Find Academic Supervisors

Mohammed Al-KhalidiView profile

Associate Professor

• AI Security
• IoT Security
• Mobile Computing
• +3 more

Mohammed Al-Khalidi is a Senior Lecturer (Associate Professor) in Cyber Security at Manchester Metropolitan University and serves as the MSc Cyber Security Course Leader. He has secured over £500,000 in research funding from UKRI’s Global Challenges Research Fund and other bodies for projects in AI Security and Network Security. His research spans AI security, IoT security, Mobile Computing, Cloud Computing, Ad-Hoc Networks, and Information Centric Networks. He has contributed to EU projects including POINT (iP Over IcN - the betTer IP). He currently supervises PhD students working on Intelligent Mobility Management in 6G, Zero Trust Security for Internet of Drones, UAV Security using AI/Blockchain, and Cybersecurity Frameworks for Intelligent Transport Systems.

Joy EzeView profile

Lecturer

• Machine Learning
• Internet of Things (IoT)
• Telecommunications
• +3 more

Dr. Joy Eze is a Lecturer in Computer Science at the Department of Computing, Goldsmiths, University of London. She holds a PhD in Applied Computing from the University of Bedfordshire (2021). Her research focuses on interdisciplinary applications of machine learning, data science, and health technology, with notable contributions to IoT cybersecurity, smart supply chain management, and vehicular networks. Key publications include work on AI-driven temperature control for perishable foods, 5G/6G-enabled Internet of Vehicles, and vulnerability detection in industrial IoT systems. She has presented at international conferences such as DASA 2024 and ITED 2022.

Alphan SahinView profile

Assistant Professor

• Wireless Communications
• Signal Processing
• Machine Learning
• +4 more

Alphan Sahin serves as Assistant Professor in Electrical Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing since August 2019, specializing in physical-layer wireless communication systems with expertise spanning signal processing, machine learning, and 5G/6G standards development. His academic foundation includes: B.S. Electrical Engineering (2005), Istanbul Technical University B.S. Telecommunications Engineering (double major, 2006), Istanbul Technical University M.S. Electrical Engineering (2008), Istanbul Technical University Ph.D. Electrical Engineering (2013), University of South Florida Research integrates signal processing, communication theory, and AI/ML algorithms to solve physical-layer challenges: Complementary sequence design for low-PAPR OFDM systems Index modulation with chirp signals for integrated radar-communication Distributed learning over wireless networks using FSK and DFT-spread techniques Waveform optimization for IEEE 802.11 and 3GPP 5G NR standards His 12 publications (2020-2022) reveal consistent innovation in physical-layer techniques, particularly complementary sequences and machine learning applications for wireless systems, earning recognition through two major paper awards. Scientific recognition includes: Best Paper Award at IEEE CCNC 2021 Outstanding Paper Award at ICNS 2020 Industry-academia collaboration drives his research, leveraging prior experience at InterDigital for standards development and current university-industry partnerships advancing wireless communication technologies. Dr. Sahin leads research within USC's wireless communications group, focusing on next-generation physical-layer solutions through hands-on development of novel waveforms and machine learning frameworks.

Yasar GurbuzView profile

Professor

• Electronics Engineering
• Microelectronic Systems
• RF/Microwave Integrated Circuits
• +5 more

Prof. Yasar Gurbuz is a Professor of Electrical Engineering at Sabanci University's Faculty of Engineering and Natural Sciences, where he has been a faculty member since 2000. He holds a B.Sc. (1990), M.S. (1993), and Ph.D. (1997) in Electrical Engineering. Prior to Sabanci, he worked as a senior research associate at Vanderbilt University (1997-1999) and at Aselsan Inc. (1999-2000). His research focuses on microelectronic systems, RF/microwave integrated circuits, MEMS, and semiconductor-based sensors/actuators. He is a member of IEEE and SPIE and leads a research group at Sabanci University. His research interests emphasize high-performance analog/mixed-signal ICs, phased array systems for 5G applications, low-noise amplifier design, and infrared photodetectors. Recent work includes advancements in SiGe BiCMOS technology for RF front-ends, plasmon-enhanced infrared sensors, and adaptive phased array architectures. His publications span topics like low-phase-noise oscillators, wideband power amplifiers, and smart pixel readout integrated circuits (DROICs). Prof. Gurbuz’s contributions extend to microbolometer thermal modeling, biomedical sensors for point-of-care diagnostics, and nanorectenna-based energy harvesting. His designs often integrate novel fabrication techniques with advanced signal processing algorithms to address challenges in high-frequency electronics and biomedical sensing.

Pietro CamardaView profile

Professor

• Wireless Networks
• Resource Allocation
• Network Protocols
• +2 more

Pietro Camarda is Full Professor of Telecommunications at Polytechnic University of Bari's Department of Electrical and Information Engineering. With expertise spanning wireless networks and multimedia systems, his research develops protocols for resource allocation, cognitive networks, and streaming services. Recent publications focus on Social IoT architectures (2025), real-time 3D streaming frameworks (2016), and maritime emergency systems (2015). His laboratory advances solutions for 5G/6G networks and adaptive video delivery.

Ahmed Refaey HusseinView profile

Associate Professor

• Edge Computing
• Network Security
• Blockchain
• +2 more

Dr. Ahmed Refaey Hussein is an Associate Professor in the School of Engineering at the University of Guelph, specializing in Computer Engineering. His research focuses on distributed edge computing, network security, and blockchain applications for next-generation communication systems. He teaches advanced courses in computer architecture and VLSI design while leading research on secure software-defined systems, industrial IoT, and autonomous networking solutions. His work targets practical implementations in smart communities and critical infrastructure protection.

• Big Data Analytics
• Machine Learning
• Artificial Intelligence
• +4 more

Mahmoud Daneshmand is an Industry Professor at the School of Business and holds a joint appointment in the Department of Computer Science at Stevens Institute of Technology. He has over 40 years of experience in academia and industry, serving as a Distinguished Member of Technical Staff at Bell Labs and AT&T Shannon Labs. His research focuses on Big Data Analytics, Machine Learning, IoT, and Data Mining, with over 300 publications and three books to his name. He co-founded the Business Intelligence & Analytics MS program at Stevens and leads initiatives in IEEE, including steering committees for IoT and Big Data journals. Education: PhD (1976) in Statistics from UC Berkeley; MA (1973) in Statistics from UC Berkeley. Research Interests: Big Data, AI, IoT, Data Mining, Risk Management, and Network Reliability. Dr. Daneshmand has received numerous awards, including IEEE Distinguished Lecturer, AT&T Recognition Awards, and IEEE Standards Committee honors. He chairs international conferences, edits journal special issues, and advises on industry standards. His work spans academia-industry collaboration, innovation in data-driven technologies, and leadership in IEEE initiatives. Grants & Patents: Holds two patents (2009-2010) and led over 60 large-scale Bell Labs projects. PI of the American Bureau of Shipping Grant. Service: Editorial roles in IEEE journals, NJBDA board member, and academic coordinator for Stevens' programs.

• Optical Wireless Communication
• B5G/6G Networks
• Aerospace Communications
• +7 more

Dr. Vuong Mai is an Assistant Professor at the School of Computer Science, AI and Electronics , Faculty of Engineering and Digital Technologies , University of Bradford, UK. He is a core member of the Bradford-Renduchintala Centre for Space AI. Previously, he worked as a Research Assistant Professor at KAIST, South Korea. His research focuses on optical wireless, B5G/6G, aerospace communications, and space AI. He teaches modules in MSc Satellite Systems Engineering and MSc Advanced Biomedical Engineering. Research Interests : Optical Wireless Communication (e.g., free-space optics, lasercom) Future Space Networks (e.g., satellite constellations, space quantum internet, interplanetary links) AI/ML-driven solutions for space networks Advertised PhD Projects : AI-Enabled Free-Space Optics for Satellite Communications Earth Observation with AI Quantum Space-Aerial-Terrestrial Networks Advising & Students : Currently supervising PhD students Aftab Hussain and Nighat Sultana, as well as MSc students Thong Tran, Anthony Emuze, and Sethma Bandara. He has advised over 30 students globally. Labs/Teams : Founder and Lead of the OSpace research group, focusing on optical wireless and space networks.

Mahmoud H. QutqutView profile

Teaching Professor

• Smart city-enabling technologies
• Internet of Things (IoT)
• Cybersecurity
• +3 more

Dr. Mahmoud H. Qutqut is an Assistant Teaching Professor in the Faculty of Computer Science at the University of New Brunswick (UNB) in Fredericton, Canada since September 2023. Previously, he served as Chair of the Cybersecurity and Cloud Computing Department at Applied Science University in Jordan (July 2022–August 2023) and was promoted to Associate Professor there in December 2019. He has held academic positions since 2014, including a visiting role at Queen’s University (2017–2019) where he contributed to research and teaching. His educational background includes a Ph.D. (2014) and M.Sc. (2008) in Telecommunication Systems, and a B.Sc. (2004) in Computer Systems. Research interests focus on smart city technologies, IoT, cybersecurity, and data-driven networks. He actively publishes in top-tier venues such as IEEE Access and has served on technical committees for conferences and journals. Notable achievements include a Teaching Excellence Award nomination (2018) and founding the Cisco Academy at Applied Science University (2015). Dr. Qutqut’s academic career spans teaching roles at Queen’s University, where he instructed courses on computer networks and computing fundamentals. His research bridges theoretical advancements with practical applications in network security, machine learning, and IoT systems. He has supervised impactful student projects, such as winning entries in graduation competitions (2017).

Dan WuView profile

Associate Professor

• Machine Learning
• Uncertain Reasoning
• Robotics
• +3 more

Dr. Dan Wu is an Associate Professor at the School of Computer Science, University of Windsor. His research focuses on uncertain reasoning, machine learning, knowledge representation, and robotics. He holds a PhD from the University of Regina (2003). His work bridges theoretical advancements and practical applications in robotics, traffic systems, and probabilistic inference. Education: PhD in Computer Science, University of Regina, 2003 Research Interests: Machine Learning: Focused on deep learning models for traffic prediction and robotics. Uncertain Reasoning: Developing probabilistic methods for cooperative robotic systems. Robotics: Multi-robot coordination, navigation, and obstacle avoidance. Knowledge Representation: Applications in distributed Bayesian networks and graph-based systems. Publications Trends: Recent work emphasizes urban traffic management (reinforcement learning for signal control), vehicular networks (task offloading in 5G), and privacy-preserving federated learning. Earlier studies addressed multi-robot coverage algorithms and probabilistic localization techniques. Lab/Teams: Active in AI-driven robotics and intelligent transportation systems research, though specific lab names are not explicitly mentioned in the provided texts.

• Fluid Antenna Systems
• Reconfigurable Intelligent Surfaces
• Integrated Radio-Sensing
• +4 more

Dr. Tuan Anh Le is a Senior Lecturer in Design Engineering at Middlesex University's Faculty of Science and Technology, Department of Design Engineering & Mathematics. He holds a B.Eng. and M.Sc. in Electronics and Telecommunications from Hanoi University of Technology, and a Ph.D. from King's College London funded by the UK's EPSRC and Mobile VCE scholarship. His research focuses on developing resource allocation strategies for next-generation wireless networks using convex optimization and nature-inspired intelligence. Key areas include reconfigurable antenna systems, integrated sensing-communications, PHY-layer security, and energy-efficient 5G/6G architectures. Recent publications demonstrate strong focus on beamforming optimization techniques using metaheuristic algorithms (especially Firefly Algorithm), cognitive radio systems, and dual-function radar-communications. Work frequently appears in IEEE Transactions journals and major telecom conferences. Supervises PhD candidates in antenna design and wireless systems. Teaches modules including Digital Signal Processing, System Design, and Mobile Communications. Previously contributed to EU-funded projects on green radio technologies.

Thomas KunzView profile

Professor

• Internet of Things
• Smart Grid/Smart City
• Mobile computing systems
• +7 more

Roles & Affiliations: Professor in the Department of Systems and Computer Engineering at Carleton University, Ottawa. Holds a Dr.-Ing. from the Technical University of Darmstadt (Germany). Active in research and academic leadership, including serving on Carleton's Board of Governors (2012-15). Education: Dr.-Ing., Technical University of Darmstadt, Germany (1994) Postdoctoral experience: University of Waterloo (1994-1997) Research Focus: Internet of Things (Smart Grid/City) Mobile computing systems & wireless networks Software-defined networking (SDN) and network function virtualization (NFV) Machine learning applications in networking Adaptive mobile systems and tactical radio networks Key Achievements: World's Top 2% Most-Cited Scientists (2022, Stanford-Elsevier) Top 0.5% Global Scholars (2024, ScholarGPS) Carleton Research Achievement Awards (2012-13, 2004-05) Carleton Graduate Mentoring Award (2010) Advising & Labs: Supervised numerous graduate students (see linked list) Developed NetAnalyzer , an open-source network analysis tool

Mostafa TahaView profile

Assistant Professor

• Security of Embedded Systems
• Internet of Things (IoT)
• Implementation Attacks and Countermeasures
• +3 more

Mostafa Taha is an Assistant Professor at Carleton University's Systems and Computer Engineering Department within the Faculty of Engineering and Design. He holds a PhD from Virginia Tech (2014) and has held postdoctoral roles at Worcester Polytechnic Institute and Western University. His research focuses on securing embedded systems and IoT against implementation attacks, including side-channel analysis, leakage-resilient designs, and cryptographic algorithm hardening. He has contributed to projects like LR-Keymill, a keystream generator with inherent SCA resistance, and has served on program committees for conferences such as DATE and SPACE. Education includes a PhD in Computer Engineering (Virginia Tech), M.Sc. in Electrical Engineering (Assiut University), and B.Sc. in Electrical Engineering (Assiut University). His work spans hardware security, cryptographic implementations, and vehicular networks. Awards include Egyptian Government and Assiut University scholarships for his PhD and M.Sc., respectively. Research interests emphasize quantifying side-channel resistance, leakage-resilient architectures, and lightweight cryptographic implementations. Notable publications include work on AES S-box optimization, threshold implementations for SIMON, and quantifying masking strength in software. He teaches courses on cryptographic implementations, computer systems design, and digital systems at Carleton. Publications reflect a focus on hardware-oriented security, with contributions to conferences like CHES, FDTC, and HOST. His work on LR-Keymill demonstrates a novel approach to SCA resistance without explicit countermeasures, achieving 67.9-bit post-attack complexity. Awards and industrial connections highlight his impact in embedded system security.

Richard YuView profile

Professor

• Wireless Networks
• Edge Computing
• Federated Learning
• +7 more

Richard Yu is a Professor at the Carleton School of Information Technology, Carleton University. His research focuses on cross-layer design in wireless systems, security in wireless networks, green information technologies, and multimedia over wireless networks. He holds a Ph.D. from the University of British Columbia and is a Professional Engineer (P.Eng). His work integrates machine learning, edge computing, and reinforcement learning to address challenges in vehicular networks, autonomous systems, and IoT. Education Ph.D., University of British Columbia Research Interests Professor Yu’s research spans wireless communication systems , edge computing , and AI-driven optimization . He explores novel paradigms such as federated learning for industrial IoT, secure UAV-assisted satellite networks, and generative AI for video understanding. His work emphasizes practical applications in autonomous vehicles, smart infrastructure, and industry 4.0 systems. Recent Trends in Publications His recent articles highlight advancements in reinforcement learning frameworks for resource allocation, safety-critical AI in video generation, and cross-modal fusion for embodied agents. He also investigates hybrid NOMA/OMA systems and quantum-inspired algorithms for next-generation networks. Advising & Grants No specific advisees are listed, but his research is supported by grants focusing on edge intelligence, vehicular networks, and secure computing. Labs & Teams Associated with Carleton’s School of Information Technology research groups, focusing on wireless systems and AI for industrial applications.

Jihoon RyooView profile

Associate Professor

• Wireless Networking
• Mobile Computing
• Internet of Things
• +7 more

Jihoon Ryoo is an Associate Professor in the Department of Computer Science at SUNY Korea, where he has been employed since 2017. He directs the AI2S Lab and co-founded the startup IDCITI. He holds a Ph.D. from Stony Brook University (2017) and M.S./B.S. degrees from Korea University. Research Interests: Dr. Ryoo's work focuses on practical implementations in wireless networking and mobile systems, including backscatter communication, IoT connectivity, saliency-based video streaming, and GNSS-independent localization. His projects span uGPS (metro localization), SALI360 (360° video optimization), and autonomous anti-drone systems, often leveraging deep learning and RF analytics. Awards & Grants: Incheon City Mayor Award (Entrepreneur, 2024 & S/W Hackathon, 2020) Prime Minister Awards (ICT Colloquium & Applied Data Competition, 2020) IITP Excellence Research Award (2019) Grants: National XR-Lab initiatives (MSIT), Incheon-RISE program (2025–2030), NRF streaming platform research, and multiple Incheon Techno Park projects. Teaching & Service: Courses include Computer Networks, Computer Vision, Algorithms, and Wireless Networks. Service includes TPC roles (MobiSys, ICCCN), Director of SUNY Korea's ICT CCP Program (2018–2020), and XR-Lab Director (2021–2023).