Dr. Jaume Ramis Bibiloni is an Associate Professor at the Department of Mathematics and Informatics, School of Engineering, University of the Balearic Islands (UIB). He holds a Telecommunication Engineer degree from Polytechnic University of Catalonia (UPC) and a PhD in Computer Science from UIB. Affiliation: University of the Balearic Islands Research Focus: Blockchain-based systems, wireless body area networks (WBANs), radio resource management, IoT, and network modeling Teaching: Courses include Network Modeling, Cybersecurity, Telecommunication Projects, and Final Degree Projects for Telematics Engineering and double degrees His research integrates blockchain technology with IoT platforms for drug quality monitoring, secure notifications, and digital credentials. He has developed energy-efficient protocols for WBANs and contributed to NFT-based ticketing systems. Recent publications emphasize multi-sensor IoT architectures, soulbound tokens, and energy harvesting techniques. Scientific Awards: Co-recipient of Best Paper Award at IEEE Vehicular Technology Conference 2009-Spring He collaborates on R&D projects funded by the Spanish and Balearic Islands governments and is a member of the Security and e-Commerce (SECOM) research group. His teaching spans 5 years, covering network modeling, cybersecurity, and engineering projects.
Alexey Vinel is a researcher affiliated with the University of West London, focusing on wireless communication systems, network security, and energy-efficient protocols. His work spans vehicular networks (VANET), IoT architectures, and heterogeneous LTE systems. Key research areas: Computer Networks, Wireless Communication, Energy Efficiency Active publication period: 2013–2017 His publications demonstrate expertise in: QoS optimization for IoT and multimedia streaming Security mechanisms in vehicular and low-power networks Energy cooperation strategies for millimeter-wave networks Radio resource management in LTE/LTE-A systems Collaborations include researchers like Jonathan Loo, Yue Chen, and Magnus Jonsson. Notable journals include IEEE Systems Journal , IEEE Communications Letters , and IEEE Sensors Journal .
Prof. Marius Brezovan is a faculty member at the Department of Software Engineering, Faculty of Automatic Control, Computers and Electronics, University of Craiova. He earned his PhD in Automatic Systems in 1998 under Prof. Dr. Eng. Mircea Ivanescu. Teaching Subjects: Object-Oriented Programming, Expert Systems, Software Engineering, Compiler Design, Formal and Automatic Languages Research Focus: Formal methods in system modeling, concurrent object-oriented programming, image processing, and multimedia applications His publications span topics like Petri nets, image segmentation algorithms, and database migration. He led two CNCSIS-funded projects on object-oriented Petri nets for manufacturing systems and contributed to CNCSIS-accredited publishing houses. As a member of the Research Center 'Development of Multimedia Applications' and the editorial board of 'Else Software', he participates in international conferences as committee member and reviewer.
Maria Kihl is a Professor at Lund University's Department of Electrical and Information Technology, where she also serves as Assistant Head of Department. She leads research in mission-critical networked systems, focusing on Industry 4.0, cloud-based control systems, and 5G/6G architectures. As Director of the NEXTG2COM Competence Centre, she coordinates advanced digitalization initiatives. She is also affiliated with ELLIIT, Sentio, and multiple university profile areas including AI and Digitalization. Her research explores autonomous vehicle systems, intelligent traffic management, and network security, with recent work emphasizing machine learning integration in transportation and 5G readiness for industrial applications. Publications demonstrate consistent focus on real-time control systems and cybersecurity in emerging technologies. Awards: Best Paper Award (2018) She directs the NEXTG2COM centre, managing projects on next-gen communication infrastructures funded by Vinnova, and collaborates extensively with industry partners. Her team develops experimental testbeds for autonomous intersection management and vehicular communication systems.
Qixia Zhang is a Postdoctoral Research Fellow in Computer Science at UiT The Arctic University of Norway and a guest researcher at University of Oslo. Their research spans multiple cutting-edge domains including cloud/edge computing, AI and machine learning, distributed systems, energy efficiency, and IoT applications. Zhang is actively involved in several major research projects including HAPADS, MISO, EMLEMS, eX3, DILUTE, and AirQMan, which focus on environmental monitoring, energy efficiency, and advanced computing systems. Dr. Zhang completed their educational journey at Huazhong University of Science and Technology in China, earning a B.Eng. degree in 2016 and a Ph.D. degree in 2021. Additionally, they studied Economics at Wuhan University from 2014-2016. Their academic path demonstrates a strong interdisciplinary foundation combining computer science with economic perspectives. Zhang's research interests focus on the intersection of computing technologies and environmental sustainability. They investigate how edge and cloud computing architectures can be optimized for energy efficiency while supporting demanding applications like air pollution monitoring and renewable energy integration. Their work on machine learning applications spans multiple domains including wind energy forecasting, IoT data collection, and vehicular edge computing. The research demonstrates a consistent theme of applying computational intelligence to solve real-world environmental challenges. The publication record reveals a strong trajectory in both theoretical and applied research. Early work focused on network function virtualization and edge computing infrastructure, while more recent publications show increasing emphasis on environmental applications including air pollution monitoring, wind energy analysis, and climate-related computing challenges. The research demonstrates a clear evolution toward addressing sustainability challenges through advanced computing techniques, with recent publications heavily featuring Norwegian environmental contexts. Best Paper Award of IEEE/ACM IWQoS 2019 National Scholarship of China for PhD First-class Academic Scholarship Outstanding Graduate Award Excellent Student Cadre Scholarship Zhang serves as a guest editor for Journal Symmetry's Special Issue on Applications based on Symmetry in Machine Learning and Data Mining. They are actively involved in multiple research projects funded by the Research Council of Norway, including HAPADS, MISO, EMLEMS, eX3, DILUTE, and AirQMan. These projects represent significant funding commitments to advance computing technologies for environmental monitoring and energy efficiency. Zhang is also a member of the Arctic Green Computing (AGC) research group at UiT. Based at UiT's Department of Computer Science in Tromsø, Zhang collaborates with the Arctic Green Computing research group and maintains active connections with University of Oslo's Department of Informatics. Their research environment bridges theoretical computer science with practical environmental applications, leveraging Norway's unique position in Arctic research and renewable energy development. The recent guest researcher position at Karlsruhe Institute of Technology further demonstrates their international research network and collaborative approach.
Dr. Elias Eze is a Lecturer at the Department of Computing and Engineering within the School of Architecture, Computing and Engineering at the University of East London. He joined UEL in July 2022 after working as a Research Fellow and Associate Lecturer at the University of Bedfordshire and an academic at Ebonyi State University in Nigeria. PhD in Computer Science (University of Bedfordshire, 2017) MSc in Computer Networking (University of Bedfordshire, 2012) BSc in Computer Science (Ebonyi State University, Nigeria, 2010) Dr. Eze specializes in Big Data Analytics , Machine Learning , Artificial Intelligence , Network Security , and Cyber Security . His research focuses on applying deep learning and data mining techniques to aquaculture, vehicular networks, and food supply chains. He is a Certified Ethical Hacker (CEH) and an associate member of the British Computer Society. His recent publications emphasize the integration of 5G-IoT connectivity with Big Data Analytics for aquaculture optimization, leveraging Neural Networks in water quality monitoring, and enhancing communication reliability in Vehicular Ad-Hoc Networks (VANETs). Notable projects include the Advancing Digital Precision Aquaculture in China (ADPAC) initiative funded by the Newton Fund, Innovate UK, and BBSRC. Dr. Eze teaches modules such as Computers and Network Security (CN6003) and Big Data Analytics (CN7031). He supervises final-year projects, master's dissertations, and doctoral students.
Dr. Vu Phi Tran is a Researcher at the University of New South Wales (UNSW) Canberra, affiliated with the School of Engineering and Technology. He serves as a Research Assistant, Teaching Staff member, and Casual Professional staff within the Trusted Autonomy research group since 2020, contributing to high-impact publications in IEEE Transactions and Elsevier journals. His educational background includes a B.E. in Automation and Control Engineering from HCMC University of Technology and Education (2010), an M.S. in Mechatronics Engineering from Asian Institute of Technology (2015), and a Ph.D. in Aerospace Engineering from UNSW Canberra (2019). He previously served as a Lecturer at HCMC University from 2010-2012. Tran’s research spans adaptive and robust control , non-linear systems , UAV swarm coordination , and neural-fuzzy control architectures . His work focuses on real-world applications including gas source localization, resilient flight control for nano-drones, and formation control under disturbances, leveraging negative-imaginary systems theory and machine learning. Recent publications demonstrate a strong trend toward multi-robot environmental monitoring and adaptive learning-based controllers for uncertain environments. His scientific achievements include: Rockwell Automation Scholarship for Engineering Excellence THE HISAMATSU PRIZE for outstanding Mechatronics performance UNSW Tuition Fee Scholarship Dean’s Award for Outstanding PhD Theses T.F.C Lawrence Prize for Aeronautical Science Tran actively serves as a reviewer for IEEE Transactions on Robotics and Vehicular Technology, while leading projects funded by DST and AFOSR grants. His current work focuses on machine learning for obstacle avoidance in robot swarms and robust flight control systems. He operates from the Autonomous System Laboratory (Building 17, Room 131) at UNSW Canberra, collaborating with international researchers on UAV-UGV interaction systems.
Unai Hernandez Jayo is a Lecturer at the University of Deusto's College of Engineering, Bilbao campus, teaching Electronics , Electrical Engineering/Circuits , and Power Electronics in industrial degrees. He serves as Director of the Master's Degree in Industrial Automation, Electronics and Control and has been accredited as Professor by ANECA. His research focuses on remote laboratories , e-learning , and vehicular communications within the DEUSTEK research group (A-rated by Basque Government). Teaches core electronics subjects in industrial engineering Active in educational technology and remote experimentation Develops scalable remote lab architectures and real-time control systems Research Interests include: Remote Laboratories E-Learning and Educational Technology Vehicular Communication Systems Wireless Sensor Networks Smart City Applications Engineering Pedagogy His publications show a strong focus on remote laboratories (especially VISIR platform), vehicular communication protocols , and smart city sensor networks . He has contributed to systematic reviews on extended remote labs and VR/AR techniques in educational experimentation. Academic Contributions : Accredited Professor by ANECA (Spanish quality agency) Holds two active 6-year research periods and one technology transfer period from CNEAI Academic Editor (Sensors journal 2022-2023)
Henry Hui serves as a Research Fellow at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, where he conducts cutting-edge cybersecurity research focused on critical infrastructure protection. His work bridges theoretical security frameworks with practical industrial applications across multiple high-stakes domains. His research expertise spans several interconnected cybersecurity domains: Industrial Control Systems Security : Specializing in vulnerability analysis of Siemens S7 PLCs, secure Smart Grid communications, and ICS testbed development for critical infrastructure protection Safety-Critical Systems : Developing security pattern implementations and runtime monitoring architectures for systems where failure could cause catastrophic consequences Automotive Cybersecurity : Addressing security gaps through ISO/SAE 21434 standard implementation and vehicle security architecture design Embedded Systems Security : Creating security solutions for resource-constrained environments including hypervisor monitoring and hardware-based cryptographic acceleration Analysis of his 2018-2025 publication record reveals consistent focus on practical security solutions for industrial environments. His recent work demonstrates increasing specialization in hardware security (2025 RISC-V research) while maintaining strong industry relevance through automotive standards and PLC vulnerability research. This trajectory shows sophisticated evolution from foundational ICS security (2018-2019) toward integrated hardware-software security solutions. No scientific awards or professional honors were documented in the available information. Information regarding student supervision, research grants, or laboratory facilities was not provided in the source materials, though his collaborative fingerprint shows active engagement with five similar research profiles across cybersecurity domains.
Panagiotis Pantazopoulos is a Senior Researcher and Technical Project Manager at the Institute of Communication and Computer Systems (ICCS) in Greece. Since 2015, he has focused on research project management and the design/analysis of Intelligent Transport Systems (ITS) applications. His work spans vehicular networks, cybersecurity, distributed machine learning, and network protocols. PhD in Computer Science (2009-2015) under Prof. Ioannis Stavrakakis (IEEE Fellow) MSc in Control and Computing from National & Kapodistrian University of Athens (2004-2009) BSc in Physics (Telecommunications major) from National & Kapodistrian University of Athens (2004) Research Interests: Connected vehicles, automated driving applications, distributed machine learning, vehicular cybersecurity, and network protocol design. His projects include HORIZON-CL3-2023 CASTOR, HORIZON-CL5-2021 CONNECT, and H2020 initiatives like Hi-Drive and TERAWAY. Recent Publications highlight edge-cloud resource allocation, federated learning, and vehicular cybersecurity. He has contributed to IEEE, Elsevier, and Springer publications, with experimental validation on 5G testbeds and cross-border datasets. Editorial Role: Associate Editor at IEEE Intelligent Vehicles Symposium since 2017.
Professor Christos Politis is a Chair in Digital Technologies at the School of Computer Science and Mathematics , Kingston University London, where he serves as Director of the Digital Information Research Centre (DIRC). His research focuses span Wireless Multimedia & Networking , Cognitive Radio , 5G/4G Networks , and Emergency Communication Systems , with significant contributions to Energy Efficiency , Security Protocols , and IoT Applications . He has led 23 academics 15 postdoctoral researchers Over 40 PhD students at DIRC. With over 200 publications and two patents , his work is funded by EU and UK programs (FP5/6/7, H2020, EPSRC, Innovate UK). He consults for governmental and commercial organizations in EU, UK, Canada, Greece, Qatar, China, and Malaysia , and holds a PhD and MSc in Electrical and Electronic Engineering from the University of Surrey, along with a BEng from the University of Athens. His academic journey includes roles at Ofcom, the University of Surrey, and placements in Greece. Recent publications highlight advancements in AI-driven ECG analysis , UAV-assisted post-disaster networks , V2X security , and smart energy systems . He is a senior member of the IEEE and a UK chartered engineer.
Prof. Dr. Aykut Hocanın is a Professor in the Electrical and Electronic Engineering Department at Eastern Mediterranean University, Faculty of Engineering, in Gazimağusa, Northern Cyprus. He has held various academic and administrative positions at the university since 2000, including Assistant Professor (2000), Associate Professor (2006), Professor (2012), Vice Chairman (2003-2007), Chairman (2007-2014), Dean of the Faculty of Engineering (2014-2020), and Rector of Eastern Mediterranean University (2020-2023). His educational background includes a Ph.D. in Electrical Engineering from Boğaziçi University (1994-2000), an M.Eng. in Electrical Engineering from Texas A&M University (1992-1993), and a B.S.E.E. in Electrical and Computer Engineering from Rice University (1988-1992). Prof. Hocanın's research interests span a wide range of topics in signal processing and communications. His work primarily focuses on adaptive filtering algorithms, wireless communication systems, and signal processing techniques. He has made significant contributions to the development of recursive inverse adaptive filtering algorithms, sparse system identification, and applications in echo cancellation and interference suppression. His research bridges theoretical developments with practical implementations in communication systems. Analysis of his recent publications reveals a strong focus on adaptive signal processing techniques, particularly recursive inverse adaptive filtering algorithms and their applications. His work extends to two-dimensional signal processing, impulsive noise environments, and MIMO systems. The research shows a consistent progression from fundamental algorithm development to practical applications in communication systems. His scientific achievements have been recognized through various scholarships and honors: Fahir İlkel Ph.D Scholarship, Boğaziçi University President's Honor List, Rice University CASP Scholarship from AMIDEAST He is an active member of the scientific community, serving as a reviewer for numerous prestigious journals including IEEE Transactions on Signal Processing and IEEE Transactions on Communications. Prof. Hocanın has supervised numerous graduate students, with many of his publications co-authored with PhD and Master's candidates. He has led research projects, including a TRNC Ministry of Education project on "Adaptive Filtering for Interference Cancellation." His service to the academic community extends to conference organization roles, including Technical Program Chairman for SİU 2013 and Conference co-chairman for ICSCCW 2009. He maintains active professional affiliations as a Senior Member of IEEE (with memberships in Communications Society, Signal Processing Society, and Vehicular Technology Society) and a Senior Member of ACM, demonstrating his standing in the international research community.
Guido Albertengo serves as an Associate Professor in the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin. His academic responsibilities span multiple educational programs including the College of Electronic, Telecommunications and Physics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. Albertengo teaches courses related to communication systems, IoT applications, and automotive informatics across various degree programs including Communications Engineering, Electronic Engineering, and ICT for Smart Societies. Albertengo's research focuses on Internet of Things (IoT) applications, particularly in vehicular traffic monitoring systems. His work integrates telecommunications technologies with sensor networks and embedded systems to develop solutions for smart transportation infrastructure. His expertise spans wireless communication protocols, network performance analysis, and the application of deep learning techniques to urban traffic forecasting problems. Analysis of Albertengo's recent publications reveals a consistent research trajectory centered on communication systems for IoT applications, particularly in transportation contexts. His work demonstrates expertise in evaluating cloud messaging platforms, developing smartphone-based traffic monitoring solutions, and applying deep learning to traffic prediction. The publications show strong interdisciplinary connections between telecommunications engineering, computer science, and transportation systems. Albertengo has supervised doctoral students in the Electronics and Communications Engineering program from 2003/2004 through 2010/2011. His research projects include commercially funded work such as Scientific Analysis of Case Studies and Operational Scenarios of the Field Application of IEEE 802.15.4 Communications (2010-present), Personal and Trusted Services for the Connected Car (2015-2016), and Preliminary Analysis of a Scenario for the Use of New HW and SW Technologies Suitable for Wireless Network Transmission (2008). Albertengo is an active member of the TNG (DET) research group, which focuses on telecommunications network technologies and their applications. His work bridges academic research with practical commercial applications, particularly in the automotive and smart city domains.
Hao Yang is an Associate Professor in the Department of Civil Engineering at McMaster University, specializing in Intelligent Transportation Systems and Connected Vehicle Technologies . His research focuses on optimizing traffic flow, enhancing eco-driving strategies, and developing centralized control systems for urban mobility. Key areas: Traffic Flow Modeling, V2X Communication, Spatiotemporal Data Analysis Scientific Contributions : Recent publications analyze deep reinforcement learning for vehicle merging, macroscopic fundamental diagrams for congestion prediction, and multi-algorithmic ensemble models for traffic speed forecasting. His work spans hybrid physics-ML approaches and real-time traffic management systems. Teaching : Instructs courses including Pavement Materials and Design (CIVENG 4G04/6G04), Surveying for Transportation (CIVENG 2A03), and Travel Demand Analysis (CIVENG 711).
Martin Lundgren is a Senior Lecturer in Informatics at the School of Informatics, University of Skövde. His work focuses on Information Security and Cybersecurity, particularly in air traffic management, automotive systems, and smart home environments. Specializes in human-centric cybersecurity approaches Active in certificateless cryptography for transportation systems Investigates stress factors in security risk management His recent publications analyze cybersecurity readiness in modern cars (2023-2024), threat intelligence integration (2023), and risk management tools for aviation (2025). Research trends show cross-domain applications of security frameworks and human factors in cybersecurity.
