جست‌وجوی استاد و پژوهشگر

• Electromagnetic Fields
• Wireless Communication Systems
• Quantum Computing Applications
• +۳ مورد دیگر

Prof. Franco Moglie is an Associate Professor at the Department of Information Engineering of the University of Marche Polytechnic (UNIVPM). His research focuses on electromagnetic field theory, wireless communication systems, quantum computing applications, and bioelectromagnetics. He leads projects on reverberation chamber analysis, reconfigurable intelligent surfaces, and FDTD simulations. His work spans topics like 5G signal propagation, quantum optimization for wireless networks, and electromagnetic shielding materials. He actively contributes to IEEE standards for stochastic radiator characterization and has pioneered chaotic chamber designs for enhanced testing environments. Research interests include advanced FDTD simulations for complex cavities, time-reversal techniques for biomedical applications, and the development of composite materials for electromagnetic shielding. He collaborates with industry and academia on projects involving 5G infrastructure testing, quantum computing for electromagnetic problems, and bioelectromagnetic safety assessments. Recent publications highlight innovations in quantum algorithms for waveguide simulations, experimental validations of 5G systems in reverberation chambers, and statistical analysis of shielding effectiveness. His work bridges theoretical electromagnetics with practical applications in telecommunications and medical engineering.

Wojciech Kmiecikمشاهده پروفایل

پژوهشگر

• Optical Networks
• Elastic Optical Networks
• Survivable Overlay Multicasting
• +۱۲ مورد دیگر

Dr. Eng. Wojciech Kmiecik is a researcher at the Department of Computer Systems and Networks, Faculty of Electronics, Photonics and Microsystems, Wrocław University of Science and Technology. He is actively involved in multiple research teams including Machine Learning, Computer Networks, Advanced Data Analysis Methods, and Metaheuristics. He also contributes to teaching and supervises diploma theses. His research focuses on optical networks , survivable multicasting , multi-criteria optimization , and metaheuristic algorithms . He has led and contributed to projects such as Dark-Box Optimization, evolutionary multi-criteria optimization, and advanced methods for multi-layer networks. His work bridges theoretical algorithm development with practical network design. The publication trends from 2010 to 2020 show a consistent focus on network survivability , elastic optical networks , and task allocation in parallel systems . His research integrates optimization techniques into networking solutions, particularly in dual homing architectures and deadline-sensitive provisioning. Key themes include resilience, efficiency, and scalability in both optical and computational systems. Scientific Awards: Medal for long-standing service to Wrocław University of Science and Technology Dr. Kmiecik has supervised diploma theses and is involved in teaching. He has not received externally reported grants, but his sustained project involvement suggests institutional or collaborative funding. He collaborates extensively with Prof. Krzysztof Walkowiak and other researchers in the department. Research Labs and Teams: Machine Learning Team Teaching Team Computer Networks Team Advanced Data Analysis Methods Team Metaheuristics Team

• Signal Processing
• Telecommunications
• Quantization
• +۱۲ مورد دیگر

Jelena Nikolic is an Associate Professor in the Department of Telecommunications at the Faculty of Electronics, University of Niš, Serbia. She has been a core faculty member since earning her PhD in 2011 and was promoted to Assistant Professor in 2014 and Associate Professor in 2020. Her academic work is deeply rooted in signal processing, quantization theory, and data compression, with expanding interests in machine learning applications for communications. Research Interests: Her primary research areas include quantization , data and signal compression , approximations of the Q-function , and neural network weight compression . She applies these to telecommunications, digital signal processing, and emerging AI-driven communication systems. Her work bridges theoretical analysis with practical implementation, particularly in companding quantizers, polar quantization, and adaptive coding schemes. Publication Trends: Her recent publications (2020–2022) show a clear evolution toward integrating machine learning with classical signal processing, especially in post-training quantization of neural networks and AI-based compression. Earlier works (2013–2018) focus on theoretical foundations of quantization for Gaussian and Laplacian sources, with rigorous mathematical modeling and performance analysis. The consistent use of terms like 'companding', 'scalar quantizer', 'Gaussian source', and 'SQNR' reflects a strong foundation in information theory and digital communications. Scientific Awards: Prof. Dr. Ilija Stojanović Award (2017) – Best professional work in telecommunications Advising and Grants: She has mentored 2 master’s and 2 diploma students. She has participated in 10 major research projects funded by the Ministry of Education and Science of Serbia, Erasmus+, Norwegian Ministry of Foreign Affairs, and the Science Fund of Serbia, including projects on software-defined radio, dialogic systems, and AI-based quantization (Com-in-AI). She has also served on numerous academic committees for thesis defense, hiring, and academic evaluation across multiple institutions. Labs and Teams: While no specific lab name is mentioned, her involvement in experimental and computational work—such as laboratory exercises in acoustics, signal processing, and VoIP, as well as MATLAB-based practicals—indicates active participation in teaching and research labs at the Faculty of Electronics. She has collaborated extensively with Prof. Zoran Perić and others in the telecommunications group, forming a strong research team focused on quantization and compression.

Tan Chee Keongمشاهده پروفایل

مدرس ارشد

• Software-defined networks
• Beyond 5G networks
• Indoor positioning systems
• +۸ مورد دیگر

Dr. Tan Chee Keong is a Senior Lecturer at the School of Information Technology, Monash University, Malaysia. He holds a PhD in Information and Communication Technology from Multimedia University (2014). His expertise lies in network system design, with a focus on software-defined networks, beyond 5G networks, indoor positioning systems, game theory, machine learning, and data science. He has secured over RM 800K in research grants as a principal or co-investigator and contributed to over 10 international journal papers. Notably, he received the Best Teaching Award from Multimedia University in 2016. Research activities include projects funded by government and industry, such as AI-Driven Energy Management for Smart Cities and IoT-based energy monitoring systems. His work addresses challenges in network efficiency, indoor positioning, and smart city technologies. Dr. Tan has collaborated on projects involving UAV swarming intelligence, reinforcement learning, and autonomous systems. Education: B.Eng (Hons) in Electronics (Telecommunication), Multimedia University, 2006 M.Eng.Sc (Information and Communication Technology), Multimedia University, 2009 Ph.D (Information and Communication Technology), Multimedia University, 2014 Research Interests: Optimizing wireless networks and protocols Indoor positioning and trajectory tracking Game theory applications in network resource management Machine learning for signal processing and localization Recent publications (2023–2025) emphasize AI-driven solutions for energy efficiency, path planning in disaster environments, and blockchain-based logistics optimization. These reflect a trend towards integrating AI/ML with traditional networking challenges. Awards: Best Teaching Award, Multimedia University (2016) Grants & Projects: AI-Enabled Energy Management (RM 800K+) IoT-Based Energy Monitoring (2022–2025) Smart City IoT Applications He plays a key role in industry-academia collaborations, particularly in Malaysia’s tech sector. His labs focus on developing practical solutions for smart city infrastructure and next-generation communication systems.

Zhinong Yingمشاهده پروفایل

استاد

• Antennas
• Wireless Communication
• Millimeter-Wave Systems
• +۳ مورد دیگر

Zhinong Ying is a Professor in the Department of Electronic Systems at Aalborg University, Denmark. He specializes in antenna systems, electromagnetic propagation, and millimeter-wave technologies. His research focuses on reconfigurable intelligent surfaces, near-field MIMO systems, and 5G/6G antenna design. Education: Lic. Tech. in Microwave Antennas, Chalmers University of Technology (1995) M.S.E.E. in Wireless Antennas, Beijing University of Posts and Telecommunications (1986) Research interests include antenna design for mobile terminals, millimeter-wave applications, and electromagnetic exposure standards. He has led over 12 projects including 'New basic restrictions above 6 GHz for localized exposure' and 'MWF mm wave power density simulations.' Recipient of the IEEE Fellow award (2020) for contributions to antenna technologies. Active in conferences such as IEEE International Symposium on Antennas and Propagation. Advises projects on antenna measurement systems and collaborates with industry partners like Sony Research Center. His lab focuses on over-the-air testing platforms and hybrid beamforming architectures.

• Optical Communications
• Silicon Photonics
• High-Speed Electronics
• +۳ مورد دیگر

Bart Moeneclaey is an Assistant Professor at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology (EA05), and also serves as an IMEC Postdoctoral Researcher. His work bridges photonics and electronics for next-generation high-speed communication systems, with particular expertise in silicon photonics and integrated circuit design for optical networks. His primary research interests include: Optical Communications and Networking Silicon Photonics and Integrated Optoelectronics High-Speed Electronic Circuit Design Coherent Optical Receivers and Transmitters Photonic-Electronic Co-Design for Next-Generation Networks Electronic Design Automation for High-Speed Systems Analysis of his publication record (2020-2025) reveals a clear progression toward increasingly sophisticated integrated systems, with recent work focusing on 100+ GBd optical communication systems. His research demonstrates a strategic shift from fundamental circuit components (transimpedance amplifiers, modulator drivers) to complete system solutions, particularly emphasizing silicon photonics combined with advanced BiCMOS technologies. The trend shows increasing attention to practical implementation challenges while pushing performance boundaries, with multiple publications addressing 128-GBd systems and low-complexity architectures for next-generation optical networks. His significant research contributions include: Development of coherent passive optical networks Design of multi-gigabit coherent receivers Innovations in high-speed transimpedance amplifiers Advancements in analog demultiplexing architectures Low-complexity quasi-coherent receiver designs Dr. Moeneclaey serves as a PhD supervisor, currently guiding Jakob Declercq's doctoral research (2020-2026) focused on high-speed optical receiver design. Previously (2011-2016), he held a research fellowship funded by IWT/VLAIO for research into next-generation coherent passive optical networks, establishing his foundational expertise in this field. His work is conducted within Ghent University's photonics research ecosystem, collaborating closely with IMEC on integrated circuit and photonics design. These research efforts have significant implications for telecommunications infrastructure, data center interconnects, and high-performance computing networks, positioning Belgium at the forefront of photonics innovation.

Edward Gebaraمشاهده پروفایل

دانشیار

• Radiation-tolerant electronics
• Extreme temperature integrated circuits
• Self-healing integrated circuits
• +۴ مورد دیگر

Dr. Edward Gebara is an Associate Professor of Electrical and Computer Engineering at Michigan State University's College of Engineering. His expertise spans radiation-tolerant electronics, extreme-temperature integrated circuits, and self-healing mixed-signal techniques. He holds B.S., M.S., and Ph.D. degrees in Electrical and Computer Engineering from Georgia Institute of Technology (1996–2003). Research Interests: Radiation-tolerant electronics for aerospace Extreme temperature environment circuits Self-healing and reconfigurable ICs Wireless cancellation and signal integrity solutions Professional Activities: Former Director of Engineering at Electromagnetic Sensor Technologies Inc. (2011–2023) Adjunct Assistant Professor at Georgia Tech (2010–2011) IEEE MTT-S Symposium roles: Vice Chair (2010–2012), Technical Committee Chair (2018–2021), and Workshop Chair (2021) Awards: Best Paper Award at IEEE International Microwave Symposia (2000) Grants & Advising: Directed Ph.D. students in mixed-signal and microwave systems Led industry-academia collaborations in GaAs/GaN technologies Labs & Teams: Mixed-Signal Research Group at Georgia Tech (2003–2011) Electromagnetic Sensor Technologies R&D team

Liucheng Guoمشاهده پروفایل

پژوهشگر ارشد

• AI software-hardware co-design
• embedded AI
• high-performance computing (HPC)
• +۷ مورد دیگر

Dr. Liucheng Guo is a Visiting Senior Research Fellow and RAEng Industrial Fellow at King’s College London, affiliated with the Department of Mathematics within the Faculty of Natural, Mathematical & Engineering Sciences. His expertise spans AI software-hardware co-design, embedded AI, and high-performance computing (HPC), with a focus on sustainable human-machine interfaces (HMI) for sectors like IoT, Automotive, Healthcare, and XR. He holds a Ph.D. from Imperial College London and an MA from Peking University. Dr. Guo has co-founded the award-winning AI startup TG0, securing seven patent groups and over £20 million in grants from InnovateUK, RAEng, and the European Innovation Council. His research emphasizes smart home, IoT, and healthcare applications, including VR mirror therapy for post-stroke rehabilitation and gesture-based control systems. He is a Senior Member of IEEE and Fellow of IET/BCS/RSA, reflecting his leadership in bridging research and industry. His grants include Smart Grants, KTP awards, and SME Leader initiatives. He actively promotes STEM through roles as RAEng Visiting Professor and public engagement ambassador.

• Cloud computing
• Cybersecurity
• Software Engineering
• +۷ مورد دیگر

Paal Engelstad is a Professor at Oslo Metropolitan University's Faculty of Technology, Art and Design, Department of Computer Science. His research focuses on Cloud computing , Cybersecurity , and Software Engineering , with significant contributions to Graph Neural Networks (GNNs) and their applications in network analysis, renewable energy forecasting, and telecom systems. Research interests span Applied Artificial Intelligence and Autonomous Systems and Networks . Recent publications address spatio-temporal wind forecasting , GNN propagation schemes , and 5G network security . He contributes to advancements in renewable energy integration and telecom protocol analysis .

Tokunbo Ogunfunmiمشاهده پروفایل

استاد

• Deep Learning
• Artificial Neural Networks
• Adaptive Signal Processing
• +۷ مورد دیگر

Tokunbo Ogunfunmi is a Professor of Electrical and Computer Engineering and Director of the Information Processing and Machine Learning (IPML) Research Lab at Santa Clara University's School of Engineering. He served as Associate Dean for Research and Faculty Development from 2010-2014 and as Associate Dean for Mission, Culture and Inclusion from 2021-2024. Dr. Ogunfunmi holds a Ph.D. and M.S. from Stanford University (1990, 1984) and a B.S. from the University of Ife, Nigeria (1980). His research interests span deep learning, artificial neural networks, adaptive/nonlinear signal processing, digital signal processing, and multimedia signal processing with VLSI/DSP/FPGA implementations. Dr. Ogunfunmi has published 4 books and over 200 refereed journal and conference papers in these areas. His recent publications demonstrate strong focus on deep learning applications, hardware acceleration for neural networks, quaternion-based adaptive algorithms, and efficient video/speech processing techniques. Dr. Ogunfunmi has received numerous awards including the SCU Presidential Special Recognition Award (2020), IEEE Meritorious Service Awards (2021, 2013), Carnegie Foundation Visiting Professorships (2019, 2015), and multiple Best Paper Awards. He has served in significant editorial roles including Senior Associate Editor for IEEE Signal Processing Letters and Associate Editor for several IEEE Transactions. As an active member of the professional community, he is a Senior Member of IEEE, Member of Sigma Xi, and Member of AAAS. His industrial experience includes consulting for major companies such as Broadcom, AMD, NEC, AT&T Bell Labs, and NIKON Precision Research & Development. Dr. Ogunfunmi is also a registered professional engineer in California.

Lei Jiaoمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Tsetlin Machines
• +۷ مورد دیگر

Lei Jiao is a Professor in the Department of Information and Communication Technology at the University of Agder's Faculty of Engineering and Science. Previously serving as an Associate Professor from May 2014 to October 2022, Dr. Jiao has established himself as a leading researcher in artificial intelligence, with particular expertise in Tsetlin Machines and their applications across diverse domains. PhD in Information and Communication Technology, University of Agder (2008-2012) Master of Engineering in Communication and Information System, Shandong University (2005-2008) Bachelor of Engineering in Telecommunication Engineering, Hunan University (2001-2005) Dr. Jiao's research spans multiple cutting-edge areas including interpretable artificial intelligence, wireless communication protocols, network resource allocation, and signal processing. His work on Tsetlin Machines has pioneered new approaches to machine learning that emphasize interpretability while maintaining high performance. The research group he contributes to at the University of Agder focuses on Autonomous and Cyber-Physical Systems (ACPS), Battery recycling, and the Centre for Artificial Intelligence Research (CAIR). Analysis of Dr. Jiao's recent publications reveals a strong emphasis on interpretable AI systems, particularly through Tsetlin Machines. His work spans applications in GNSS jammer detection, crowd anomaly detection, DNA sequence classification, and hardware acceleration of machine learning models. The research consistently demonstrates how logical, rule-based approaches can provide transparent alternatives to traditional neural networks while maintaining competitive performance. Supervised numerous PhD students including Vojtech Halenka, Ahmed K. Kadhim, and Sindhusha Jeeru Mentored over 30 Master's thesis projects covering topics from Tsetlin Machines to signal processing and computer vision Collaborates extensively with Ole-Christoffer Granmo and other leading researchers in the AI field Dr. Jiao actively contributes to advancing the field through supervision of doctoral candidates, collaboration on major research projects, and development of novel machine learning approaches that balance performance with interpretability. His work bridges theoretical foundations with practical applications across telecommunications, computer vision, and natural language processing domains.

Mario Di Mauroمشاهده پروفایل

پژوهشگر

• Network Intrusion Detection
• Machine Learning
• Cybersecurity
• +۶ مورد دیگر

Mario Di Mauro is a prominent researcher in computer science and engineering, specializing in network security, intrusion detection, and network function virtualization (NFV). His work focuses on leveraging neural networks, machine learning, and stochastic modeling to enhance availability analysis in softwarized systems and telecommunications infrastructure. His research spans critical areas such as: Neural-based intrusion detection systems Optimal configurations for high-availability telecom systems Performance evaluation of multimedia protocols over LTE Machine learning for encrypted traffic detection Key trends in his publications include hybrid active learning for video quality assessment, sensitivity analysis of NFV architectures, and the application of deep learning to network security. Collaborations with co-authors like M. Longo, F. Postiglione, and G. Galatro highlight his interdisciplinary approach.

• Smart Grids
• Power Systems
• Energy Efficiency
• +۵ مورد دیگر

Dr. Krzysztof Billewicz serves as an Assistant Professor in the Department of Computer Science and Systems Engineering at the Faculty of Computer Science and Telecommunications, Wroclaw University of Science and Technology. Based in building C-3, room 122, he maintains active teaching responsibilities with consultation hours during the winter semester 2023/24 on Mondays (9:00-11:00) and Tuesdays (18:35-20:35, remote). His research spans the critical intersection of electrical engineering, energy policy, and human factors, with primary focus areas including smart grid development, electricity theft detection, building energy efficiency, and the psychological impacts of electrical systems. Work addresses Poland-specific energy challenges such as coal phase-out transitions, urban heat island effects, and grid modernization imperatives, demonstrating consistent interdisciplinary engagement between technical power systems analysis and socio-technical dimensions of energy infrastructure. Analysis of his 2016-2023 publications reveals evolving emphasis from foundational smart grid technologies toward integrated societal considerations. Key trends include methodological innovation in theft detection using consumption anomalies, critical assessment of policy impacts during energy transitions, and pioneering exploration of psychological dimensions in energy systems – establishing a distinctive research profile that bridges engineering rigor with human-centered perspectives in the Polish energy landscape. Scientific awards: No specific awards, fellowships, or medals were documented in available sources. Regarding academic mentoring, no information was provided about doctoral or master's students supervised. Similarly, details of research grants secured or laboratory affiliations were not mentioned in source materials, indicating primary focus on independent scholarly publication within the departmental framework.

Eleni Ekaterini Leligouمشاهده پروفایل

استاد

• Computer Networks
• Industrial Web Server Applications
• Blockchain Technology
• +۷ مورد دیگر

Professor Eleni Ekaterini Leligou is a full-time faculty member at the University of West Attica , serving in the Department of Industrial Design and Production Engineering since November 2017. Previously, she taught at the Technological Educational Institution of Central Greece (2007–2017) and was a research associate at the National Technical University of Athens (1998–2007). Education Diploma in Electrical and Computer Engineering, National Technical University of Athens (1995) PhD in Electrical and Computer Engineering, National Technical University of Athens (1998–2002) – thesis graded “Excellent” Research Interests Her work lies at the intersection of computer networks, blockchain, Internet of Things, and artificial intelligence with a strong emphasis on industrial and energy-management applications . Specific themes include trust and routing protocols for sensor networks, FPGA-based acceleration of network algorithms, blockchain-enabled network security, IoT solutions for smart energy systems, and federated-learning models for maritime energy optimisation. Teaching Contributions At undergraduate level she delivers core courses on Internet Technology in the Digital Industry, Cloud Computing Engineering and Data Security and Protection . At postgraduate level she contributes to four distinct programmes: Artificial Intelligence and Deep Learning (inter-departmental MSc), Information Systems (Hellenic Open University), Production and Service Automation , and New Technologies in Shipping and Transportation . Publications Overview Her 2024–2025 scholarly output demonstrates an aggressive push toward next-generation networks (6G, LiFi, RIS), blockchain integration in diverse domains (gaming, supply-chain, PLC security), and AI/ML methodologies ranging from federated learning to GAN-based image generation, all applied to industrial, maritime and educational contexts. Laboratory & Teams She conducts her research within the Computational Intelligence and Intelligent Systems Laboratory – EYNES , leading projects that blend networked embedded systems, AI and blockchain technologies.

François LE PENNECمشاهده پروفایل

پژوهشگر

• Antenna Design
• Underwater Wireless Communications
• Electromagnetic Compatibility
• +۴ مورد دیگر

François LE PENNEC is a Researcher in the Microwave Department at IMT Atlantique, working on the Brest campus. His academic position involves research in specialized areas of microwave engineering and wireless communications, with a focus on practical applications in challenging environments. Dr. LE PENNEC's research interests primarily center around antenna design, particularly for underwater and marine applications. His work explores the challenges of electromagnetic wave propagation in water environments, which presents significant technical hurdles due to water's attenuation properties. He has made notable contributions to underwater radio frequency communications, developing specialized antenna systems that can operate effectively in submerged conditions. Additionally, his research extends to the interaction between renewable energy infrastructure (particularly small wind turbines) and telecommunications systems, investigating how these green energy solutions can be integrated with cellular networks without causing electromagnetic interference. Analysis of Dr. LE PENNEC's publication record reveals a consistent research trajectory focused on practical engineering solutions for challenging communication environments. His work spans underwater wireless systems, electromagnetic compatibility issues with renewable energy installations, and advanced antenna design for 4G mobile technologies. The publications demonstrate a strong emphasis on experimental validation through measurements and modeling, with particular attention to real-world implementation challenges. His research bridges theoretical electromagnetic principles with practical engineering applications, showing particular expertise in solving problems related to signal propagation in non-standard media. Dr. LE PENNEC has contributed significantly to understanding the electromagnetic interactions between wind turbine installations and cellular base stations, providing valuable insights for the telecommunications industry as it seeks sustainable power solutions. His work on underwater communication systems represents an important niche within wireless communications research, addressing the growing need for reliable subsea data transmission for scientific, commercial, and defense applications.