Find Academic Supervisors

• Wireless Communications (5G/6G)
• AI/Machine Learning Applications
• Cyber Security and Privacy
• +9 more

Dr. Diep N. Nguyen is an Associate Professor and Associate Dean (Teaching & Learning) at the University of Technology Sydney (UTS), leading the Agile Communications and Computing Group within the Faculty of Engineering and Information Technology. He holds adjunct positions at universities in the US, Vietnam, and Japan. His research focuses on wireless communications (5G/6G), AI-driven networking, cybersecurity, and edge computing, with over 200 publications and $7M in grants from NSF, ARC, and industry partners. He has supervised 15 PhD students, many now in senior academic and industry roles globally. Key roles include Director of Transnational Education, co-founder of Food Agility CRC, and leadership in international initiatives like APEC DARE. Education: Ph.D. and M.E. in Electrical and Computer Engineering from The University of Arizona and UC San Diego, respectively. Professional service includes editorial roles for IEEE Transactions and conference leadership (e.g., IEEE VTC, INFOCOM). Awards include UTS Research Excellence Awards (2021, 2024), DECRA (2015), and industry recognitions like the 2024 iAward and IoT Impact Award. Research emphasizes AI applications in communications, cybersecurity for Industry 4.0, and 6G security. Notable projects include Australia-Vietnam 5G/6G Centre ($2.1M) and DFAT-funded initiatives for disaster management. Books authored include Deep Reinforcement Learning for Wireless Communications and Generative AI for Communications Systems . Teaching focuses on integrating research into courses like Cloud Security and Industry 4.0 Technologies. His pedagogy emphasizes self-directed learning through authentic research tasks, supported by real-time feedback channels.

Tan WongView profile

Professor

• Wireless Communications
• Physical-Layer Security
• Software-Defined Radios
• +5 more

Tan Wong is a Professor and Graduate Coordinator in the Department of Electrical & Computer Engineering at the University of Florida, part of the Herbert Wertheim College of Engineering. His research focuses on wireless communications, physical-layer security, and software-defined radios, with contributions to MIMO systems, federated learning, and privacy-preserving techniques. He holds a leadership role in graduate education and has published extensively in top-tier conferences/journals. Research interests include secure wireless protocols, adversarial defense mechanisms, and signal processing for next-generation radar systems. Notable work includes jamming-resilient channel estimation and privacy-preserving localization methods. His recent projects explore dynamic spectrum sharing via deep reinforcement learning and efficient federated learning over resource-constrained devices. Publications span 20+ years, emphasizing theoretical foundations (e.g., Cramér-Rao bounds) and practical applications like automotive radar and GPS-denied navigation. Despite no explicitly listed awards, his prolific publication record indicates significant academic contributions. Advising details and grants are not detailed in provided materials, but his role as Graduate Coordinator suggests involvement in student mentoring. No lab/team affiliations are mentioned in the text.

• Cybersecurity
• IoT Security
• Blockchain Technology
• +5 more

Doctor Nan Li is a faculty member at the University of Wollongong, Australia, where they hold a PhD from the same institution. Their research focuses on cybersecurity, IoT security, blockchain technology, and privacy-preserving cryptographic protocols. They have been actively involved in securing distributed systems, authentication mechanisms, and federated learning frameworks. Research interests include cryptographic protocol design, IoT threat mitigation, blockchain forensics, and educational technology innovation in computer science. Recipient of grants such as the Secure Private Cloud grant (2023) and the User-Centric Privacy-Preserving Techniques grant (2023). Current supervision of two PhD projects: leveraging generative AI for IoT security and pragmatic cryptography development. Recent work emphasizes policy-based authentication systems, oblivious location services, and mitigating attacks in federated learning. Their contributions span over 50 peer-reviewed publications, with notable advancements in chameleon hash functions and blockchain rewriting mechanisms. Teaching and supervision activities reflect a commitment to advancing secure technologies and educational methodologies in computer science and cybersecurity domains.

Sheeraz AlviView profile

Research Fellow

• Federated Learning
• Wireless IoT Networks
• Satellite Communications
• +3 more

Dr. Sheeraz Alvi is a Research Fellow at the ANU School of Engineering developing wireless solutions for IoT networks under Associate Professor Nan Yang. His current projects include federated learning for wireless systems and satellite communication modeling for ANU-Optus Bushfire Research Centre. Alvi's research spans adaptive resource allocation, terahertz spectrum management, and privacy-preserving machine learning in distributed networks. Recent publications address UAV-assisted monitoring, wildfire detection systems, and fairness optimization in heterogeneous networks. As co-investigator for bushfire detection projects, Alvi designs ground-based IoT sensor networks for early fire detection. His work bridges theoretical communication models with environmental monitoring applications.

Madhusanka LiyanageView profile

Associate Professor

• Network Security
• 5G
• 6G
• +4 more

Madhusanka Liyanage is an Associate Professor/Ad Astra Fellow and Director of the Network Softwarization and Security Labs (NETSLAB) at University College Dublin's School of Computer Science. He holds adjunct and honorary professorships at the University of Oulu and universities in Sri Lanka. His research focuses on network security, 5G/6G technologies, blockchain, and AI-driven systems. He has authored/co-authored over 250 publications, secured €10M+ in research funding, and led major projects like the EU Horizon Europe initiatives. Notable awards include the 2020 IEEE ComSoc Outstanding Young Researcher Award and recognition as a World's Top 2% Scientist (2020–2024). Education: B.Sc. (First Class Honours) from University of Moratuwa (2009), M.Eng. (Asian Institute of Technology, 2011), M.Sc. (University of Nice Sophia Antipolis, 2011), D.Sc. (University of Oulu, 2016) Research Interests: 5G/6G, Blockchain, AI/ML, Federated Learning, IoT, Network Slicing His work spans security orchestration, quantum-resistant cryptography, and smart grid innovations. He has advised 24+ students, secured grants from EU, IRC, and industry partners, and contributed to standards via ENISA consultancy. Current projects include CONFIDENTIAL6G and ROBUST-6G, addressing privacy and security in next-gen networks.

Shen WangView profile

Assistant Professor

• Artificial Intelligence
• Computer Networking
• Big Data Processing
• +5 more

Dr. Shen Wang is an Assistant Professor (Tenured) at the School of Computer Science, University College Dublin, Ireland. He holds an M.Eng. from Wuhan University and a Ph.D. from Dublin City University. As an academic co-director of Netslab and a member of the UCD Earth Institute, his research focuses on explainable AI, connected autonomous vehicles, and cybersecurity in telecommunications. He has led EU projects like the Horizon 2020 SPATIAL initiative and collaborates with industry partners such as IBM Research Brazil and Boeing. His teaching roles include coordinating modules like Programming for Big Data and Leadership in Security. He advises PhD students on topics like federated learning and autonomous systems. Notable awards include the IRC Postgraduate Scholarship (2021) and recognition for transport resilience research. His work bridges AI, edge computing, and blockchain for future networks and smart mobility.

Sidney GivigiView profile

Professor

• Robotics
• Machine Learning
• UAV Control
• +5 more

Sidney Givigi is a Professor at Queen's University, associated with the School of Computing within the Faculty of Arts and Science. His research focuses on Robotics, Machine Learning, UAV Control, and Multi-Vehicle Systems. He leads projects in autonomous systems, swarm intelligence, and reinforcement learning applications. His work addresses challenges in autonomous vehicle coordination, adversarial attack mitigation in intelligent systems, and real-time decision-making algorithms. Collaborative perception under adverse conditions and dynamic system control are key research themes. Research highlights include the TRATSS task scheduling system for autonomous vehicles, the IPRPAS benchmark dataset for adversarial sample analysis, and innovations in UAV software update protocols. His contributions span theoretical frameworks and practical implementations in robotics and AI. He is affiliated with the Ingenuity Labs Research Institute, advancing translational research in automation and intelligent systems. No academic awards or student advisement information is explicitly documented in the provided texts.

Nima AfrazView profile

Assistant Professor

• Blockchain Technology
• Telecommunications
• Network Economics
• +7 more

Nima Afraz is an Assistant Professor in the School of Computer Science at University College Dublin (UCD), affiliated with the CONNECT Research Centre. He holds a PhD from Trinity College Dublin. His research focuses on blockchain applications in telecommunications, network economics, and optical network virtualization. He is Vice-Chair of the Linux Foundation’s Hyperledger Telecom SIG. Education: BSc and MSc from Islamic Azad University, PhD in Computer Science (Trinity College Dublin, 2020), and Certificates in University Teaching from UCD. Research Interests: Blockchain in telecoms, decentralized systems, federated learning, edge computing, and network resource sharing. Notable projects include blockchain-based marketplaces for 5G networks, conflict management in Open RAN, and distributed ledger applications for telecom infrastructure sharing. Grants: Lead on SFI-funded projects (e.g., RE-ROUTE, Data-driven xApps Conflict Management) and Irish Research Council grants exploring blockchain in telecom. Active in professional roles including Deputy Director of UCD’s Graduate Research School. Teaching: Coordinates modules on Data Structures, Object-Oriented Programming, and Computer System Performance. Supervises PhD students in network economics and distributed systems. Professional Activities: Published in top journals/conferences (IEEE Transactions, ACM, OFC), holds patents on PON virtualization, and contributes to industry standards via Hyperledger. Authored a book chapter on blockchain for 5G networks.

• Artificial Intelligence
• Wireless Communications
• Cognitive Radio Networks
• +4 more

Prof. Juraj Gazda is a Professor at the Faculty of Electrical Engineering and Informatics, Technical University of Kosice. His research focuses on cognitive radio networks, artificial intelligence, green communications, and agent-based modeling. He holds a PhD in engineering from TUKE (2010) and has extensive industry experience as an external consultant at Nokia Networks (2011–2014), advising on LTE wireless systems. He has been a guest researcher at institutions like Ramon Llull University (Spain), Technical University of Hamburg (Germany), and Delft University of Technology (Netherlands). His teaching includes stochastic modeling and data analysis courses. Gazda’s work bridges academia and industry, emphasizing network security, autonomous systems, and 6G technologies. Research highlights include contributions to UAV-assisted networks, blockchain-based spectrum management, and AI-driven edge computing. His projects address real-world challenges in 5G/6G networks, including energy efficiency, secure communication, and autonomous vehicle coordination. Gazda actively collaborates with global tech firms like Verizon Wireless, contributing to network design and optimization. Publications span AI applications in healthcare, vehicular networks, and quantum computing. He advocates for interdisciplinary research, integrating machine learning, blockchain, and metaverse technologies to address future mobility and communication needs.

Sanjiv BhatiaView profile

Professor

• Computer Vision
• Image Processing
• Cyber Security
• +7 more

Sanjiv Bhatia is a Professor of Computer Science at the University of Missouri-St. Louis, specializing in computer vision, image processing, and operating systems. He holds a PhD in Computer Science from the University of Nebraska-Lincoln and has extensive industry consulting experience in defense applications. His educational background includes: PhD in Computer Science, University of Nebraska-Lincoln (1991) MS in Computer Science, University of Arkansas at Fayetteville (1987) BE in Computer Science Engineering, Motilal Nehru National Institute of Technology (1983) Dr. Bhatia's research focuses on developing algorithms for computer vision applications including image indexing, object tracking, and multi-sensor fusion. His work bridges theoretical computer science with practical applications in defense systems and cloud computing. His publications demonstrate consistent focus on algorithm development for image processing and pattern recognition, with recent expansion into environmental modeling applications. Research trends show progression from core computer vision techniques to applied geospatial analysis and optimization methods. Awards include: Chancellor's Award for Excellence in Teaching (2015) He teaches courses in Operating Systems, Digital Image Processing, and Cloud Computing. His instructional approach emphasizes practical implementation and system-level programming skills, with curriculum materials including extensive programming assignments and open-book examinations.

William J. BeksiView profile

Assistant Professor

• Robotics
• Computer Vision
• Machine Learning
• +7 more

William J. Beksi is an Assistant Professor at The University of Texas at Arlington's Department of Computer Science and Engineering, and director of the Robotic Vision Laboratory. His research focuses on robotics, computer vision, and machine learning, with applications in autonomous systems, agricultural robotics, and event-based vision. PhD, MS in Computer Science (University of Minnesota) BS in Mathematics and Computer Science (Stevens Institute of Technology) Dr. Beksi develops algorithms for robot perception and autonomy, emphasizing topological data analysis, control barrier functions, and 3D reconstruction. His work has been sponsored by NSF, USDA, DoD, and industry partners. Recent publications (2023-2025) span event-based vision, agricultural robotics, 3D vision, and safety-critical systems. Key trends include polynomial path planning for deception, edge-informed contrast maximization, and semi-supervised active learning frameworks. ONR Summer Faculty Fellow (2022-2024) NSF CRII Award (2020) IEEE Senior Member UTA CSE Rising Star Research Award (2024) Dr. Beksi advises PhD students in robotics and computer vision, including recipients of UTA Dissertation Fellowships and DoD SMART scholarships. His lab collaborates with institutions like krtkl, AFRL, and NSWCDD on projects ranging from UAV collision avoidance to lunar robotics.

• Robotics
• Aerospace Engineering
• Telecommunications
• +4 more

Abhishek BERA is a Postdoctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the Space Robotics department at the University of Luxembourg. His research focuses on advanced robotics, telecommunications, and aerospace engineering, with particular emphasis on multi-robot coordination, UAV networks, and space exploration systems. He holds a strong record of innovation in resilient communication architectures, blockchain-based infrastructure, and 5G/6G technologies for disaster response and lunar exploration. Key research areas include: Multi-robot systems and planetary exploration 6G-UAV networks and edge computing Blockchain applications for space infrastructure Lunar mapping and resilient exploration systems IoT-enabled UAV networks His recent work explores cutting-edge topics such as ROS2 middleware optimization for planetary robotics, trustful coopetitive infrastructures for space missions, and edge-driven geofencing solutions for beyond-visual-line-of-sight (BVLOS) drone operations. His research bridges theoretical advancements with practical implementations in aerospace and telecommunications sectors.

Alhussein AbouzeidView profile

Professor

• Computer Networks
• Networked Systems
• Internet of Things (IoT)
• +5 more

Alhussein Abouzeid is a Professor in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI). His research focuses on computer networks, networked systems, IoT, smart grid, vehicular networks, and spectrum management. He contributes to the Center for Materials, Devices, and Integrated Systems (CMDIS) and maintains a research group dedicated to advancing dynamic spectrum access, privacy-aware localization, and wireless caching policies. Primary Research Focus: Computer Networks, IoT, Smart Grid, Vehicular Networks Research Center: Center for Materials, Devices, and Integrated Systems (CMDIS) Professor Abouzeid's recent work explores the integration of graph neural networks in spectrum enforcement, privacy-aware deep learning for localization, and spatially correlated content caching in wireless networks. His publications highlight advancements in spectrum partitioning, retransmission protocols, and traffic flow control, with applications in 5G/6G systems and smart grids. Scientific Trends: 2025: Machine learning for spectrum enforcement (Spec-GNN) 2023: Privacy-preserving localization and caching optimization 2021: Stochastic spectrum market models and lease duration optimization 2020: Workload distribution and collaborative caching frameworks

• Porous Media Flow
• Geological Carbon Sequestration
• Subsurface Energy Systems
• +2 more

Dr. Cheng Chen is Associate Professor and Nariman Farvardin Professor in the Department of Civil, Environmental and Ocean Engineering at Stevens Institute of Technology. He directs the Subsurface Energy, Water and Environmental Systems (SEWES) Lab, focusing on porous media transport phenomena through combined computational and experimental approaches. His NSF and DOE-funded research addresses multiphase flow in geological formations for carbon sequestration, shale energy recovery, and nuclear waste disposal. Recent work integrates machine learning for scale-bridging data assimilation and distributional reinforcement learning for autonomous marine systems. Chen's methodological innovations include lattice Boltzmann simulations for pore-scale analysis and Gaussian process models for uncertainty quantification. Scholarly outputs demonstrate consistent focus on energy-geoscience interfaces, with recent expansion into privacy-preserving federated learning applications for IoT systems. His 2023-2024 publications increasingly address security challenges in distributed computing and adversarial machine learning. Major Recognition: Stanford Top 2% Most Cited Scientist (2023) Nariman Farvardin Endowed Professorship Chen teaches numerical methods in environmental engineering and subsurface flow modeling, maintaining industrial partnerships with Schlumberger, SeaRobotics, and Consolidated Edison. He holds editorial roles for SPE Journal and has authored over 60 peer-reviewed publications.

Fatemeh Khoda ParastView profile

Assistant Professor

• Cybersecurity
• Cyber Threat Intelligence
• Digital Forensics
• +3 more

Fatemeh Khoda Parast is an Assistant Professor in the Department of Computer Science at the University of New Brunswick (UNB). She previously served as an Assistant Professor at the University of Guelph from September 2023 to September 2024. Her PhD in Computer Science from UNB (2019–2023) focused on the security of large-scale distributed storage systems. She currently researches transforming cyber threat intelligence into rapid defense mechanisms. Education: PhD in Computer Science, University of New Brunswick (2019–2023) Her research interests span cybersecurity, cyber threat intelligence, digital forensics, and cloud storage security. She explores cryptographic solutions for distributed systems and AI-driven threat detection. Recent work includes CephArmor (secure Ceph storage interfaces) and neural network-based RSA cryptanalysis. Her publications address cutting-edge topics like AI in threat intelligence automation and privacy-preserving machine learning for distributed data. No scientific awards are explicitly mentioned. No advising or grant details are provided. Her work contributes to advancing secure cloud infrastructure and cryptographic protocols.