جست‌وجوی استاد و پژوهشگر

Rosario Culmoneمشاهده پروفایل

استادیار

• Internet of Things
• Blockchain Technology
• Sensor Networks
• +۷ مورد دیگر

Rosario Culmone is an Assistant Professor at the University of Camerino, with a strong research focus in Internet of Things (IoT), sensor networks, and related technologies. His academic work spans multiple domains including smart city applications, blockchain implementations, and educational technology. Dr. Culmone's research interests center around IoT interoperability , sensor network optimization , and formal verification methods for intelligent environments. His work demonstrates a consistent focus on practical applications of distributed systems, with significant contributions to energy-efficient routing algorithms, blockchain-based certification systems, and ontology-driven frameworks for ambient assisted living. An analysis of his publication record reveals a clear trajectory from foundational work in wireless sensor networks and ECA rules verification toward more applied research in smart city technologies, food traceability using blockchain, and AI-enhanced educational systems. His most recent publications (2023-2025) show increased focus on practical implementations addressing real-world problems in security, education, and supply chain management. Dr. Culmone has developed several notable frameworks including the Share Pattern for IoT interoperability, NARUN for noise-adaptive routing, and IRON , a domain-specific language for programming IoT devices. His research bridges theoretical computer science with practical implementations across multiple application domains.

Kashif Naseer Qureshiمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Healthcare Systems
• +۶ مورد دیگر

Kashif Naseer Qureshi is an Associate Professor in the Department of Electronic and Computer Engineering at the Faculty of Science and Engineering, University of Limerick, Ireland. His research focuses on the intersection of artificial intelligence, healthcare systems, blockchain technology, and wireless communication networks. His recent work explores: AI-driven healthcare architectures (tri-tier models, distributed networks) Blockchain applications in medical and smart city systems Advanced machine learning techniques for data imbalance problems Edge computing security and privacy frameworks Next-generation AI language models with ethical considerations Publications demonstrate a strong emphasis on practical implementations across IoT, cybersecurity, and smart infrastructure domains. His email contact is KashifNaseer.Qureshi@ul.ie .

• Wireless Networks/Communications
• IoT
• Cyber Security
• +۱۳ مورد دیگر

Professor Qiang Ni is an esteemed academic at Lancaster University , affiliated with the School of Computing and Communications , Data Science Institute , and Security Lancaster Center . Currently serving as Head of Communication Systems Research Group , School Director of International Partnership , and Theme Lead in Security and Defence at the Lancaster Intelligent, Robotic and Autonomous Systems (LIRA) Research Centre , he has previously held roles as School Director of Postgraduate Studies and Deputy Director of Research . Research focus areas include Wireless Networks/Communications , IoT , Cyber Security , AI , Digital Twins , and Quantum Communication Key projects involve INTACT (secure IoT-to-Cloud), CoGNETs (swarm intelligence), SustainAIRA6G (AI-driven resource allocation), and TRACE-V2X (multi-RAT traffic steering) Recent publications address 6G communication design , quantum neural networks , blockchain-based border control systems , and intelligent vehicular networks As an IEEE Senior Member and IEEE Communications Society Distinguished Lecturer , he chairs editorial boards for IEEE Transactions on Green Communications and JSAC Machine Learning Series . His supervision spans Wireless Communication , Big Data Analytics , and Quantum Machine Learning PhD research topics. Active in H2020 , Horizon Europe , and UKRI funded projects, he also contributes to IEEE standard committees.

• Efficient sampling methods
• Compressed sensing
• Medical imaging: ultrasound, MRI, CT
• +۱۲ مورد دیگر

Prof. Yonina Eldar is a Professor of Electrical Engineering at the Faculty of Mathematics and Computer Science , Weizmann Institute of Science. She holds the Dorothy and Patrick Gorman Professorial Chair and serves as Head of the Manya Igel Center for Biomedical Engineering and Signal Processing . Her research bridges classical signal processing with modern deep learning techniques. Develops model-based deep learning frameworks combining domain knowledge with data-driven approaches Focuses on sub-Nyquist sampling for efficient data acquisition in radar, ultrasound, and communications Created hardware prototypes for time-encoding machines and modulo-ADC systems Innovates in joint radar-communication systems for autonomous vehicles Her work emphasizes algorithm unrolling to create interpretable neural networks with reduced training requirements. Publications demonstrate applications in: Medical imaging (ultrasound, ECG monitoring) Autonomous systems (automotive radar) Communication technologies (DFRC systems) Active in theoretical foundations of model-based deep learning, with recent work establishing mathematical guarantees for unfolded networks. Collaborations include Tsinghua University and industry partners for hardware validation.

Naima Kaabouchمشاهده پروفایل

استاد

• Artificial Intelligence
• Wireless Communications & Networking
• Cybersecurity
• +۲ مورد دیگر

Dr. Naima Kaabouch, a Professor at the University of North Dakota’s College of Engineering & Mines, is the Director of the Artificial Intelligence Research (AIR) Center. Her work spans artificial intelligence, wireless communication, cybersecurity, sensing, and autonomous systems. School: College of Engineering & Mines Department: School of Electrical Engineering & Computer Science Research Interests: Dr. Kaabouch’s research focuses on advancing AI, wireless networks, and secure communication protocols. She leads projects in autonomous systems and dynamic spectrum management, supported by grants from NSF, NASA, FAA, and ND Chamber of Commerce. Scientific Awards: Chester Fritz Distinguished Professor Award (2024) UND Outstanding Faculty Scholar (2016) NASA Joe Kosmo Excellence Award (2011) IEEE Contest Awards (2006–2012) NASA Robotics Competition accolades (2011–2016) Advising and Grants: She has mentored numerous students in projects resulting in national awards. As PI/CoPI/CoI, she has secured funding from NSF, NASA, FAA, and state agencies for research in AI, cybersecurity, and autonomous systems.

Mohammad Imran Chowdhuryمشاهده پروفایل

استادیار

• Algorithms
• Machine Learning
• Robotics
• +۳ مورد دیگر

Mohammad Imran Chowdhury is an Assistant Professor of Instruction in the Department of Computer Science at the University of Texas at San Antonio (UTSA), affiliated with the College of Sciences. His teaching focuses on Algorithms, Machine Learning, and Robotics. He holds a Ph.D. and M.S. in Computer Science from Florida State University, alongside a B.Sc. in Computer Science and Engineering from Chittagong University of Engineering and Technology. His research interests revolve around path planning algorithms for autonomous systems, robotics navigation, and optimization in networks. Notable work includes contributions to probabilistic roadmaps (PRM) for robot path planning, obstacle avoidance strategies for unmanned vehicles, and energy-efficient protocols for mobile ad hoc networks (MANET). Recent studies emphasize real-time path replanning for underwater and surface vehicles in dynamic environments. Chowdhury’s publications reflect a strong focus on interdisciplinary applications of computer science, spanning robotics, autonomous systems, and algorithm design. His work bridges theoretical foundations with practical implementations in military, marine, and vehicular contexts. While no specific awards are listed, his academic trajectory highlights sustained engagement in cutting-edge computational research and pedagogy.

Tim Taltyمشاهده پروفایل

استاد

• Wireless Communications
• Communication Systems
• Signal Processing
• +۴ مورد دیگر

Tim Talty is a Collegiate Professor and Director of Admissions for the Master of Engineering Program at Virginia Tech's Bradley Department of Electrical and Computer Engineering. He holds a Ph.D. from the University of Toledo (1996) and a B.S. from Trine University (1987). His research focuses on wireless communications, signal processing, and intra-vehicle sensor networks, with particular emphasis on physical layer security and mobile communications. Key research areas include lidar systems, vehicular antennas, and software-defined radio architectures. He has contributed to innovations in automotive communication networks, including UWB localization and transparent antenna fabrication. His work bridges theoretical advancements with practical applications in autonomous vehicles and telematics. Notable awards include the General Motors ‘Boss Kettering’ Award for Innovation (2019) and the Commander's Award for Civilian Service from the U.S. Army. He has served as an ABET program evaluator and actively participates in industry collaborations, including leadership roles in IEEE conferences and automotive R&D initiatives. Recent publications emphasize energy-efficient computing for ADAS, lidar miniaturization, and 5G vehicle connectivity. His research trends highlight interdisciplinary approaches to solving challenges in vehicular communication, sensor fusion, and autonomous systems.

Amna Mazenمشاهده پروفایل

استادیار

• Robotics
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Dr. Amna Mazen is an Assistant Professor with a joint appointment between the Department of Applied Computing and the Department of Manufacturing and Mechanical Engineering Technology at Michigan Technological University. She holds a Ph.D. in Robotics from the University of Detroit Mercy (2024), an MSc in Automatic Control from Fayoum University (2018), and a BSc in Electrical Engineering from Fayoum University (2013). Education: Ph.D., Robotics, University of Detroit Mercy, USA, 2024 MSc., Automatic Control, Fayoum University, Egypt, 2018 BSc., Electrical Engineering, Fayoum University, Egypt, 2013 Her research focuses on Autonomous Robots/Vehicles , Machine Learning , and Robotics , with expertise in ROS, deep learning, computer vision, and control system design. She has contributed to interdisciplinary projects spanning healthcare robotics, energy management via drone imagery, and industrial automation. Dr. Mazen’s publications highlight trends in robot navigation , 3D printing optimization , and deep learning applications in robotics and energy systems. Her work includes trajectory planning using Bézier contours, warehouse automation, and occupancy detection via WI-FI data. Scientific Awards: No awards listed in the provided text. Dr. Mazen has over a decade of teaching experience, previously instructing at the University of Detroit Mercy and Fayoum University. Her teaching interests include Robotics and Mechatronics , Manipulator Robotics , and Control System Design .

Bassam Shaerمشاهده پروفایل

استاد

• Embedded System Design
• VLSI Design and Test
• Digital Signal Processing
• +۵ مورد دیگر

Dr. Bassam Shaer is a Professor in the Department of Electrical and Computer Engineering at the University of West Florida (UWF), affiliated with the Hal Marcus College of Science and Engineering. He has over 20 years of experience in academia, with a focus on embedded systems, VLSI design, and distance learning methodologies. Shaer earned his Ph.D. and M.S. in Electrical Engineering from the University of South Florida and a B.S. from the University of Florida. Educational Background: Ph.D. in Electrical Engineering, University of South Florida (Tampa, FL) M.S. in Electrical Engineering, University of South Florida (Tampa, FL) B.S. in Electrical Engineering, University of Florida (Gainesville, FL) Research Interests: Dr. Shaer's work spans embedded system design , VLSI testing and partitioning , analog/digital electronics , and distance-learning laboratory development . His innovations include energy conservation systems, robotic ball collection mechanisms, and intelligent tracking telescopes. He emphasizes practical applications of microcontrollers and FPGA-based solutions. Teaching: Shaer teaches courses such as Electronic Circuits , VLSI , Digital Computer Architecture , and Microprocessor Applications , integrating hands-on lab experiences. He has developed interactive distance-learning systems to enhance accessibility in engineering education. Professional Contributions: He has reviewed over 10 academic journals and contributed to projects like solar array positioning systems and LabVIEW-based plotter controls. His research often bridges theoretical engineering principles with real-world applications in robotics, renewable energy, and automated systems. Labs/Teams: He collaborates with initiatives like the Science Olympiad and Science Showcase , promoting interdisciplinary engineering education and innovation.

• IoT Security
• Wireless Communication Protocols
• Vehicular Networks
• +۳ مورد دیگر

Dr. Rafik Zitouni is a Research Fellow and Lead Software Engineer at the University of Surrey's School of Computer Science and Electronic Engineering, affiliated with the Institute for Communication Systems. His work focuses on wireless communication protocols, IoT security, vehicular networks, and adaptive networking solutions. He has contributed to advancements in 6TiSCH, LoRaWAN, and MQTT protocols, with an emphasis on security mechanisms, network optimization, and machine learning applications. Research interests include securing industrial IoT networks, vehicular emergency messaging systems, and low-power wide-area networks (LPWAN). He has pioneered techniques such as fuzzy logic-based detection of selfish nodes in 6TiSCH and Fuzzy C-Means clustering for LoRa parameter optimization. His work on FPGA-based sensor fusion for autonomous vehicles addresses real-time data processing challenges. Key contributions span 20+ peer-reviewed publications in journals like Wireless Networks and Computer Communications , and conferences including IWCMC and MENACOMM. He actively collaborates with industry and academia on open radio access networks (O-RAN) and underwater localization systems. Current research emphasizes machine learning-driven network automation and resilient IoT infrastructure.

Seyed Ahmad Soleymaniمشاهده پروفایل

پژوهشگر ارشد

• Cybersecurity
• Edge Computing
• Internet of Things (IoT)
• +۳ مورد دیگر

Dr. Seyed Ahmad Soleymani is a Research Fellow at the University of Surrey's Institute for Communication Systems and part of the 5G/6G Innovation Centre. His research focuses on cybersecurity, edge computing, IoT, UAV systems, and 5G/6G networks. He has contributed to secure authentication protocols for medical and industrial IoT systems, UAV-assisted edge computing optimization, and multi-target tracking algorithms using Q-learning. His work emphasizes energy efficiency, data security, and real-time applications in smart manufacturing and vehicular networks. Research interests include secure communication in UAV networks, sustainable edge node deployment, and privacy-preserving authentication schemes. He has explored applications such as flood forecasting via UAV-assisted sensors and energy-efficient building systems. His publications span IEEE journals and conferences, addressing challenges in edge computing resource allocation, intrusion detection systems, and trust management in 5G-IIoT environments. Collaborations involve institutions like the University of Electronic Science and Technology of China and Universiti Teknologi Malaysia. Notable contributions include the MI3SE encryption scheme for outdoor IIoT devices and the TRUTH trust scheme for 5G industrial IoT. His work combines machine learning (e.g., SAC, Q-learning) with network optimization to address latency, security, and scalability in modern communication systems. He has also developed frameworks for cybertwin-based 6G networking and secured target tracking in O-RAN environments.

Mohammad Hasanمشاهده پروفایل

مدرس ارشد

• Computer Networks
• Cyber Security
• Cloud Computing
• +۵ مورد دیگر

Dr. Mohammad Hasan is a Senior Lecturer in Digital, Tech, Innovation & Business at Staffordshire University with extensive expertise in cybersecurity, cloud computing, and network engineering. His educational background includes a PhD in Mobile Ad-hoc Networks, MSc in Computer and Network Engineering, and BSc in Computer Science. His primary research focuses on: Computer networks including wireless systems and IoT Cybersecurity frameworks and threat analysis Cloud computing infrastructure and virtualization Machine learning applications in data analytics Recent publications demonstrate strong trends in machine learning applications for pattern recognition (eSports analytics), network security (XSS prevention), and biomedical signal processing (brain source localization). Dr. Hasan maintains professional certifications including CCSK, CompTIA Security+, and Cisco CyberOps Associate, and holds Senior Fellow status with the Higher Education Academy.

Pramod K. Varshneyمشاهده پروفایل

استاد

• Distributed sensor networks
• Data fusion
• Statistical inference
• +۴ مورد دیگر

Pramod K. Varshney is a Distinguished Professor at Syracuse University's Department of Electrical Engineering and Computer Science, within the College of Engineering & Computer Science. He also holds adjunct professorships at Upstate Medical University (Radiology) and Xidian University (China). His research focuses on distributed sensor networks, data fusion, machine learning, and signal processing, with applications spanning defense, healthcare, and IoT. Varshney has led over four decades of research funded by major agencies like DoD, NSF, and industry partners. Education: PhD (Electrical Engineering, University of Illinois, 1976), MS (1974), BS (1972). His research interests emphasize foundational aspects of data/information fusion, sensor networks, and AI-driven analytics. Notable contributions include pioneering work in distributed detection theory and secure inference in adversarial environments. Recent publications highlight advancements in federated learning, anomaly detection, and multi-target tracking. Varshney has been honored with prestigious awards such as the IEEE Fellow (1997), Yaakov Bar-Shalom Award (2018), and Syracuse University's Chancellor’s Lifetime Achievement Award (2023). He has advised numerous PhD and Master’s students, contributing to over 350 publications, including seminal books like Distributed Detection and Data Fusion (Springer, 1997). He has directed Syracuse's CASE (Center for Advanced Systems and Engineering) and actively collaborates with global institutions. His work bridges theoretical advancements with real-world applications in healthcare imaging, cybersecurity, and autonomous systems.

Harry F. Hemondمشاهده پروفایل

استاد

• Biogeochemistry
• Environmental Chemistry
• Wetland Geochemistry
• +۵ مورد دیگر

Professor Harry F. Hemond is a distinguished faculty member at the Massachusetts Institute of Technology (MIT) in the Civil and Environmental Engineering department. With a career spanning decades, his research focuses on the biogeochemical cycling of chemicals in aquatic and wetland systems, environmental instrumentation development, and sustainable energy solutions . He has received multiple awards, including the MIT Bose Award for Excellence in Teaching (2007) and the CEE Maseeh Graduate Teaching Award (2010), highlighting his dual expertise in research and education. B.S., Worcester Polytechnic Institute M.A., Connecticut College Ph.D. 1977, MIT His research interests include: Biogeochemistry of inland and coastal waters, emphasizing trace metals and methane dynamics Development of in-situ chemical instrumentation like the NEREUS mass spectrometer and optical sensors Renewable energy applications, particularly solar organic Rankine cycle engines Recent publications emphasize methane venting mechanisms , trace metal deposition , and low-cost sensor systems for environmental monitoring. His lab has pioneered techniques for real-time water chemistry analysis and studies of metal cycling in contaminated sediments. Awards and honors include: MIT Irwin Sizer Award (1991) CEE Departmental Service Award (2003) CEE Departmental Appreciation Award (2005) MIT Bose Award (2007) CEE Maseeh Teaching Award (2010) Students under his mentorship include PhD candidates studying methane cycling , water quality sensors , and trace metal geochemistry . The Hemond Lab develops in-situ observational systems to study Earth's biochemical cycles in challenging environments.

• Cybersecurity
• Machine Learning
• Internet-of-Things (IoT)
• +۵ مورد دیگر

Sejun Song, Ph.D., is a Professor at the School of Computer & Cyber Sciences (SCCS) at Augusta University, Georgia. He has held prior roles including Assistant Professor at Texas A&M University and founding director of the Cisco Test Engineering Center (Cisco-TEC). His research focuses on Cybersecurity, Machine Learning, IoT, and Mobile/Wireless Communications for applications in smart cities, eHealth, transportation, and agriculture. Song holds a Ph.D. in Computer Science and Engineering from the University of Minnesota (2001) and has industry experience at Cisco Systems and Honeywell Research Lab. His work spans funded projects by NSF, DoD, NASA, NIH, and others. Notable contributions include AI-driven cybersecurity solutions, crowd dynamics modeling, and edge computing frameworks for surveillance. Awards include the NASA Summer Fellowship and multiple best paper/video awards at conferences like CCNC and Mobisys. His interdisciplinary projects include smart infrastructure development and technology education for underserved populations. Research Highlights: Deepfake detection using corneal reflections (READFake, MobiDeep) Resilient network systems for IoT and space communications Energy-efficient semantic communication protocols Funding Agencies: NSF, DoD, ONR, AFOSR, NASA, NIH, CDC Awards reflect multiple domains: teaching excellence (Center for Teaching Excellence Scholar), research innovation (Air Force Visiting Fellowship), and applied results (best video/paper awards). Key labs/teams involve Cisco-TEC and collaborations on edge computing, federated networking, and smart city infrastructure. Current research emphasizes trustworthy AI systems, green communication, and pandemic-era crowd safety analytics.