جستجوی استاد راهنمای دانشگاهی

Mohammad Shojafar (M'17-SM'19) is an Associate Professor at the Institute for Communication Systems within the Faculty of Engineering and Physical Sciences at the University of Surrey , UK. He has secured over £1.9M in research funding as Principal Investigator for projects like ORAN-TWIN (EPSRC), PRISENODE (MSCA-IF), TRACE-V2X (MSCA-SE), and D-XPERT (Innovate UK), among others. Previously held positions include Senior Researcher at University of Toronto and Toronto Metropolitan University, Senior Researcher at Italian universities (Telecom Italia Mobile), and Postdoc at University of Padua Key affiliations: Associate Editor for IEEE Transactions on Network and Service Management, Intelligent Transportation Systems, Green Communications and Networking, and Consumer Electronics Magazine Research Specialism: 5G/6G Security and Privacy Open-RAN Security Green Networking Adversarial Machine Learning Applied Cryptography Publication Trends: Focus on Open RAN security challenges (bearer context migration poisoning, KPI poisoning attacks), IoT/Fog security (GAN-based attacks, distributed intrusion detection), Lightweight Cryptography (multi-signature protocols, authentication schemes), and AI-driven Network Optimization (federated learning, reinforcement learning applications). Recent work addresses security in vehicular networks, smart grids, and video streaming frameworks. Scientific Recognition: Marie Curie Individual Fellowship (MSCA-GF-IF) Intel Innovator ACM Professional Member Sustainability Fellow at Institute for Sustainability IEEE Senior Member Supervision: Currently supervising 6 PhD students and has graduated 5 PhD/MSc students since 2021. Active in 5G/Open RAN security research with over 20 related publications since 2022.

• Network Security and Privacy
• Open-RAN Security and Privacy
• Green Networking
• +۲ مورد دیگر

Dr. Muhammad Fahim is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on AI-driven solutions for healthcare, including wearable sensor data analysis, deep learning models for healthcare platforms, and integrating intelligence into digital twins for societal impact. He specializes in multimodal sensor data, energy expenditure estimation, and activity recognition in smart homes. His work spans projects such as TUDOR (Ubiquitous 3D Open Resilient Network) and MISO (Atmospheric Carbon Monitoring). He has been awarded the Queen's Merit Fellowship and SEDA Leading Undergraduate Programmes Certification. His research interests include edge intelligence, quantum-based models, and proactive health monitoring systems. Dr. Fahim collaborates internationally and has contributed to over 60 publications in areas like smart healthcare systems, network security, and environmental modeling. He actively participates in academic activities, including PhD examinations and invited talks on AI and wearable computing.

• AI in Healthcare
• Deep Learning
• Multimodal Sensor Data
• +۷ مورد دیگر

Prof. Huan Nguyen is a Professor of Digital Communication Engineering at Middlesex University, affiliated with the Faculty of Science and Technology's Design Engineering & Mathematics department. He leads the London Digital Twin Research Centre and the 5G/6G & IoT Research Group. He holds a PhD from the University of New South Wales (2007) and a BSc from Hanoi University of Science & Technology (2000). Research Interests: Digital twin modeling, machine learning for disaster management and structural health monitoring, 5G/6G communication systems, and IoT. His work focuses on smart factories, critical infrastructure resilience, and healthcare applications like stroke care via digital twins. Grants & Leadership: Secured £2.5M+ in grants, including projects on quantum-assisted digital twinning (QuanDT, £93K), cognitive twins for Dubai manufacturing (£270K), and stroke care in Vietnam/Indonesia (StrokeDT, £99.8K). Served as PI or Co-I on 15+ grants from EPSRC, British Council, and industry partners. Teaching: Currently teaches Digital Communication Systems and Major Project modules. Previously instructed courses in digital communications, wireless systems, and telecommunications at Middlesex and other institutions. Awards & Roles: Senior Fellow of the HEA (2019), Senior IEEE Member, and Chair of the Vietnamese Intellectual Society in the UK/Ireland. Editor for KSII Transactions on Internet and Information Systems and REV Journal on Electronics and Communications . Labs & Teams: Leads research groups focused on digital twins, 5G/6G, and IoT. Collaborates with global partners like VinGroup, Vietnamese universities, and UK institutions on Industry 4.0 and healthcare innovation.

• Digital Twin Modeling
• Machine Learning
• Wireless Communications
• +۵ مورد دیگر

Dr. Seyed Ahmad Soleymani is a Research Fellow at the University of Surrey's Institute for Communication Systems and part of the 5G/6G Innovation Centre. His research focuses on cybersecurity, edge computing, IoT, UAV systems, and 5G/6G networks. He has contributed to secure authentication protocols for medical and industrial IoT systems, UAV-assisted edge computing optimization, and multi-target tracking algorithms using Q-learning. His work emphasizes energy efficiency, data security, and real-time applications in smart manufacturing and vehicular networks. Research interests include secure communication in UAV networks, sustainable edge node deployment, and privacy-preserving authentication schemes. He has explored applications such as flood forecasting via UAV-assisted sensors and energy-efficient building systems. His publications span IEEE journals and conferences, addressing challenges in edge computing resource allocation, intrusion detection systems, and trust management in 5G-IIoT environments. Collaborations involve institutions like the University of Electronic Science and Technology of China and Universiti Teknologi Malaysia. Notable contributions include the MI3SE encryption scheme for outdoor IIoT devices and the TRUTH trust scheme for 5G industrial IoT. His work combines machine learning (e.g., SAC, Q-learning) with network optimization to address latency, security, and scalability in modern communication systems. He has also developed frameworks for cybertwin-based 6G networking and secured target tracking in O-RAN environments.

• Cybersecurity
• Edge Computing
• Internet of Things (IoT)
• +۳ مورد دیگر

Dr. Ghazanfar Ali Safdar is a Senior Lecturer in Computer Networking at the University of Bedfordshire's School of Computer Science and Technology (part of the Faculty of Creative Arts, Technologies and Science). He holds a PhD from Queen's University Belfast (2005) and has extensive industry experience with organizations like Schlumberger and Siemens. His research focuses on energy-efficient wireless protocols, cybersecurity in communication networks, and green networking. Key areas include cognitive radio networks, 5G/6G technologies, IoT, and D2D communications. He has led projects on interference mitigation in LTE systems and spectrum sensing for cognitive radios. Editorial Roles: Associate Editor for IET Networks, Editor-in-Chief for EAI Transactions on Energy Web Supervised 9+ PhD students (e.g., on Femtocells, Energy Management in LTE, and V2X Security) Awards: Vice Chancellor’s Course of Year Award (2017), Best Teacher Nomination (2018) His technical expertise spans OPNET simulation, antenna design for wearables, and security protocols for vehicular networks. Current research includes history-assisted spectrum sensing and connected vehicle cybersecurity.

• Energy Efficient Communication Networks
• Wireless Networking
• Cyber Security
• +۷ مورد دیگر

Dr. Muhammad Asad is a Lecturer in Computer Science at the School of Engineering, Computing and Mathematics. With 13+ years of research experience, his work focuses on federated learning, wireless communication systems, and IoT network optimization. Primary Role: Lecturer in Computer Science Key Research Areas: Federated Learning, Wireless Communication, and IoT Security His research spans communication-efficient AI systems, blockchain-integrated learning frameworks, and energy optimization in sensor networks. Recent work includes security-enhanced federated learning protocols for vehicular networks and healthcare analytics. Publications (2018-2024) demonstrate consistent contributions to fields including: Privacy-preserving machine learning IoT-oriented network architectures Blockchain-based security systems Medical imaging diagnostics

• Federated Learning
• Wireless Communication
• Blockchain Technologies
• +۷ مورد دیگر

Michele Sevegnani is a Senior Lecturer in the School of Computing Science at the University of Glasgow, where he also earned his PhD. His work focuses on formal methods, particularly bigraphs with sharing, for modeling and verifying complex, location-aware, event-based systems. He is actively involved in major research initiatives including Probable Futures, TransiT, and CHEDDAR, funded by Responsible AI UK, UKRI, and industry partners. Education: PhD in Computing Science, University of Glasgow MSc in Bioinformatics, University of Edinburgh and University of Trento His research interests include formal verification, digital twins, probabilistic model checking, IoT, mixed-reality systems, and human-autonomy teaming. He has developed BigraphER, an open-source suite for bigraph simulation and analysis. His recent work addresses formal modeling of BDI agents, 5G/6G protocols, and AI in law enforcement. His publications span formal methods, AI, networking, and human-robot interaction, showing a consistent focus on applying rigorous mathematical models to real-world systems. Trends include runtime verification, safety assurance in autonomous systems, and the integration of AI with formal guarantees. Scientific Awards: Nominated for the BCS Distinguished Dissertation Award (2013) Recipient of Amazon Research Award (2022) He advises multiple PhD students and postdoctoral researchers. He has secured grants from the Royal Society of Edinburgh, Taiwan’s Ministry of Science and Technology, and Amazon. He has been a visiting researcher at UC Berkeley and collaborates with institutions in France and Taiwan. He leads the development of BigraphER and is a member of the editorial board of Science of Computer Programming . He regularly presents at international venues and workshops on formal methods and AI safety.

• Formal Methods
• Bigraphs with Sharing
• Formal Verification
• +۱۷ مورد دیگر

Victor-Alexandru Darvariu is a Retained Lecturer in Engineering Science at Jesus College, University of Oxford, and a Postdoctoral Research Assistant at the Oxford Robotics Institute. He is also an Honorary Research Fellow at UCL Computer Science. His academic journey includes a PhD in Computer Science from University College London (UCL, 2023), an MSci in Computer Science from the University of Birmingham (2018), and pre-university education in Moldavia, Romania. His research focuses on developing AI techniques for decision-making problems, with a particular emphasis on reinforcement learning, graph theory, combinatorial optimization, and multi-agent systems. Recent projects include mission planning for underwater gliders and causal discovery using reinforcement learning. His work bridges theoretical foundations with practical applications in robotics, operations research, and causal inference. Key publications include contributions to causal discovery via model-based RL, bike-sharing system optimization, and graph reinforcement learning for combinatorial problems. Code and data for many projects are publicly available. He actively shares research updates on platforms like Bluesky, highlighting collaborations and methodological innovations.

• Reinforcement Learning
• Graph Learning
• Combinatorial Optimization
• +۴ مورد دیگر

Professor Hamid Jahankhani is a Professor at Northumbria University with expertise in cybersecurity and digital forensics. He holds a PhD from Queen Mary College, University of London, and previously served as Professor of Information Security and Cyber Criminology at the University of East London. His research focuses on cybersecurity, information security, digital forensics, and critical national infrastructure protection. His work emphasizes industrial partnerships and relevance to law enforcement agencies across the UK and Europe. Professor Jahankhani serves as Editor-in-Chief of the International Journal of Electronic Security and Digital Forensics and chairs the annual International Conference on Global Security, Safety and Sustainability (ICGS3). He has authored over 30 books and 300 publications. Notable Academic Contributions: Supervised 14 PhD/professional doctorate students to completion Overseen 67 PhD students

• Cybersecurity
• Information Security
• Digital Forensics
• +۲ مورد دیگر

Shidrokh Goudarzi is a Senior Lecturer in Computer Science at the School of Computing and Engineering, University of West London. She previously held academic positions at the Centre for Vision, Speech, and Signal Processing (CVSSP) at the University of Surrey and as a senior lecturer at Universiti Kebangsaan Malaysia (UKM). She holds a PhD in Communication Systems and Wireless Networks. Her research focuses on wireless networks, artificial intelligence, machine learning, IoT, and cloud computing, with contributions to resilient IoT technologies and smart city applications. She has designed architectures for smart IoT systems and developed models for distributed communications and vehicular networks. Her work bridges theoretical advancements with industry-relevant solutions. Dr. Goudarzi serves on the editorial boards of high-ranked journals including IEEE Transactions on Industrial Informatics and IEEE Transactions on Network Science and Engineering. She also reviews for reputable journals like Computational Intelligence and KSII Transactions on Internet and Information Systems. She teaches courses such as MSc Communication Systems, BSc Computer Science, and BSc Artificial Intelligence, reflecting her expertise in both theoretical and applied computing disciplines.

• Wireless Networks
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر