جستجوی استاد راهنمای دانشگاهی

Hai Dongمشاهده پروفایل

مدرس ارشد

• Service-Oriented Computing
• Edge Intelligence
• Blockchain
• +۴ مورد دیگر

Dr. Hai Dong is a Senior Lecturer at the School of Computing Technologies, RMIT University in Melbourne, Australia, with promotion to Associate Professor scheduled for 2026. He serves as the Founding Director of the CloudTech-RMIT Green Cryptocurrency Joint Research Laboratory (GreenCryptoLab) and Leader of the Smart Sensing and Services Research Area. Previously, he held research fellow positions at both RMIT University and Curtin University. Dr. Dong is a Senior Member of IEEE and chairs the IEEE Computational Intelligence Society Task Force on Deep Edge Intelligence. Dr. Dong's research spans several cutting-edge domains including Service-Oriented Computing, Edge Intelligence, Blockchain, AI Security, Cyber Security, and Machine Learning. His work bridges theoretical foundations with practical applications, particularly in secure and efficient computing systems. He has developed innovative approaches for smart contract security, edge computing optimization, federated learning, and blockchain applications with a strong focus on sustainability and real-world impact. His publication record demonstrates consistent high-impact contributions across top venues including AAAI, ASE, ICML, TSE, and TSC. Dr. Dong's research shows a clear trajectory toward increasingly sophisticated integration of AI with edge computing and blockchain systems, with growing emphasis on security, privacy, and resource efficiency. Recent work highlights his leadership in addressing emerging challenges in LLM-generated smart contracts and secure federated learning systems. Best Research Paper Award at ICSOC 2016 Best Paper Award at IEEE ICBC 2025 2023 RMIT Award for Research Engagement and Impact - Industry Engagement in Graduate Research Dr. Dong has successfully supervised numerous PhD and Master's students to completion, with many going on to prestigious positions. He has secured over $5 million in research funding as Chief Investigator from sources including ARC, CRC, QNRF, and industry partners like ANZ, CloudTech, and Telstra. His GreenCryptoLab research facility represents a significant industry-academic partnership focused on sustainable blockchain technologies. Dr. Dong maintains active collaborations with researchers worldwide and serves on committees for over 100 international conferences.

• Computer Science
• Wireless Sensor Networks
• Internet of Things (IoT)
• +۳ مورد دیگر

Muhammad Khalil Afzal is a faculty member at COMSATS University Islamabad within the Department of Computer Science . His career focuses on Internet of Things (IoT) , Wireless Sensor Networks , and Machine Learning applications in network optimization. Key collaborations with researchers like Byung-Seo Kim and Sung Won Kim Published extensively in IEEE Access , Sensors , and Future Generation Computer Systems Research spans data-driven intelligence , QoS in IoT , and smart transportation systems : Developed graph convolutional GRU frameworks for traffic prediction Explored NOMA for low-latency communications in 5G Innovated blockchain-based privacy preservation in vehicular networks

• Computer Networking
• Wireless Communications
• Network Virtualization
• +۵ مورد دیگر

Thierry Turletti is a Professor at INRIA with extensive research in computer networking, wireless communications, and network virtualization. His work focuses on network emulation, software-defined networking, 5G networks, and content-centric networking with numerous publications spanning over two decades. His primary research interests include developing advanced network emulation frameworks that maintain high fidelity in distributed environments, optimizing wireless network performance through innovative ray tracing techniques, and creating robust programmable networks with optimal failure recovery. His work bridges theoretical networking concepts with practical implementations, particularly in the areas of mobile edge computing and 5G network optimization. Recent publications demonstrate a clear trend toward solving practical networking challenges in large-scale distributed environments, with emphasis on network emulation fidelity, wireless signal propagation modeling, and network function placement. His research spans broad disciplines including computer networking, telecommunications engineering, and distributed systems, with specific focus on radio frequency mapping, network monitoring, and mobile network optimization. Dr. Turletti has been instrumental in developing network experimentation frameworks and tools that enable researchers to conduct realistic network testing in controlled environments. His work on Distrinet and Sophia-node represents significant contributions to the field of network testbeds and emulation platforms.

• Edge Computing
• Internet of Things
• Vehicular Networks
• +۵ مورد دیگر

Muhammad Bilal is an Associate Professor at Zhejiang University's School of Computer Science, Department of Computer Science and Technology. His research spans multiple cutting-edge domains in computer science and engineering, with a particular focus on edge computing, Internet of Things, and vehicular networks. His research interests include Edge Computing , Internet of Things , Vehicular Networks , Federated Learning , Digital Twins , and Cloud Computing . His work addresses critical challenges in resource allocation, latency optimization, privacy preservation, and intelligent decision-making in distributed computing environments. He has made significant contributions to developing novel frameworks for service caching, computation offloading, and secure data processing in next-generation networks. His recent publications reveal a strong trend toward integrating artificial intelligence with edge and cloud infrastructure, particularly focusing on privacy-preserving techniques and resource-efficient algorithms. His work spans applications from intelligent transportation systems to healthcare monitoring and meteorological services, demonstrating the versatility and real-world impact of his research. Dr. Bilal has established a prolific publication record with numerous high-impact papers in top-tier journals and conferences, reflecting his active engagement in the academic community. His collaborative approach is evident through extensive co-authorship networks, particularly with researchers in China, Pakistan, and internationally.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Matthew Watson is a researcher at Durham University , Department of Computer Science, UK. His work spans Computer Science , Artificial Intelligence , and Human-Computer Interaction , with a focus on autonomous systems , semantic search , and pedagogical tools . Research Trends : Recent publications include applications of machine learning in adaptive cruise control , UAV-based wildlife tracking , and deep learning frameworks like KerasCV/KerasNLP. Earlier work involved mathematical combinatorics and cognitive modeling in dialogue systems. Collaborations : Co-authored with Navid Mohajer, Darius Nahavandi, Ashok K. Krishnamurthy, and others in domains like robotics, bioinformatics, and software engineering. Publications include 13 peer-reviewed articles from 2008–2025, covering topics in control systems , knowledge graphs , and algorithm design .

• 5G/6G Networks
• Wireless Networks
• Mobility Management
• +۵ مورد دیگر

M.Sc. Anna Prado is a Research and Teaching Associate at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich. She holds a B.Sc. in Information Systems and Communication Engineering from Bauman Moscow State Technical University (2017) and an M.Sc. in Communication Engineering from TUM (2020). She is currently pursuing her Ph.D., focusing on mobility management in 5G/6G networks, simulation of wireless systems, and digital twins for 6G. Her research emphasizes minimizing handover occurrences while ensuring smooth user connectivity through optimization and reinforcement learning techniques. Anna's academic role involves contributing to projects like the BMBF-funded 6G-ANNA initiative, which aims to develop holistic 6G systems prioritizing security, sustainability, and flexibility. She collaborates on network architecture design, resource allocation strategies, and resilient communication frameworks. Her work aligns with German technological sovereignty goals, addressing industrial and societal needs through advanced network technologies. Her research interests span 5G/6G networks, wireless resource management, digital twins, and machine learning applications in networks. She has authored/co-authored peer-reviewed papers on topics like admission control, slice dimensioning, energy-efficient edge orchestration, and secure 6G architectures. Her contributions enhance network efficiency, reliability, and adaptability for future communication systems. Anna is actively involved in the FlexComNetsLab and 6G-IP Lab, testing and demonstrating innovative 6G concepts. She participates in conferences and collaborates with industry partners to bridge academic research and real-world deployment.

Boris Koldehofeمشاهده پروفایل

استاد

• Distributed Systems
• Computer Networks
• Software-defined Networking
• +۴ مورد دیگر

Prof. Dr. Boris Koldehofe is a Full Professor of Distributed and Operating Systems at the Technical University of Ilmenau, Germany since 2023. Previously, he held Full Professor of Computer Networks at the University of Groningen (2020–2023) and served as a Senior Researcher/Lecturer at Technical University of Darmstadt (2014–2020). He is also an Adjunct Professor at TU Darmstadt since 2020. Research Focus: Distributed Systems, Software-defined Networking, Complex Event Processing (CEP), Fog Computing, Privacy Engineering Education: Habilitation in Communications and Distributed Systems (2019), PhD in Computer Science (2005) Research Trends : His 2024–2023 publications emphasize analog/memristor-based network computing , privacy-preserving CEP , and time-sensitive networking . Key themes include programmable data planes , AI-driven infrastructure , and energy-efficient systems . Recent work explores federated learning in vehicular networks and privacy engineering for IoT analytics . Projects & Leadership : He leads the DFG CRC 1053 MAKI (2014–2024) and the Parrot: Privacy Engineering for IoT project (2021–). He serves as principal investigator for dynamic Industry 4.0 communication networks and has managed collaborations with institutions like EPFL, University of Stuttgart, and University of Heidelberg.

• Computer Networks
• Telecommunications
• Cloud Computing
• +۷ مورد دیگر

Raouf Boutaba is a Professor at the University of Waterloo, Canada, with a focus on networking and telecommunications research. His work spans computer networks, cloud computing, network security, and software-defined networking (SDN). He has contributed to advancements in 5G/6G networks, network slicing, energy-efficient architectures, and machine learning applications in networking. His research addresses challenges in network monitoring, resilient communication systems, and optimizing network performance through reinforcement learning and intelligent algorithms. He collaborates extensively with researchers globally, publishing in top-tier journals and conferences such as IEEE Transactions on Networking and NOMS. Boutaba’s work often bridges theoretical contributions with practical implementations, emphasizing real-world applicability in telecommunications and distributed systems. His recent focus includes open RAN architectures, edge computing, and securing encrypted traffic in evolving network environments.

• Wireless Communications
• 5G/6G Technologies
• Vehicular Networks
• +۵ مورد دیگر

Shanzhi Chen is affiliated with the China Academy of Telecommunication Technology, specifically the State Key Laboratory of Wireless Mobile Communications in Beijing. He holds a PhD from the Beijing University of Posts and Telecommunications (1997). His research focuses on next-generation wireless communication systems, including vehicular networks (C-V2X), 5G/6G technologies, satellite communication, edge computing, and IoT. Key contributions include work on dynamic resource allocation, beamforming for LEO satellites, and AI-driven network architectures. Research Interests: Wireless Communications Vehicular Networks & C-V2X 5G/6G System Design LEO Satellite Systems Edge Computing & IoT Machine Learning for Networks Publications (2023–2025) emphasize cutting-edge topics like beam-space multiplexing using metasurfaces, reinforcement learning for UAV networks, and UCAN architectures for 6G. His work bridges theoretical advancements with practical applications in smart transportation and satellite-terrestrial integration.

• Edge Computing
• 5G Networks
• Serverless Applications
• +۴ مورد دیگر

Dr. Balázs Sonkoly is a researcher specializing in edge computing, serverless applications, and 5G network optimization. His work focuses on latency-sensitive systems, multi-user augmented reality coordination, and cloud-native microservice management across distributed architectures. Key research themes include network function virtualization (NFV), software-defined networking (SDN), and programmable packet-optical networks Recent publications analyze AI-driven autoscaling, P4-assisted serverless migration, and multi-domain service orchestration Article trends reveal expertise in mixed reality frameworks, federated learning for vehicular networks, and edge-cloud convergence. His collaborations span institutions like IEEE, SIGCOMM, and the UNIFY project. Contributions to conferences like NOMS, ISMAR, and GLOBECOM highlight practical implementations of edge cloud platforms, SLAM integration, and latency-constrained resource allocation.

• Computer Science
• Engineering
• Intelligent Transportation Systems
• +۳ مورد دیگر

Professor Weisong Shi is a faculty member at Wayne State University, leading the Connected and Autonomous Driving Laboratory. His research focuses on enabling technologies for connected and autonomous driving, including edge computing, communication systems, data analytics, and cybersecurity solutions. He holds the title of Fellow of the IEEE (FIEEE), indicating significant contributions to the field. Research interests emphasize integrating cyber-physical systems, vehicular networks, and smart transportation infrastructure. His work addresses challenges in real-time data processing, secure execution environments, and privacy-preserving tools for autonomous systems. No scientific awards or grants are explicitly mentioned in the provided text. The laboratory represents a key platform for advancing autonomous driving technologies through interdisciplinary collaboration.

Samaneh Rashidibajganمشاهده پروفایل

مدرس

• Cybersecurity
• Ad Hoc Networks
• Opportunistic Networks (OppNets)
• +۵ مورد دیگر

Dr. Samaneh Rashidibajgan is a Lecturer in Computer Science at the School of Computer Science & Engineering , Constructor University Bremen, Germany. She holds a Doctoral Degree in Information Systems and Cybersecurity from Münster University (2023). Her academic career spans roles as a Research Assistant at Rostock University (2015–2019) and Research & Teaching Assistant at Münster University (2019–2022). Research Interests : Security in Opportunistic Networks (OppNets), Privacy Preservation in Ad Hoc Networks, Solutions for Vehicular OppNets, and Security in Cyber-Physical Systems. She explores blockchain integration for network integrity, machine learning for performance optimization, and trust models to counter attacks like Sybil and selective dropping. Publications : Her work focuses on cybersecurity trends in decentralized systems, including blockchain for OppNets, privacy-preserving routing algorithms, and attack detection mechanisms. Key contributions include cluster-based routing for privacy, trust frameworks for Sybil attacks, and key-sharing methods in OppNets. Work Experience : 2024–Present : Lecturer and Researcher, Constructor University. 2019–2022 : Research & Teaching Assistant, Münster University. 2015–2019 : Research Assistant, Rostock University.

• French Language Practice
• Romance Studies
• Computer Vision
• +۳ مورد دیگر

Viridiane Fay is a researcher in the Institute of Modern Languages and Romance Studies at the University of Würzburg , specializing in French language practice and applied computational methods. During lecture periods, she holds office hours every Tuesday from 1 p.m. to 2 p.m., with appointments available during semester breaks. Role: French Editor, Language Practice Location: Am Hubland, 97074 Würzburg Contact: viridiane.fay@uni-wuerzburg.de Her research spans two distinct domains: French language pedagogy and computer vision/AI . While her institutional affiliation focuses on Romance Studies, her publication record reveals expertise in: Medical and underwater image processing Transformer-based architectures Federated learning and network optimization Watermarking and security algorithms Multi-modal AI applications Neuroscience signal analysis Recent work includes lightweight segmentation models (e.g., ContextFormer), drone/aerial imagery detection frameworks (CH-YOLO-Lite), and privacy-preserving AI systems (Find). Despite limited biographical details in the scrape, her 30+ publications since 2017 suggest significant technical contributions.

• Cognitive Radio Networks
• Reinforcement Learning Applications
• Wireless Communications
• +۷ مورد دیگر

Professor Kok-Lim Alvin Yau is an accomplished academic at Taylor's University in Malaysia, specializing in cognitive radio networks, reinforcement learning applications, and intelligent communications systems. With over 75 publications spanning from 2011 to 2025, he has established himself as a leading researcher in wireless networking and artificial intelligence applications in communications. His research interests encompass cognitive radio networks, reinforcement learning for networking applications, vehicular communications, edge computing, and the integration of AI in communication systems. Professor Yau's work demonstrates a consistent focus on applying machine learning techniques to solve complex networking challenges, particularly in dynamic spectrum access and resource allocation problems. Analysis of his recent publications (2023-2025) reveals a strategic shift toward more interdisciplinary research, combining reinforcement learning with generative AI techniques, exploring semantic communications, and addressing challenges in 6G-enabled vehicular networks. His work shows increasing emphasis on practical implementations and real-world applications of theoretical concepts, particularly in intelligent transportation systems and edge computing environments. Professor Yau has made significant contributions through numerous survey papers that have helped shape research directions in cognitive radio networks and reinforcement learning applications. His editorial work for special issues in IEEE Access and other journals demonstrates his standing in the academic community. He has successfully supervised multiple PhD students including Geong Sen Poh, Mee Hong Ling, and Aqeel Raza Syed, with whom he continues to collaborate on research projects. His international collaborations span institutions in China, Pakistan, and the UK, reflecting the global recognition of his research expertise.

• Artificial Intelligence
• Machine Learning
• Edge Computing
• +۷ مورد دیگر

Huan Liu is a Professor at Arizona State University's School of Computing, Informatics, and Decision Systems Engineering, with research spanning artificial intelligence, edge computing, and interdisciplinary applications. His work bridges theoretical advances with real-world implementations across healthcare, transportation, and environmental systems. His primary research interests include: Artificial Intelligence and Machine Learning for complex system optimization Edge-Cloud Computing architectures for IoT and vehicular networks Medical image analysis and clinical decision support systems Graph neural networks and multimodal learning Privacy-preserving federated learning frameworks Recent publications demonstrate strong emphasis on applied AI, with 15+ 2025 papers addressing UAV swarm intelligence, medical diagnostics, and sustainable transportation through novel algorithmic approaches. Publication trends reveal consistent leadership in: Developing efficient edge computing solutions for dynamic environments Creating medical AI tools with clinical validation Innovating in graph-based and multimodal learning Applying optimization techniques to logistics and environmental challenges His work frequently appears in top venues including IEEE Transactions, Bioinformatics, and AAAI.