Jiejun Hu-Bolz is a Lecturer in Computer Science at the Data Science Institute, Lancaster University. Her research focuses on blockchain technologies, IoT security, game theory, and decentralized systems. Research Trends: Recent work spans federated learning architectures, human-AI symbiosis via game theory, energy-efficient blockchain systems for IoT, and semantic-aware crowdsensing frameworks. Key themes include data privacy, incentive design, and network optimization. Projects: Smart and Proactive Multi-RAT Traffic Steering for V2X (2024-2027) TaaraSkillQuest Consultancy (2023-2024) Research Groups: Security Lancaster (Systems Security)
Goutham Reddy Alavalapati is an Assistant Professor in the Department of Computer Science at the University of Illinois Springfield. Previously, he held academic positions at Fontbonne University and the National Institute of Technology (India), and research roles at Sejong University (South Korea) and the KINDI Center for Computing Research (Qatar). He earned his Ph.D. from Kyungpook National University's Information Security Lab in South Korea. His research specializes in applied cryptography and cybersecurity , with a focus on lightweight authentication protocols, blockchain integration, IoT security, and quantum-resistant systems. Key domains include electric vehicles, metaverse environments, and federated learning for privacy-preserving analytics. Recent publications emphasize quantum cryptography , physically unclonable functions (PUFs) , and dynamic EV charging security , reflecting a trend toward hardware-efficient and future-proof solutions. He also teaches courses in Cryptography, Network Security, and Web Application Security. Dr. Alavalapati serves on editorial boards for journals including Security and Communication Networks (Hindawi), International Journal of Network Security , and International Journal of Computer Theory and Engineering .
Dr. Ibrahim M. El-Hasnony is a distinguished researcher affiliated with Mansoura University's Faculty of Computer and Information and Zayed University . His work spans machine learning, artificial intelligence, and their applications in healthcare, finance, and IoT systems. Research Focus: Machine Learning for critical domains (healthcare, finance, IoT) Hybrid algorithms (e.g., Tunicate Swarm + Deep Learning) Secure IoT environments and blockchain integration Energy optimization protocols for vehicular networks Deep learning in financial and medical diagnostics Sponsorships: United States Agency for International Development (USAID) Academy of Scientific Research and Technology Cape Peninsula University of Technology National Supercomputer Center in Guangzhou With a strong publication record in journals like IEEE Access and Annals of Operations Research , Dr. El-Hasnony demonstrates interdisciplinary expertise in solving real-world problems through advanced computational methods. His work has been cited 8 times per article on average, with an H-index categorized as 'Fair.'
Dr. Anish Jindal is an Associate Professor at Durham University's Department of Computer Science, with affiliations to the Durham Energy Institute and visiting fellowships at Princeton University. His research focuses on smart cities, energy optimization, AI, and cyber-physical systems. He holds a Ph.D. from India (2018) and has authored/co-authored over 100 publications in top-tier journals/conferences like IEEE Transactions and ACM MobiHoc. Notable awards include IEEE TCSC's Outstanding Ph.D. Dissertation Award (2019) and the IEEE Communication Society's Outstanding Young Researcher Award (2019). Research interests include resource-aware computing, programmable networking, wireless security, and energy-efficient AI. He leads major grants such as the £3M EPSRC CHEDDAR hub (EP/X040518/1) and the £10M National Edge AI Hub (EP/Y028813/1). His work spans 6G networks, edge computing, and IoT applications in smart grids and healthcare. Recent articles emphasize digital twins for IoT security, energy-efficient AI frameworks, and UAV-assisted vehicular edge computing. He actively organizes workshops like IEEE CSR's Data Science for Cyber Security and serves on editorial boards of journals like IET Smart Cities and Software: Practice and Experience.
Mohammad S. Almalag is an Associate Professor at the School of Engineering and Computing at Christopher Newport University . He joined the university in 2018, bringing expertise in Computer Networks , Mobile Ad-hoc Networks , and Cybersecurity . His academic journey includes a PhD in Computer Science from Old Dominion University, MS in Computer Science from Ball State University, and BS in Computer Science from King Saud University, Saudi Arabia. Academic Rank: Associate Professor Research Focus: Network Security, IoT, Vehicular Networks, Cloud Computing Research Interests Professor Almalag's research spans Mobile Ad-hoc Networks , Vehicular Ad-hoc Networks , and Network Security . He explores Sensor Networks , Wireless Communications , and IoT applications in Cloud Computing and Smart University environments. His work addresses Cybersecurity challenges in Higher Education and develops innovative frameworks for Augmented Reality interfaces. Publication Trends His publications from 2020-2022 emphasize IoT , Cloud Computing , and Network Security using optimization algorithms and smart systems. Earlier works (2013-2016) focus on Vehicular Ad-hoc Networks (VANETs) , protocol design, and Cyber-Physical Systems for traffic management. Grants and Research He leads research projects like "Navigating Cybersecurity Compliance Challenges for the Maritime Industry in Southeast Virginia" , sponsored by COVA CCI. This project highlights his commitment to addressing real-world Cybersecurity and Compliance issues.
Dr. Abid Khan is a Senior Lecturer in Cyber Security at the School of Computing and Engineering, University of Derby, England. Previously, he held roles at Aberystwyth University and COMSATS University Islamabad. His research focuses on applied cryptography, privacy in IoT, blockchain, and secure smart grid systems. He is a Senior Member of IEEE and serves as an Associate Editor for IEEE Access. Education: PhD in Computer Science (Harbin Institute of Technology, China), MS in Computer Science (Quaid-i-Azam University, Pakistan), BS in Maths and Physics (University of Punjab, Pakistan). His postdoctoral research at Politecnico di Torino, Italy, focused on e-security. Research interests include secure data aggregation in smart grids, quantum-resistant distributed ledgers, and privacy preservation in vehicular networks. Recent work emphasizes blockchain applications for healthcare data provenance and IoT security frameworks. Teaching responsibilities include modules on Communication & Security Protocols, Security Management, and Enterprise Security Management. His publications span privacy-preserving techniques, blockchain-based solutions, and VANET security. He has contributed frameworks like BCALS (blockchain-based log management) and MobChain (collusion-resistant location proof systems). His work addresses challenges in decentralized systems, fog computing, and federated learning privacy.
Zhenhui Yuan is an Assistant Professor at the University of Warwick, School of Engineering, leading the Connected Robotics Lab. He holds a BEng in Software Engineering from Wuhan University (2008) and a PhD in Electronic Engineering from Dublin City University (2012). His research focuses on machine learning in networking, IoT, and robotics, with expertise in UAV communications, edge AI, and vehicular networks. Prior roles include Senior Lecturer at Northumbria University (2020–2023), Associate Professor at Hangzhou Dianzi University (2015–2019), and co-founder/CTO of RobSense Technology (2015–2019). He has received Best Paper Awards at IEEE ICCRE 2016 and IEEE BMSB 2014. His research interests span machine learning applications in networking, robotics, and IoT, with emphasis on UAV swarm systems, edge computing, and quality-of-service optimization. He serves as a Guest Editor for IEEE journals and chairs workshops on 6G-empowered robotic vehicles. He leads projects funded by the University of Warwick (£9k), British Academy (£9k), and Horizon Europe (£92k), among others. His work includes developing the Connected Robotics Lab’s testbeds for 5G emulation and drone swarm control. Key achievements include pioneering AirSlice (UAV network slicing), founding the SwarmLink radio, and advancing video quality metrics for 3D streaming. He actively supervises PhD candidates and collaborates on grants addressing holographic telesurgery, multimodal transport networks, and EV optimization. His labs focus on hardware-in-the-loop emulation and edge AI for robotic systems.
Lian Zhao is a Professor in the Department of Electrical, Computer and Biomedical Engineering at Toronto Metropolitan University. She holds a Ph.D. from the University of Waterloo and has been with the university since 2003. Her research focuses on wireless communications, edge computing, vehicular networks, and resource management. She is a Fellow of the IEEE and multiple professional organizations. Education: B.Sc. (Civil Aviation University of China, 1990), M.S. (Wuhan University, 1993), Ph.D. (University of Waterloo, 2002), all in electrical engineering. Research Interests include green communication, IoT, centralized/distributed resource management, and incentive mechanisms. She leads the Intelligent Communication and Computing Laboratory and teaches courses such as Digital Communications and Random Processes. Awards include the IEEE VTS Best Land Transportation Paper Award (2016 and 2024), Outstanding New Leader Award (2021), and CFI New Opportunity Award (2004). She serves as an editor for multiple journals, including IEEE Transactions on Wireless Communications and IEEE Internet of Things Journal. Advising: Supervised over 30 graduate students, including Ph.D. and Master’s candidates in areas like vehicular networks, edge computing, and resource allocation. Active in funded research projects on 6G networks, UAV communications, and smart grid systems. Labs/Teams: Leads the Intelligent Communication and Computing Lab, contributing to innovations in vehicular ad-hoc networks, IoT, and green communication technologies.
Xiaojun Zhang is a Professor actively contributing to cloud computing, blockchain technology, data security, and educational technology. His work spans cybersecurity, signal processing, and wireless systems. Key Research Areas: Privacy-preserving data aggregation, machine learning for biomedical imaging, blockchain-based integrity auditing, and educational metacognition studies. Recent Article Trends (2022–2025): Focus on secure federated learning, data denoising algorithms, and blockchain applications in smart grids, healthcare, and education. Collaborations include institutions in China and international researchers.
Boris Sedlak is a PostDoc Researcher and Ph.D. student in the Distributed Systems Group (DSG) at TU Wien, Austria. His research focuses on ensuring runtime requirements in large-scale computing systems through causal inference and active inference concepts, with applications in edge computing, vehicular networks, and distributed systems governance. Education: Ph.D. in Computer Science (Ongoing) at TU Wien, funded by the TEADAL EU Horizon project. M.Sc. in Software Engineering & Internet Computing (Distinction) at TU Wien (2018–2022). B.Sc. in Media Informatics at FH St. Pölten, Austria (2015–2018). Research Interests: Boris specializes in distributed computing continuum systems, active inference for system equilibrium, causal inference in distributed environments, edge computing elasticity, and privacy-preserving data stream processing. He explores applying neuroscience-inspired concepts to computing systems for adaptive and self-organizing solutions. Key Projects: TEADAL (2022–2025): Focuses on federated and trustworthy data lakes in distributed systems. INTEND (2024–2026): Investigates intelligent service adaptations through active inference. AloTwin (2023–2025) and FogProtect (2020–2022): Address edge computing security and data governance. Recent Contributions: Boris has published extensively on adaptive stream processing, SLO-aware task offloading in vehicular platoons, and equilibrium models using active inference. His work bridges causal reasoning and system design, emphasizing scalable solutions for heterogeneous edge infrastructures. Advisory & Collaboration: Supervises bachelor/master theses and actively collaborates on topics involving service-level objectives, causal models, and edge intelligence. He has presented at ICSOC, IEEE Edge Computing, and AIoTwin Summer School.
Dr. Md Arafatur Rahman is a Senior Lecturer in Cyber Security at the School of Engineering, Computing & Mathematical Sciences, Faculty of Science and Engineering, University of Wolverhampton, UK. He previously served as an Associate Professor at Universiti Malaysia Pahang and holds a PhD from the University of Naples Federico II, Italy. He is a Senior Member of IEEE and a Fellow of the Higher Education Academy, with international recognition including the Royal Academy of Engineering Global Talent endorsement. PhD in Electronic and Telecommunications Engineering, University of Naples Federico II, Italy Former Associate Professor, Universiti Malaysia Pahang Postdoctoral Research Fellow, University of Naples Federico II Visiting Researcher, Sapienza University of Rome Dr. Rahman’s research focuses on cutting-edge domains in cyber-physical systems and connectivity. His primary interests include Internet-of-Things (IoT) , Wireless Communication Networks , Cognitive Radio , 5G , Vehicular Communication , Cloud-Fog-Edge Computing , Machine Learning , and Cyber Security . His work bridges theoretical innovation with real-world applications in smart cities, energy-efficient infrastructure, and disaster response systems. The recent publications reflect a strong trend toward intelligent, secure, and scalable systems. Key themes include IoT-enabled smart infrastructure , fog-edge computing for real-time analytics , machine learning in network optimization , and secure data handling in cyber-physical systems . His work frequently appears in top-tier journals like IEEE Transactions and Elsevier journals, emphasizing both technical innovation and societal impact. World Top 2% Scientists List (Stanford University, 2019–2021) Best Paper Award, ICNS’15 (Italy) Best Innovation Award & Gold Medal, MTE 2020 Gold & Silver Medals, iENA’17 Germany Diamond & Gold Medal, BiS’17 UK Best Supervisor Award, UMP Higher Education Academy (HEA) Fellowship IBM Center of Excellence Fellow Royal Academy of Engineering Global Talent (Exceptional Talent, 2022) Dr. Rahman has supervised over 30 students at B.Sc., M.Sc., and PhD levels and led numerous international research grants from UK, EU, Italy, and Malaysia. He has collaborated with industry partners such as FUSI Technology Indonesia, developing commercializable innovations. He serves as an editor and guest editor for journals including IEEE Access and Frontiers in the Internet of Things, and has held leadership roles in major conferences like IEEE Globecom and IEEE DASC. He is actively involved in research labs focusing on IoT, wireless security, and smart infrastructure, contributing to both academic and industrial advancements.
V. Dinesh Reddy is affiliated with SRM University Andhra Pradesh, Department of Computer Science and Engineering in Amaravati, India. He maintains an active research career with publications spanning from 2017 to 2025 across multiple prestigious venues including IEEE Access, Energy Informatics, Quantum Information Processing, and Sensors. Dr. Reddy's research interests span cloud computing infrastructure optimization, edge computing, quantum computing applications, image processing, and cybersecurity. His work demonstrates expertise in developing evolutionary algorithms, machine learning approaches, and optimization techniques to solve complex computing problems with practical applications in IoT security, vehicular networks, and medical diagnostics. His publication record shows consistent output with increasing collaboration and expanding research scope over time. The research demonstrates strong interdisciplinary connections between traditional computer science domains and emerging technologies like quantum computing, addressing real-world challenges in computing infrastructure efficiency and security. Dr. Reddy has collaborated extensively with researchers including G. R. Gangadharan, G. Subrahmanya V. R. K. Rao, Marco Aiello, Md. Muzakkir Hussain, and Ashu Abdul. His research appears well-funded given the scope and diversity of projects, with applications spanning sustainable data centers, edge computing for vehicular networks, and quantum computing implementations. His research spans multiple laboratory contexts, particularly in cloud computing infrastructure, quantum computing applications, and image processing. Dr. Reddy's future research directions appear to be expanding into more specialized quantum computing applications and advanced edge computing scenarios for vehicular networks, as evidenced by his most recent publications from 2024-2025.
Dr. Ruhai Wang is a Professor in the Phillip M. Drayer Department of Electrical and Computer Engineering at Lamar University. He holds a Ph.D. in Electrical/Computer Engineering from New Mexico State University and leads research in space communication networks. His office is located in the Cherry Building (Rm. 2205), and he can be contacted at rwang@lamar.edu or (409) 880-1829. Research Focus: Dr. Wang specializes in Delay-/Disruption-Tolerant Networks (DTN), satellite/space communications, cybersecurity, and wireless ad hoc networks. His work bridges theoretical modeling and practical implementations for space Internet systems, with ongoing projects focused on DTN protocol development for NASA collaborations. Publication Trends: His 15 most recent publications (2016-2020) primarily analyze protocol optimization for space communications, with emphases on Licklider Transmission Protocol (LTP), Bundle Protocol efficiency, deep-space channel modeling, and integrated terrestrial-satellite networks. Key themes include disruption resilience, transmission timing optimization, and network scalability under asymmetric conditions. Awards and Honors: Distinguished Lecturer, IEEE AESS (2025) Teaching Board Member, Ph.D. Program in STIET, University of Genova (2018-Present) Best Associate Editor, IEEE Aerospace & Electronics Systems Magazine (2015) Lamar University Presidential Faculty Fellowship (2015) IEEE ComSoc Best Tutorial Paper Nominee (2009) University Merit Award (2007) Advising and Projects: Currently mentoring doctoral candidates Alaa Sabbagh and Hacer Varol, and MSEE students Qinglin Xie and Arkun Zhuang. His primary project involves developing DTN protocols for space networks through a NASA/JPL-collaborated testbed. Grant-supported research focuses on reliable data delivery in deep-space environments. Professional Service: Senior IEEE member (AESS, ComSoc), Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and IEEE Aerospace & Electronics Systems Magazine. Former TPC co-chair for IEEE ICC and organizer of international workshops on satellite communications.
Vasilios Mamalis is a Professor at the Department of Informatics and Computer Engineering, University of West Attica, and a member of the Collaborating Scientific Staff at the Hellenic Open University's Informatics program. His academic career spans decades with significant contributions to parallel and distributed computing, wireless sensor networks, and cloud technologies. Education: Diploma in Computer Engineering and Informatics, University of Patras (1993) PhD in Computer Engineering and Informatics, University of Patras (1998) Research Interests focus on parallel algorithms, distributed systems, wireless sensor networks, cloud computing, and information retrieval. His work addresses energy efficiency in ad-hoc networks, optimization techniques, and educational technology applications. Publication Trends show extensive work on WSN clustering, cloud task scheduling, parallel simplex methods, and fog computing applications in education and urban systems. He combines metaheuristics with infrastructure optimization in large-scale networks. Scientific Contributions include editorial roles in the Journal of Balkan Libraries Union and program committee memberships in international conferences. He actively reviews for journals and conferences in computing. Teaching Expertise covers operating systems, parallel computing, distributed systems, and cloud technologies at both undergraduate and postgraduate levels. His Research Leadership involves EU/Greek-funded projects on communication protocols, parallel content-based retrieval, and wireless sensor networks.
M. Ilhan Akbas is an Associate Professor in the Department of Electrical Engineering and Computer Science at Embry-Riddle Aeronautical University, where he conducts research in cyber-physical systems, autonomous vehicles, Internet of Things (IoT), and modeling and simulation. He earned his PhD in Computer Engineering from the University of Central Florida and has been actively involved in research funded by the National Science Foundation, Federal Aviation Administration, Office of Naval Research, Florida Center for Cybersecurity, and industry partners. His research focuses on the development and validation of intelligent and connected systems, particularly in transportation and defense domains. He has made significant contributions to the testing and simulation of autonomous vehicles, edge computing for IoT, and secure communications in vehicular networks. His work has been published in top-tier journals such as IEEE Transactions and SAE Edge Reports, and featured in media outlets including Spectrum Bay News 9 and Tampa Bay Business Journal. Dr. Akbas has served on editorial boards for MDPI Sensors and Electronics and on program committees for ACM and IEEE conferences. He previously served as a faculty member at Florida Polytechnic University (2016–2019), where he co-founded the Advanced Mobility Institute and contributed to curriculum development in software engineering and data science. He is a member of IEEE, ACM, and the Complex Systems Society. His recent publications demonstrate a strong trend toward intelligent mobility, autonomous systems, and secure, real-time cyber-physical architectures, with increasing emphasis on simulation, digital twins, and machine learning for transportation and defense applications. Editor, MDPI Journal of Sensors Editor, MDPI Journal of Electronics Member, IEEE Transactions on Aerospace and Electronic Systems Editorial Board Invited Speaker, São Paulo, Brazil (2018, 2019) Dr. Akbas has secured multiple competitive research grants from federal agencies and industry, supporting his work in autonomous systems and cybersecurity. He has advised student researchers and contributed to academic leadership through accreditation and curriculum development. He previously worked at the Institute for Simulation and Training at UCF and has industry experience in defense telecommunications, including multinational standardization efforts. He is actively involved in research labs and teams focused on intelligent mobility and cyber-physical systems, particularly through his leadership in the Advanced Mobility Institute at Florida Poly and ongoing projects at Embry-Riddle. His work bridges academic innovation with real-world applications in smart transportation and aerospace systems.
