Find Academic Supervisors

• Smart Systems
• Optimum Resource Allocation
• Massive MIMO Systems
• +13 more

Dhammika Jayalath is an Associate Professor at Queensland University of Technology (QUT) in the School of Electrical Engineering & Robotics within the Faculty of Engineering. He has been with QUT since 2007, initially as a Senior Lecturer and later promoted to Associate Professor. Prior to joining QUT, he worked as a Senior Researcher at National ICT Australia Ltd and held a Fellowship at the Australian National University. His educational background includes a PhD in Wireless Communications from Monash University and a Graduate Certificate in Higher Education from QUT. He is a Senior Member of IEEE and active in multiple IEEE societies including Communications, Signal Processing, and Vehicular Technology. Research Interests: Dhammika's research focuses on Smart Systems with particular expertise in wireless communications and networking. His work spans Physical Layer Security, Massive MIMO Systems, Internet of Things, Optimum Resource Allocation, Cooperative communications, Cognitive radio, and Vehicular communications. He has made significant contributions to 5G New Radio, Chaotic Communications, Orthogonal Frequency Division Multiplexing (OFDM), and Space-Time Signal Processing. Publication Trends: His recent publications demonstrate a strong focus on 5G/6G networking technologies, physical layer security for IoT devices, and optimization of wireless communication systems. His work bridges theoretical communications theory with practical implementation challenges, particularly in vehicular networks, secure communications, and resource allocation for heterogeneous networks. The articles show increasing interdisciplinary work, combining machine learning techniques with traditional communications engineering approaches. Scientific Awards: 2007: Early Career Academic Recruitment and Development (ECARD) award from QUT 2009: Elevated to Senior Member Grade of IEEE 2000: IEEE travel grant Multiple scholarships during graduate studies at Monash University Supervision and Grants: Professor Jayalath has supervised numerous PhD students to completion with research topics including chaotic communication systems, resource allocation in heterogeneous networks, and vehicular communication systems. He has secured multiple research grants totaling over AU $300,000, including projects from ARC, QUT internal grants, and industry partnerships with Queensland Fire and Emergency Services. His current research includes physical layer security frameworks for IoT devices and optimization of massive MIMO systems for dense mobile networks. Laboratory and Team Work: He has been instrumental in establishing wireless communications research capabilities at QUT, including securing equipment grants for Software Defined Radio platforms. His work often involves interdisciplinary collaboration with researchers in signal processing, cybersecurity, and transportation systems.

Xiang SunView profile

Assistant Professor

• Mobile Edge Computing
• Internet of Things (IoT)
• Drone-assisted Mobile Access Networks
• +5 more

Dr. Xiang Sun is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of New Mexico (UNM). He holds a Ph.D. in Electrical Engineering from New Jersey Institute of Technology (2018), and M.E. and B.E. degrees from Hebei University of Engineering (2011 and 2008). His research focuses on Mobile Edge Computing, IoT, Drone-assisted Networks, Green Computing, and Data Center Optimization. Dr. Sun has been recognized with awards such as the 2018 InterDigital Innovation Award and NJIT Hashimoto Prize. Education: Ph.D., Electrical Engineering, NJIT (2018) M.E., Computer Applications Technology, Hebei University (2011) B.E., Electronic Information, Hebei University (2008) Research Interests: His work emphasizes IoT resource caching, semantic discovery, green communications, and drone-based mobile access networks. He also explores machine learning applications in edge computing and cybersecurity. Publications & Contributions: Dr. Sun has authored over 40 journal/conference papers, including impactful work on cloudlet networks and IoT semantic mashup. His research has been published in IEEE Transactions, Communications Letters, and top-tier conferences like ICC and GLOBECOM. Awards: 2018 InterDigital Innovation Award 2018 NJIT Hashimoto Prize 2017 IEEE Communications Letters Exemplary Reviewer 2016 IEEE ICC Best Paper Award Professional Activities: He serves as a TPC member for IEEE CCNC and MobiEdge, and reviewer for top journals like IEEE Transactions on Cloud Computing and IEEE Internet of Things Journal. He co-chairs the Social Computing and Semantic Data Mining symposium at IEEE ICNC 2019. Labs & Teams: Active in UNM's Electrical & Computer Engineering labs, focusing on mobile edge computing and IoT innovation. Collaborates with industry partners like InterDigital Communications.

Hongxin HuView profile

Professor

• Network Security
• Machine Learning for Security
• IoT Security
• +4 more

Hongxin Hu is a Professor and Associate Chair in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York (SUNY). His research spans security, networking, and machine learning, with publications across top conferences including security (S&P, CCS, USENIX Security, and NDSS), networking (SIGCOMM and NSDI), machine learning (NeurIPS, ICML, and EMNLP), and human-computer interaction (CHI and CSCW). His work has been funded by NSF (SaTC, CNS, IIS, OAC, SOC), USDOT, VMware, Amazon, Google, and Dell. Dr. Hu earned his PhD in Computer Science and Engineering from Arizona State University in 2012. His academic journey has led him to become a prominent researcher in cybersecurity with a strong publication record and significant research impact. Dr. Hu's research interests encompass a wide range of topics at the intersection of security, networking, and artificial intelligence. His work focuses on Emerging Network Technologies and Security (5G/Future-G, NFV, SDN, Edge computing), Machine Learning for Security and Privacy , Security and Privacy in IoT and Cyber-Physical Systems , and AI for Social Good (addressing online abuse, unsafe children's games, and cyberbullying). His interdisciplinary approach has enabled him to tackle complex security challenges through innovative solutions that combine networking expertise with machine learning techniques. His recent publications demonstrate a strong trend toward applying large language models and advanced machine learning techniques to security challenges, particularly in content moderation, vulnerability detection, and privacy protection. The research spans multiple domains including voice assistant security, IoT security, network security, and social media safety, showing a consistent pattern of addressing real-world security problems with cutting-edge technical approaches. IEEE Big Data Security Senior Research Award (2025) ACM SACMAT Test-of-Time Award (2024) NSF CAREER Award (2019) Multiple Best Paper Awards from ACM ASIACCS (2022), ACSAC (2020), IEEE ICC (2020), and ACM SIGCSE (2018) Amazon Faculty Research Award (2022) First Place Award in ACM SIGCOMM 2018 Student Research Competition Dr. Hu has successfully advised multiple PhD students, including Nishant Vishwamitra who joined UT San Antonio as a tenure-track Assistant Professor. His research has been generously funded by major agencies and industry partners. As an active member of the academic community, he serves as Associate Editor for IEEE Transactions on Dependable and Secure Computing and Computers & Security, and has held numerous leadership roles in major security conferences including TPC Co-Chair for ASONAM 2025 and IWSPA 2024/2025. Dr. Hu leads a vibrant research group that has produced significant contributions in network security function virtualization, intrusion detection systems, and privacy-preserving technologies. Current projects include developing LLM-assisted vulnerability detection systems, defenses against jailbreak attacks on large language models, and security mechanisms for emerging networking technologies. His team's work on IoT security, voice assistant applications, and online content moderation has received wide recognition and press coverage.

Muhammad UsmanView profile

Senior Lecturer

• Cloud Computing
• Edge Computing
• Distributed Systems
• +7 more

Dr. Muhammad Usman is a Senior Lecturer at the Department of Mathematics and Computer Science, Karlstad University, Sweden. His research focuses on cloud and edge computing, distributed systems, performance observability, DevOps automation, and networked systems. He holds a B.S. from NUST (Pakistan), and integrated M.S./Ph.D. from GIST (South Korea). He teaches master's-level courses in Distributed Systems and Cloud Computing. His research interests include optimizing container orchestration for edge-IoT workloads, developing AI-driven frameworks for industrial IoT (e.g., AIDA), and enhancing observability of distributed systems through frameworks like DESK and SmartX. His work often addresses challenges in resource efficiency, scalability, and fault detection in edge and cloud environments. Notable contributions include benchmarking lightweight container orchestration platforms, designing cost-effective testbeds for DevSecOps, and creating visualization frameworks for SDN-enabled clouds. His publications span topics from IIoT lifecycle management to intent-based network control. Usman actively collaborates internationally, with projects involving institutions like GIST, Aalto University, and the IEEE community. His work bridges theoretical research and practical applications in edge computing and cloud-native systems.

Adlen KSENTINIView profile

Professor

• Mobile and Wireless Networks
• Software Defined Networking (SDN)
• Mobile Edge Computing (MEC)
• +7 more

Adlen KSENTINI is a Professor at EURECOM's Communication Systems department, specializing in advanced networking technologies. His research focuses on Mobile and Wireless Networks, Software Defined Networking (SDN), Mobile Edge Computing (MEC), Network Function Virtualization (NFV), and Content Delivery Networks (CDN), with an emphasis on performance evaluation and network virtualization. He has contributed to projects like AC3 and 6G-BRICKS, exploring cloud-edge continuum integration and 6G infrastructure. Key research interests include virtualized mobile core networks, carrier cloud systems, and AI-driven network management. He has received Best Paper Awards at IEEE WCNC 2018 and IWCMC 2016 for works on network slicing and LTE modeling accuracy. His work often integrates machine learning for optimization, sustainability, and security in 5G/6G networks. Distinctions: Two Best Paper Awards Labs/Teams: Involved in EU-funded projects like AC3 and 6G-BRICKS Grants: Not explicitly listed, but active in collaborative research initiatives

• Computer Networking
• Software-Defined Networking (SDN)
• Distributed Systems
• +3 more

Mario Baldi is a researcher affiliated with the Polytechnic University of Turin, Italy , with significant contributions to computer networking , distributed systems , and software-defined networking . Key research themes: network function virtualization , programmable dataplanes , time-driven scheduling , and traffic analysis . Recent work focuses on RDMA-enabled compute offloading (2023) and DNN inference in network data planes (2023). Longstanding expertise in multicast routing , voice/data packet efficiency , and XML-based protocol parsing (2000–2006). Collaboration network includes Yoram Ofek , Fulvio Risso , and Han Hee Song , with 99+ publications spanning 1994–2023.

• Cybersecurity
• Network Protocols
• Cloud Computing
• +7 more

Damir Regvart is a lecturer at Algebra University of Applied Sciences , specializing in Cybersecurity , Network Protocols , and Cloud Computing . With a background in Electrical Engineering and a Master's in Electrical Engineering from the Faculty of Electrical Engineering and Computing in Zagreb (2002), he focuses on advanced network security protocols, Zero-touch technologies, and cloud infrastructure. Research Highlights : Zero Trust Architecture, Honeypot Deception Strategies, Machine Learning in Threat Detection, Microsoft Azure Security, and Infrastructure as Code hardening. Key Projects : Pan-European and national initiatives in network automation, cloud forensics, and IoT security. Recent Publications (2024-2025) explore cutting-edge topics like AI-driven security testing, forensic capabilities in cloud environments, and the intersection of SDN and cybersecurity. His work addresses vulnerabilities in cryptographic systems and the legal implications of digital signatures. Technology Focus : Zero-touch provisioning, Microsoft Sentinel automation, and RedFish/vSphere API integration.

Marko ŠaracView profile

Professor

• Cybersecurity
• Artificial Intelligence
• Blockchain Technology
• +7 more

Marko Šarac is a Professor at Singidunum University in the Faculty of Informatics and Computer Science . He holds a Master's degree in Contemporary Information Technologies (2008) and a PhD in Advanced Protection Systems (2013) from the same institution. His research spans Cybersecurity, Artificial Intelligence, Blockchain, Internet of Things (IoT), Machine Learning, and Data Privacy . Education: Master: Contemporary Information Technologies, Singidunum University, 2008 PhD: Advanced Protection Systems, Singidunum University, 2013 Research Focus: SSL Traffic Security, Virtual Datacenters, Biometric Cryptography, and IoT Healthcare Systems Developed frameworks for Explainable AI in Metaverse Security , Blockchain-based IoT Security Gateways , and Machine Learning for Medical Diagnostics Notable Publications: 2025: CNN-enhanced attack detection for IoT-based Metaverse 2024: Modified Firefly Algorithm for medical dataset classification 2023: Space weather prediction using metaheuristics Projects: Co-author on 9+ books including Internet Marketing (2020) and Computer Network Security (2014) Contributed to 50+ peer-reviewed journals and conference papers on cybersecurity and AI Grants & Collaborations: Active in IEEE , ZINC , and Sinteza conference series Collaborated with researchers across Europe and Asia on IoT, Blockchain, and Cloud Security Contact: msarac@singidunum.ac.rs

Marchegiani Maria LetiziaView profile

Assistant Professor

• Signal Processing
• Machine Learning
• Robotics
• +9 more

Maria Letizia Marchegiani is an Assistant Professor at the University of Parma , affiliated with the Department of Engineering and Architecture . Previously, she held academic positions at Aalborg University (2019) and Oxford Robotics Institute (2014-2018). Education: PhD in Computer Science and Engineering from Sapienza - University of Rome , MSc/BEng in Computer Engineering Her research interests span signal processing , machine learning , and their applications to robotics , autonomous systems , intelligent transportation , and intelligent healthcare . She explores intersections between auditory perception , cognitive modeling , and energy-efficient wearable systems . Recent publications demonstrate expertise in acoustic event localization , ML-SDWSN architectures , thermal camera integration for vehicles, and privacy-preserving wearable systems . Her work addresses challenges in network reliability , urban soundscapes , and human-robot collaboration .

• Multi-objective optimisation
• Evolutionary computation
• Explainable artificial intelligence
• +4 more

Dr David Walker is a Senior Lecturer in Computer Science at the University of Exeter and a member of the Institute for Data Science and Artificial Intelligence . He also contributes to the Environmental Intelligence @Exeter research network. Education: PhD in Computer Science, University of Exeter (2008–2013) BSc (Hons) in Computer Science, University of Exeter (2004–2007) Research Interests Dr Walker’s work sits at the intersection of multi-objective optimisation , evolutionary computation , explainable AI and hyper-heuristics . He develops algorithms and visual analytics that help engineers and scientists understand complex optimisation landscapes, with recent emphasis on renewable-energy planning (especially offshore wind farms) and trustworthy AI systems. Publication Trends Between 2022 and 2025 he produced a prolific stream of articles on explainable optimisation , many-objective wind-farm design and visual analytics for evolutionary algorithms . These works combine rigorous algorithmic innovation with real-world case studies, demonstrating a clear trajectory toward transparent, human-centred AI for engineering decision-making. Scientific Awards No specific awards or fellowships are mentioned in the provided material. Advising & Funding No explicit list of PhD students, post-docs or grant awards is supplied. Laboratory & Teams Dr Walker is affiliated with the Institute for Data Science and Artificial Intelligence and the Environmental Intelligence @Exeter network, indicating collaborative, interdisciplinary research environments.

Justin LipmanView profile

Professor

• Cybersecurity
• Internet of Things (IoT)
• Wireless Communications
• +6 more

Justin Lipman is a Professor in the School of Electrical and Data Engineering at the University of Technology Sydney (UTS). He serves as Director of the Cyber Digital Centre and previously led the RF and Communications Technologies Lab. With over 12 years of industry experience at Intel and Alcatel, his expertise spans cybersecurity, IoT, 5G/O-RAN, digital agriculture, and smart cities. Lipman holds a PhD in Telecommunications Engineering from the University of Wollongong. Research & Funding Secured $35M+ in research grants, including projects like UTS Vault ($8M) and the Nokia 5G Futures Lab. Focus areas: Cybersecurity, IoT infrastructure, wireless communications, and smart agriculture. 24 U.S. patents granted, including innovations in IoT security and metamaterials. Education PhD in Telecommunications Engineering (University of Wollongong, 2004) Industry experience: Chief Architect at Intel (2006–2016), Program Manager at Alcatel-Lucent (2005). Awards & Recognition IEEE Senior Member (2012) Leadership roles: Deputy Chief Scientist (Food Agility CRC), Board Director (Internet of Things Alliance Australia). Teaching & Labs Supervises HDR/PhD students in areas like SDN and IoT. Labs: RF and Communications Lab, BlueSky initiative.

• Cloud Computing
• Edge Computing
• Task Scheduling
• +5 more

Dr. Zhijun Wang is an Associate Professor of Research in the Department of Computer Science and Engineering at The University of Texas at Arlington. His work focuses on cloud and edge computing, resource management, task scheduling, and network traffic control. He holds a PhD in Computer Science from UTA (2005), an MS in Electrical Engineering from Penn State (2001), and a BS in Physics from Huazhong University of Science & Technology (1992). His research explores internet traffic control mechanisms , cloud resource allocation , and microservices architecture . Recent projects include NSF-funded work on tail latency guarantees for microservices ($600k grant, 2022-2026) and industry collaborations with Alibaba on datacenter transport protocols ($148k grant, 2018-2021). Publications highlight innovations like CurTail (tail latency scheduling) and Tailguard (data-intensive task scheduling). His work often combines price-aware protocols with distributed scheduling algorithms . Teaching focuses on foundational topics: discrete math, computer networks, and cloud computing. Grants: NSF (2022), Alibaba (2018) Key Patents: Tail Latency Scheduling (2023), Database Target Enforcement (2024) Recent Publications: 15+ papers since 2020 in top-tier venues

Deepak GCView profile

Senior Lecturer

• Cyber Security
• Digital Forensics
• Wireless Communication
• +7 more

Dr. Deepak GC is a Senior Lecturer in Cyber Security and Digital Forensics at Kingston University's School of Computer Science and Mathematics, Department of Networks and Digital Media. He holds a PhD in Wireless Communication Systems from Lancaster University, an MEng in Wireless Networks from Chonbuk National University, and a BEng in Electronics and Communication from Pokhara University. His research focuses on physical layer security , radio access technologies , 5G and beyond networks , spectrum sensing , IoT protocols , drone communications , and blockchain technologies . Recent work includes UAV-assisted networks for disaster resilience, energy-efficient IoT frameworks, and blockchain applications for network security. Dr. GC has participated in EU FP7 S3isE, EU H2020 Wi-5, and UK EPSRC DARE projects. He contributes to academic governance as a representative on Kingston's Faculty Research Degree Committee and University Data Champion. Cisco Certification Fellow of Higher Education Academy He actively supervises PhD students in cybersecurity and wireless technologies and teaches modules including Threat Hunting, Cyber Crime, and Digital Forensics.

• Systems and Networking
• Computer Architecture
• Machine Learning and Artificial Intelligence
• +3 more

Andrew W. Moore is a Professor of Networked Systems at the University of Cambridge's Department of Computer Science and Technology. His research focuses on networked systems design, high-performance prototyping (e.g., NetFPGA), and latency measurement across scales from data centers to wide-area networks. He has contributed to SDN architectures, reconfigurable networking, and energy-efficient interconnects. He teaches courses including Computer Networking (Part IB), Scientific Computing (Part IA), and advanced modules on network measurements and system performance. His work emphasizes open-source tools and reproducible research, with publications in top venues like IEEE Transactions and ACM SIGCOMM. Research interests span Systems and Networking, Computer Architecture, Machine Learning applications in networking, and Security. Recent work addresses data center latency optimization, SDN-enabled IXPs, and FPGA-based network prototyping. Collaborations include projects on energy-aware networks and hardware-software co-design. He leads the NetFPGA initiative, a widely used open-source FPGA platform for networking research and education. His lab also explores emerging storage media and applications of software-defined networking in critical infrastructure.

Yan (Cindy) SunView profile

Lecturer

• Wireless Network Protocols
• Mobile Ad Hoc Networks (MANET)
• Energy Efficiency in IoT
• +3 more

Dr. Yan (Cindy) Sun is a Lecturer in Telecommunications at Queen Mary University of London's School of Electronic Engineering and Computer Science. Her research focuses on routing strategies for ad hoc wireless networks, energy efficiency in IoT systems, and cross-layer design for next-generation wireless networks. She teaches modules on Ad Hoc Networks and Telecommunications Systems, emphasizing protocols like TCP/F, MANET routing (DSDV/ABR/AODV), and wireless broadband access technologies. Research Interests: Optimized routing in heterogeneous wireless environments Energy-saving mechanisms for IoT devices Cross-layer protocol design for 5G/6G networks Her publications (2017-2023) address VANET privacy, game-theoretic intrusion detection, and mMTC network optimization. Active in both theoretical and applied research, she has contributed to eHealth systems integrating wearable sensors with IoT frameworks. Teaching responsibilities include modules taught in collaboration with BUPT (Beijing), covering information theory, queuing theory, coding principles, and wireless network fundamentals.