr. Hassanein has successfully attracted significant research funding from government and industry sources in the competitive telecommunications field. The Telecommunications Research Lab has developed innovative platforms including SPROUTS, a rugged sensor platform used in mining, steel manufacturing, and smart-grid monitoring. TRL's work has had significant impact in WSN planning, data dissemination, and resource reuse in wireless networks, with contributions featured in IEEE Wireless Communications Magazine.
Maher Elshakankiri is an Assistant Professor, Teaching Stream at the University of Toronto's Faculty of Information. He holds a Ph.D. in Computer Engineering from Ain Shams University (Egypt), followed by a postdoctoral fellowship at the University of Regina. His research focuses on IoT, Wireless Sensor Networks (WSN), and pedagogical integration of technology and gaming. He has supervised over 100 student projects and authored a book on WSNs. Education: Ph.D. in Computer Engineering, Ain Shams University, Egypt M.Eng., B.Eng. in Engineering, Ain Shams University, Egypt Postdoctoral Fellowship, University of Regina, Canada Research Interests: IoT in healthcare, agriculture, and sports Active learning classrooms and technology in education Wireless communication protocols (V2V, UAV, RFID) Leadership & Grants: Director, Bachelor of Information (BI) Program (2024–present) Coordinator, Information Systems and Design (ISD) Concentration (2023) SSHRC Grant: 'Gaming in teaching towards a more inclusive class' (2022–2023) Professional Activities: Member, SCC IoT & Digital Twins Standards Committee Reviewer for journals including Wireless Networks , Telematics and Informatics , and Computational Intelligence Technical Program Committee member at multiple conferences Teaching: Courses include INF1340 (Programming for Data Science), INF1005/1006 (IoT Workshops), and INF452 (Information Design Coding).
Cao Jiannong is currently a Chair Professor and Director of the University Research Facility in Big Data Analytics at Hong Kong Polytechnic University . He has held academic roles including Assistant Professor at City University of Hong Kong and University Lecturer at the University of Adelaide and James Cook University. His research spans Cloud and Edge Computing , Parallel and Distributed Systems , Big Data Analytics , and Wireless Sensing . Ph.D. in Computer Science, Washington State University (1990) MSc in Computer Science, Washington State University (1986) BSc in Computer Science, Nanjing University, China (1982) His work focuses on solving theoretical and practical challenges in distributed computing , mobile cloud systems , and wireless sensor networks . Recent projects include coupled network embedding models for heterogeneous networks and SDN architectures for vehicular communication. His research also pioneers WiFi-based non-invasive health monitoring and fault-tolerant sensor deployment for structural health applications. Dr. Cao's publications highlight advancements in network embedding , edge computing , and WSN optimization . Key papers address multi-user computation partitioning , energy-efficient SHM systems , and consensus protocols for mobile networks. These works have been cited over 15,000 times, with an h-index of 60. Ministry of Education (China) Natural Science Award (2018) Distinguished Member, ACM (2017) Fellow, IEEE (2014) Best Paper Awards at IEEE DSAA, SMARTCOMP, and WCNC Dr. Cao has advised multiple PhD students, including Linchuan Xu and Weigang Wu , whose research on WSN-based SHM and coupled network embedding has practical impact. His leadership includes directing Hong Kong Polytechnic University's Big Data Research Facility and serving on technical committees for IEEE INFOCOM and ACM/IEEE conferences.
Mauro Conti is a Full Professor at the University of Padua, Italy, where he serves as Editor-in-chief of IEEE TIFS, UniPD Academic Advisor for Entrepreneurship Development, Study Program Coordinator of the MSc degree in Cybersecurity, Head of the SPRITZ Security and Privacy Research Group, and Director of the UniPD node of CINI Cybersecurity National Lab. He also maintains affiliations with TU Delft (NL) and the University of Washington (USA). Additionally, he is the CEO and co-founder of CHISITO and co-founder of DYALOGHI. His research focuses on security and privacy for wireless resource-constrained mobile devices (WSNs, RFIDs, and smartphones), computer system security, computer forensics, access control, and distributed and networked systems. Professor Conti has published extensively in top security venues including ACM CCS, IEEE S&P, NDSS, and USENIX Security, with recent work covering topics such as battery authentication, federated learning privacy, private set intersections, USB peripheral fingerprinting, and ATM PIN inference. He has received numerous prestigious awards including IEEE Fellow, Young Academy of Europe Fellow, EU Marie Curie Fellow, and DAAD Fellow. Professor Conti has advised over 100 students at various levels including PhD, MSc, and BSc, many of whom have gone on to successful careers in academia and industry. His research has been supported by multiple European Commission projects, university grants, and industry collaborations with companies like Cisco and Intel.
Jiannong Cao is a Chair Professor and Director of the University Research Facility in Big Data Analytics at the Department of Computing, Hong Kong Polytechnic University. He has held various academic roles since 1990, including Assistant Professor at City University of Hong Kong and Lecturer at Australian universities. PhD in Computer Science, Washington State University (1990) MSc in Computer Science, Washington State University (1986) BSc in Computer Science, Nanjing University (1982) His research focuses on cloud and edge computing , parallel and distributed computing , and mobile computing , with significant contributions to wireless sensor networks (WSN) for structural health monitoring (SHM) and software-defined networking (SDN) for vehicular communications. Recent work includes WiFi-based non-invasive health monitoring systems and multi-user computation partitioning in mobile cloud environments. Dr. Cao’s publications demonstrate trends in WSN optimization , SDN architectures , and cognitive modeling for network embedding , with applications in smart healthcare , transportation systems , and industrial IoT . Ministry of Education Natural Science Award (2018) ACM Distinguished Member (2017) IEEE Fellow (2014) Best Paper Awards at IEEE DSAA, SMARTCOMP, WCNC He has mentored numerous researchers, including Linchuan Xu , Xuefeng Liu , and Weigang Wu , who have authored key publications in top venues like ACM WSDM and IEEE INFOCOM . His professional roles include chairing IEEE committees and serving on grant panels for the Hong Kong Research Grant Council.
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.
Dr. Ioanna Kantzavelou is an Associate Professor at the Department of Informatics and Computer Engineering, School of Engineering, University of West Attica. She leads the INSSec Research Group, focusing on Information, Networks, and Systems Security. Her expertise spans Cybersecurity, Game Theoretic approaches in Intrusion Detection, and Critical Infrastructure Protection. She holds a Ph.D. from the University of the Aegean (2011), an M.Sc. from University College Dublin (1994), and a B.Sc. from the Technological Educational Institution of Athens (1991). Education: Ph.D. in Intrusion Detection with Game Theoretic Approaches – University of the Aegean (2011) M.Sc. in Computer Security – University College Dublin (1994) B.Sc. in Informatics – TEI of Athens (1991) Research Interests: Intrusion Detection in IoT/Wireless Sensor Networks (WSN) and Cyber-Physical Systems Cyber Ranges for Education and Research Cybersecurity for Merchant Shipping and Critical Infrastructures Hybrid Threats, Cyberterrorism, and Cyberwarfare Digital Forensics and Blockchain-Based Authentication Systems Her work includes over 30 peer-reviewed publications, three books, and contributions to R&D projects funded by the Greek government, EU, and Irish government. She actively reviews for IEEE, Elsevier, and Springer journals, and is a member of ACM, IEEE Computer Society, and the Greek Computer Society. Grants & Collaborations: EU-funded projects on Cybersecurity and Critical Infrastructure Protection Greek government grants for Cyber Ranges and IoT Security Labs/Teams: Head of the INSSec Research Group, collaborating with industry partners on Cybersecurity solutions for maritime and industrial sectors.
Rajesh M. Hegde is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur. He holds a PhD in Computer Science from IIT Madras (2005), an M.E. in Electronics Engineering from Bangalore University (1988), and a B.E. in IT Engineering from Mysore University. His research focuses on Machine Learning , AI , and multimodal systems, with applications in wireless networks, IoT, and speech/audio processing. Specific interests include federated learning, WSN, and information fusion for ASR/VR systems. His lab is located in ACES 203-204. Publications predominantly explore signal processing techniques for multimedia and speech applications, showing consistent focus on feature extraction, multimodal fusion, and real-time system design across 15+ years of research. Awards & Honors: P.K Kelkar Research Fellowship (2009-2013) Undergraduate design mentorship award, UC San Diego ISCA Grant at INTERSPEECH-ICSLP 2004 IBM Best Thesis Award recommendation Teaching excellence commendation
Maozhen Li is a Professor in the Department of Electronic and Electrical Engineering at Brunel University of London , within the College of Engineering, Design and Physical Sciences . He serves as the Vice-Dean of the NCUT Transnational Education (TNE) programme, overseeing a joint school with North China University of Technology. He has been at Brunel since 2002, progressing from Lecturer to Professor in 2013. Education: PhD, Institute of Software, Chinese Academy of Sciences (1997) Postdoctoral Research, School of Computer Science and Informatics, Cardiff University (1999–2002) His primary research interests lie in high performance computing, big data analytics, and artificial intelligence, with applications in smart grids, smart manufacturing, and cybersecurity. He focuses on developing interpretable, robust, and lightweight AI models, including work in causal AI, parallel machine learning, and edge computing. His research integrates advanced techniques such as deep learning, reinforcement learning, and blockchain for real-world system optimization. An analysis of his recent publications reveals a strong and consistent research trajectory in AI-driven solutions for environmental monitoring (e.g., PM2.5 prediction), industrial defect detection, IoT security, and intelligent transportation. His work frequently combines deep learning with graph-based modeling and federated or reinforcement learning, emphasizing scalability, efficiency, and robustness in distributed and edge environments. Scientific Awards and Recognition: Fellow of the Institution of Engineering and Technology (IET) Fellow of the British Computer Society (BCS) Shortlisted for the Computing UK BIG DATA EXCELLENCE AWARDS 2018 in the category of Most Innovative Big Data Solution Maozhen Li has successfully supervised 25 PhD students and examined over 30 PhD theses externally. He has secured significant research funding from EPSRC, the European Union (Horizon 2020), Innovate UK, and the Royal Society , with projects including Z-BRE4K, IoRL, and TDX-ASSIST. He serves as an Associate Editor for journals such as the Journal of Cloud Computing and the International Journal of Grid and High Performance Computing . Research Groups and Teams: He is affiliated with the Intelligent Engineering Frameworks (IEF) research group at Brunel, contributing to collaborative efforts in AI, IoT, and smart systems. His leadership in transnational education also fosters international research collaboration between Brunel and Chinese institutions.
Mustapha C.E. Yagoub is a Full Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, with over 500 publications in RF/microwave CAD, RFID systems, neural networks, and applied electromagnetics. He leads research in the ELEMENT Laboratory and RFM Research Group , focusing on wireless communication systems and nonlinear device modeling. PhD in Electronics (Institut National Polytechnique de Toulouse, 1994) Magister in Telecommunications (École Nationale Polytechnique d'Alger, 1987) Dipl.-Ing. in Electronics (École Nationale Polytechnique d'Alger, 1979) His research bridges Microwave Circuit Design with Artificial Intelligence , including applications in Energy Conservation and Telecommunication Systems . Key trends in his publications include hybrid modeling techniques combining Neural Networks with Computational Electromagnetics for optimizing Antenna Design and RF Components . He is a Senior Member of IEEE and licensed with the Professional Engineers of Ontario and Ordre des Ingénieurs du Québec . His lab teams focus on High-Tc Superconducting Devices and Directional Antenna Optimization for RFID networks.
National and Kapodistrian University of AthensGreece
Stavrakakis Ioannis is a Professor at the Department of Informatics and Telecommunications, School of Science, University of Athens, where he has served since 2002. He previously held academic positions at Northeastern University (1994-1999) and University of Vermont (1988-1994). Ph.D., Electrical Engineering (1988), University of Virginia Diploma, Electrical Engineering (1983), Aristotle University of Thessaloniki His research focuses on network resource allocation algorithms , cooperative content dissemination , mobile ad hoc networks , and privacy-aware protocols . He leads the Advanced Networking Research (ANR) Group. Recent publications highlight trends in AI-driven network optimization , edge computing for VR , drone-assisted sensor networks , and privacy in vehicular systems . Key themes include game theory applications, energy-efficient protocols, and distributed learning frameworks. Contact: ioannis@di.uoa.gr
Associate Professor Ke Deng is affiliated with the School of Computing Technologies at RMIT University. His research focuses on urban computing, spatiotemporal data analysis, and social networks, with expertise in data mining and artificial intelligence. He holds a PhD in Computer Science from The University of Queensland (2007), a Master's in Information and Communication Technology (2001), and a Bachelor's in Electrical Engineering (1994). Previously, he was a postdoctoral researcher at CSIRO ICT Centre and a researcher at Huawei Noah's Ark Lab. His work emphasizes practical applications of AI, such as fairness-aware recommendation systems, traffic scenario modeling, and energy-efficient protocols for IoT. Dr. Deng's career includes roles as an acting lecturer at The University of Queensland and co-supervisor of a PhD student. He has supervised numerous research projects, including advancements in quantum annealing for recommenders, fake news mitigation via reinforcement learning, and smart human sensing using millimeter-wave radar. His research outputs span journals like ACM Transactions on Information Systems and IEEE Transactions on Knowledge and Data Engineering. Education: PhD in Computer Science, The University of Queensland (2007) MSc in Information and Communication Technology (2001) BEng in Electrical Engineering (1994) Key Research Themes: Urban computing and smart cities Mechanisms for fair AI systems Energy-efficient IoT protocols Spatiotemporal data mining Grants and Collaborations: ARC Australian Postdoctoral Fellowship (2010–2012) Research at Huawei Noah's Ark Lab (2013) His recent projects highlight interdisciplinary innovation, such as quantum computing for feature selection and self-supervised networks for traffic scenario clustering. Dr. Deng is actively involved in mentoring PhD/Masters students and contributes to RMIT’s research initiatives in AI and urban informatics.
Sandra M. Đosić is an Associate Professor at the Faculty of Electronics in Niš, University of Niš, Serbia, specializing in Electronics and Embedded Systems. She has been actively contributing to research in real-time systems, fault tolerance, wireless sensor networks, and indoor localization technologies. Research Interests: Her work spans fault-tolerant real-time systems, energy-efficient computing, UWB-based indoor localization, and communication protocols for wireless sensor networks. She explores techniques such as dynamic voltage and frequency scaling (DVFS), tone-based contention resolution, and deflection routing in networks-on-chip to enhance system reliability and efficiency. Publication Trends: Her recent publications (2009–2022) demonstrate a strong focus on improving robustness and performance in embedded and distributed systems. The research integrates signal processing, network optimization, and energy-aware design, primarily applied in industrial and indoor environments. Scientific Awards: No awards are mentioned in the provided text. Advising and Grants: While no specific students are listed, she is currently participating in two national research projects, indicating active involvement in funded research. Her collaborations with researchers such as Igor Stojanovic and Milica Jovanovic suggest a strong team-based research approach. Labs and Research Teams: Although no formal lab or team name is specified, her repeated co-authorship with colleagues from the Faculty of Electronics implies active participation in a research group focused on electronics, communications, and real-time systems.
Sanem Kabadayı is an Assistant Professor at the Department of Computer Engineering, Istanbul Technical University. Her research focuses on sensor networks, middleware frameworks, and pervasive computing. Research Interests Sensor Networks (Wireless, Ad-hoc, Heterogeneous) Pervasive and Ubiquitous Computing Middleware Design for Smart Environments Data Abstraction and Communication Paradigms Advisory Role Advisor for Yakup Kayatas' thesis on AI-assisted IoT agents for smart spaces (2025). Recent Research Trends Her 15 most recent publications (2006–2024) emphasize sensor network architectures, middleware innovations for programmable environments, and abstractions for heterogeneous sensor integration. Key themes include AI-driven IoT agents, positioning techniques in wireless networks, and virtual sensor frameworks.
