جست‌وجوی استاد و پژوهشگر

Yasar Gurbuzمشاهده پروفایل

استاد

• Electronics Engineering
• Microelectronic Systems
• RF/Microwave Integrated Circuits
• +۵ مورد دیگر

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 Camardaمشاهده پروفایل

استاد

• Wireless Networks
• Resource Allocation
• Network Protocols
• +۲ مورد دیگر

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 Husseinمشاهده پروفایل

دانشیار

• Edge Computing
• Network Security
• Blockchain
• +۲ مورد دیگر

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
• +۴ مورد دیگر

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
• +۷ مورد دیگر

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. Qutqutمشاهده پروفایل

استاد آموزشی

• Smart city-enabling technologies
• Internet of Things (IoT)
• Cybersecurity
• +۳ مورد دیگر

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 Wuمشاهده پروفایل

دانشیار

• Machine Learning
• Uncertain Reasoning
• Robotics
• +۳ مورد دیگر

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
• +۴ مورد دیگر

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 Kunzمشاهده پروفایل

استاد

• Internet of Things
• Smart Grid/Smart City
• Mobile computing systems
• +۷ مورد دیگر

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 Tahaمشاهده پروفایل

استادیار

• Security of Embedded Systems
• Internet of Things (IoT)
• Implementation Attacks and Countermeasures
• +۳ مورد دیگر

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 Yuمشاهده پروفایل

استاد

• Wireless Networks
• Edge Computing
• Federated Learning
• +۷ مورد دیگر

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 Ryooمشاهده پروفایل

دانشیار

• Wireless Networking
• Mobile Computing
• Internet of Things
• +۷ مورد دیگر

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).

Ouassima Akhrifمشاهده پروفایل

استاد

• Control Systems
• Power Electronics
• Renewable Energies
• +۶ مورد دیگر

Ouassima Akhrif is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS), where she leads research in control systems and power electronics. She holds a Diplôme d'Ingénieur from Rabat, an M.Sc.A., and a Ph.D. from the University of Maryland. Her office is located at A-2575, and she can be contacted via email at ouassima.akhrif@etsmtl.ca. Dr. Akhrif directs the GREPCI Research Group (Power Electronics and Industrial Control), focusing on three primary research axes: Aeronautics and aerospace systems Sensors, networks, and connectivity Sustainable development and environmental solutions Her expertise spans nonlinear control, adaptive systems, UAV flight control, power grid stability, and renewable energy integration. Her recent publications demonstrate strong focus on UAV communication security, power grid optimization, and sustainable industrial systems. Articles frequently incorporate neural networks, model predictive control, and real-time optimization techniques applied to energy systems, aerospace control, and Industry 4.0 challenges. She has supervised over 40 graduate students, including 8 doctoral candidates and numerous Master's researchers. Student projects frequently involve UAV systems, power electronics, gas turbine control, and renewable energy applications. Industrial collaborations include Siemens Energy and aerospace partners for projects on electric propulsion, flight systems, and grid stability. As part of GREPCI, she collaborates on microgrid development, electric vehicle infrastructure, and aerospace control systems. The group maintains laboratories for power electronics prototyping, real-time simulation (Hypersim), and industrial control systems.

• Telecommunications
• Network Optimization
• Artificial Intelligence
• +۳ مورد دیگر

Professor Nancy Alonistioti is a faculty member at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. Her research focuses on advanced telecommunications technologies, including 5G/6G networks, AI-driven optimization, and network management systems. She leads studies in areas such as distributed learning frameworks for QoS prediction, fuzzy logic applications in emergency systems, and energy-efficient federated learning for wireless networks. Her work emphasizes network programmability, self-organizing mechanisms, and autonomic network management. Key contributions include the development of SIM+, a comprehensive information model for beyond 5G networks, and the Distinqt framework for privacy-aware learning in mobile systems. She explores applications in vehicular communications, maritime networks, and Industry 4.0 transformations through 5G capabilities. Professor Alonistioti’s research also addresses challenges like context-aware profiling, dynamic infrastructure-as-a-service paradigms, and genetic algorithm-based resource allocation in edge networks. Her publications span over two decades, reflecting a deep engagement with evolving network architectures and technologies.

Conor Brennanمشاهده پروفایل

دانشیار

• Wave Propagation Modelling
• Computational Electromagnetics
• Rough Surface Scattering
• +۵ مورد دیگر

Affiliations & Roles Dr. Conor Brennan is an Associate Professor in the School of Electronic Engineering at Dublin City University. His roles include academic leadership, research supervision, and teaching in propagation modeling, RF simulation, and computational methods. He is affiliated with the Stokes and FutureTech buildings and collaborates internationally, including with Wuhan University for joint Master's programs. Research Interests His work focuses on wave propagation modeling across rural, urban, and indoor environments, emphasizing computational electromagnetics, rough surface scattering, and metamaterial design. Innovations include full-wave models using integral equations and acceleration techniques like the Fast Far Field Algorithm (FAFFA) and Improved Tabulated Interaction Method (I-TIM). Urban studies involve vehicular channels and millimeter-wave systems, while indoor research explores volume integral equation methods and seamless localization (SEAMLOC). Teaching Brennan teaches advanced modules such as Propagation and Channel Modelling , , and engineering mathematics courses. His pedagogical contributions include developing technology-enhanced assessments (TeRMEd) and the UniDoodle student response system. Grants & Collaborations Research is supported by grants in wireless communication, sensor networks, and metamaterials. Collaborations span academia and industry, with notable projects in vegetation THz propagation, plant monitoring nanosensors, and curriculum design for telecommunication engineering. Labs & Teams He leads a dynamic team including graduates (e.g., Patrick Bradley, Marie Mullen) and current researchers (Vinh Pham, Ian Kavanagh). The group utilizes advanced simulation tools and experimental setups for propagation analysis, localization, and materials testing.