جست‌وجوی استاد و پژوهشگر

• Antenna Engineering
• Microwave Technology
• RF Systems
• +۳ مورد دیگر

Zhishu Qu is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science. Her research focuses on reconfigurable antenna systems, particularly leveraging gallium-based liquid metals to enable dynamic beam steering, frequency agility, and phase control. She explores applications in millimeter-wave communications, LEO satellite systems, and phased array configurations. Key contributions include innovations in transmitarray unit cells, substrate integrated waveguide (SIW) phase shifters, and adaptive antenna designs. Her work spans theoretical analysis of antenna performance limits and practical implementations of liquid metal actuation in RF components. Research interests also encompass microwave engineering, electromagnetic compatibility, and next-generation wireless infrastructure. Current trends in her publications emphasize miniaturization, low-loss solutions, and reconfigurability for 5G and beyond. Notable research areas include: Beamforming algorithms for satellite communications Liquid metal integration in RF systems Millimeter-wave phased array optimization Adaptive antenna pattern reconfiguration Publications since 2020 demonstrate sustained contributions to reconfigurable antenna architectures, with recent work (2024-2025) focusing on beam switchable antennas and distributed beamforming schemes.

• Satellite Networks
• 5G/6G Non-Terrestrial Networks
• Artificial Intelligence in Space
• +۶ مورد دیگر

Peng Hu is an Adjunct Professor at the University of Waterloo, focusing on cutting-edge research in satellite networks, 5G/6G non-terrestrial networks, and AI-driven solutions for space sustainability. His work emphasizes autonomous network management, edge computing in space, and IoT applications for industrial and healthcare systems. Research interests span satellite mega-constellations, space object detection via deep learning, and optimizing free-space optical (FSO) communication. He explores challenges in latency management, energy efficiency, and fault tolerance across heterogeneous networks, including UAV-assisted systems and industrial IoT. Key contributions include the SatAIOps framework for autonomous satellite operations and the SatNetOps multi-layer networking scheme. He has pioneered datasets like Satellite Object Detection (SOD) and developed anomaly detection methods using genetic algorithms and Monte Carlo dropout. Peng Hu’s recent work addresses global connectivity gaps via non-terrestrial networks and reviews reinforcement learning algorithms for space-air-ground integration. His technical leadership is reflected in workshops like the 5th IEEE ICC 2025 Satellite Mega-Constellations workshop.

George Shakerمشاهده پروفایل

دانشیار مدعو

• Wireless Sensor Technologies
• Biomedical Engineering
• Antennas and Propagation
• +۵ مورد دیگر

George Shaker is an Adjunct Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada, and Lab Director of the Wireless Sensors and Devices Laboratory at the Schlegel-UW Research Institute for Aging. He is also Chief Scientist at Spark Technology Labs. His research focuses on wireless sensor technologies for healthcare, autonomous systems, and IoT. He earned his bachelor's from Cairo University and master's/PhD from the University of Waterloo. Education: Bachelor’s degree, Cairo University, Egypt Master’s degree, University of Waterloo, Canada PhD, University of Waterloo, Canada Research Interests: Dr. Shaker’s work spans advanced wireless sensor systems for healthcare monitoring, UAVs, and automotive applications. His lab developed the MIRADA initiative for aging populations and pioneered radar-based non-invasive glucose monitoring. Key areas include mm-wave radar, antenna design, bioelectromagnetics, and machine learning integration. He has co-authored over 200 publications and holds 35+ patents, collaborating with companies like Google, Apple, and Toyota. Recent Article Trends: His 2025 work emphasizes AI-driven radar systems for activity recognition, bio-sensing metasurfaces, and UAV classification using digital twins. Projects include 4D radar imaging, low-cost milk quality monitoring, and smart furniture for cardiac health. Awards: IEEE AP-S Best Paper Award IEEE MTT-S Graduate Fellowship arXiv Top Downloaded Medical Article URSI Young Scientist Award Multiple student awards (see full list above) Advising & Grants: He advises graduate students in ECE and has led projects funded by NSERC and industry partners. His students have won Velocity Fund, NASA Tech Briefs, and Canadian Space Agency awards. Collaborates with over 40 companies including Amazon, Microsoft, and Medella Health. Labs & Initiatives: Leads the Wireless Sensors & Devices Lab and co-founded MIRADA, a smart apartment for aging healthcare. Active in Spark Labs for wireless innovation.

• In-Memory Computing
• Energy-Efficient Systems
• Machine Learning Accelerators
• +۳ مورد دیگر

Prof. Naresh R. Shanbhag holds the Jack S. Kilby Professorship in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. He is affiliated with the Coordinated Science Lab and the Information Trust Institute, both part of the College of Engineering. His research focuses on energy-efficient computing architectures, in-memory computing, nanoelectronics, and secure machine learning systems. Prof. Shanbhag has pioneered work on statistical error compensation techniques and resistive crossbar-based architectures, addressing critical challenges in low-power, high-performance computing. Education and career details are not explicitly provided in the text, but his extensive publications (313+) and honors indicate deep academic involvement. His research interests emphasize the intersection of hardware architecture and machine learning, with a focus on emerging technologies like MRAM and SRAM-based in-memory computing. Key awards include the IEEE Fellow designation (2006) and the prestigious Semiconductor Industry Association (SIA) University Research Award (2018). His recent work explores security vulnerabilities in in-memory architectures, energy-accuracy trade-offs in resistive systems, and adversarial robustness of neural networks. Prof. Shanbhag’s contributions span over 20 years, bridging theoretical computer science with practical hardware implementations. His lab (Coordinated Science Lab) and collaborations drive innovations in nanoscale information processing and trustworthy computing systems.

• Signal Processing
• Wireless Communications
• Networking
• +۳ مورد دیگر

Philippe Ciblat is a Professor at TELECOM Paris Tech, affiliated with the Department of Signal Processing and Communications. His research spans signal processing, wireless communications, and machine learning applications in networking. He has collaborated extensively with institutions like the University of Paris-Saclay and international researchers in areas such as cooperative communication protocols, resource allocation, and coding theory. Research Interests: Machine learning for signal processing, wireless channel modeling (Rician fading), lattice decoding, caching strategies, and distributed optimization. Notable Work: Pioneered transformer-based packet scheduling, neural network approaches to lattice decoding, and effective capacity analysis in fading channels. His contributions include over 170 publications in top venues (IEEE Trans. Signal Process., IEEE Trans. Wireless Commun.) and collaborations with industry partners on practical implementations like cache-aided polar coding. He has advised multiple researchers in distributed systems and wireless resource management.

Ali Lalbakhshمشاهده پروفایل

مدرس

• Electrical Engineering
• Antenna Design
• Metamaterials
• +۳ مورد دیگر

Ali Lalbakhsh is a Lecturer in the Department of Engineering at Macquarie University College, specializing in engineering education and antenna design. He focuses on fostering a growth mindset among students in the Diploma of Engineering program, emphasizing engagement, confidence-building, and real-world application. His teaching strategies have significantly improved student attendance, assignment submission rates, and satisfaction. He redesigned curricula for units like WENG1000 and WENG1050, incorporating scaffolded learning, peer feedback, and industry-inspired projects. His research spans metamaterials, 3D-printed antennas, and microwave engineering, with over 50 publications in top journals and conferences. He led students to national recognition in the D.Start 2022 innovation program and co-authored peer-reviewed papers with students. His work bridges educational innovation and cutting-edge antenna technology. Education: PhD in Electrical Engineering (Implied by publication track) Research Interests: Ali’s research focuses on advancing antenna technologies through metamaterials, 3D printing, and AI-driven design. He explores applications in satellite communications, 5G, and IoT systems. His work addresses challenges in beam steering, bandwidth optimization, and low-profile antenna design. Recent projects include phase-modulation metasurfaces for satellite antennas and AI-enhanced impedance matching structures. Awards: 2023 Vice-Chancellor’s Learning and Teaching Award (Student Nominated) Student Impact: Ali mentors students in research projects, leading to publications and innovation awards. His pedagogical approach emphasizes one-on-one feedback and goal-setting, enabling students to achieve beyond expectations. Collaborative projects with students have resulted in journal papers and national competitions. Labs/Teams: Active in Macquarie University’s engineering research groups focused on antenna design and educational technology.

Baibhab Chatterjeeمشاهده پروفایل

استادیار

• Biomedical IoT
• Wireless Implants
• Low-Power Circuits
• +۲ مورد دیگر

Baibhab Chatterjee is an Assistant Professor in Electrical and Computer Engineering at the University of Florida. His research focuses on developing energy-efficient integrated circuits and systems for biomedical IoT applications, neural implants, and secure body area networks. Research interests include ultra-low power circuits for biomedical sensors, novel wireless communication techniques through human tissues, brain-computer interfaces, and hardware security for implantable devices. His lab develops innovative solutions for next-generation healthcare monitoring and intervention systems. Recent publications demonstrate expertise in wireless power transfer for implants, in-memory computing architectures, and communication techniques optimized for the human body environment. The work consistently addresses challenges of miniaturization, power efficiency, and reliability in biomedical systems. Best 3-Minute Thesis Award, IEEE Microwave Week 2020 Best Paper Awards at IEEE CICC and HOST conferences Bilsland and Andrews Fellowships

Laura Toniمشاهده پروفایل

دانشیار

• Machine Learning
• Signal Processing
• Immersive Communications
• +۵ مورد دیگر

Laura Toni is an Associate Professor in the Department of Electronic & Electrical Engineering at University College London (UCL). She serves as Director of the MSc in Telecommunications and Internet Engineering and the MRes in Telecommunications. Additionally, she is a Turing Fellow at the Alan Turing Institute and a member of ELLIS (European Lab for Learning and Intelligent Systems). Her research focuses on coding, streaming technologies, machine learning for immersive communications, decision-making under uncertainty, and large-scale signal processing. She leads the LASP (Learning And Signal Processing) group at UCL. Education: MSc (2005) and PhD (2009) from the University of Bologna, followed by postdoctoral research at UC San Diego and EPFL under Professors L. Milstein, P. Cosman, and P. Frossard. Key roles include Technical Program Chair at ACM MM 2022, Keynote Co-Chair at ACM MMSys 2022, and leadership in organizing workshops on graph-based machine learning and emerging technologies in performing arts. She is a Senior IEEE Member and holds editorial roles in IEEE Multimedia Magazine and EURASIP Journal on Signal Processing. Her work bridges communication systems and machine learning, with contributions to adaptive streaming, network optimization, and graph signal processing. She actively promotes diversity and inclusion in technical conferences, including roles as Diversity Chair at MMSys 2021 and PIMRC 2020.

Bletsas Aggelosمشاهده پروفایل

استاد

• Wireless Transmission
• Wireless Relay Networks
• Software-Defined Radio
• +۳ مورد دیگر

Aggelos Bletsas is a Professor at the School of Electrical and Computer Engineering, Technical University of Crete. He holds a PhD from MIT (2005) and has expertise in wireless communication, backscatter networks, and RFID systems. His research focuses on scalable wireless networks, ultra-low-cost sensor technologies, and signal processing. Education: PhD, MIT Media Lab (2005) MSc, MIT Media Lab (2001) Diploma in Electrical & Computer Engineering, Aristotle University of Thessaloniki (1998) Research Interests: His work spans wireless transmission techniques, backscatter sensor networks, and RFID systems. Key areas include: Ultra-low-cost sensor deployment RFID localization and multi-static systems Energy-efficient hardware implementations Probabilistic inference in distributed networks Awards: IEEE Marconi Prize Paper Award (2008) Technical University of Crete Research Excellence Award (2012-2013) Multiple best paper awards at RFID-TA, ISWCS, and SENSORS Academic Contributions: He advises students who have won IEEE best thesis awards and leads projects funded by ERC grants. His laboratory focuses on practical implementations of wireless sensor networks and backscatter systems. Labs & Affiliations: Director of the Telecommunications Laboratory and affiliated with the Telecommunication Systems Institute (TSI).

Per Lynggaardمشاهده پروفایل

استاد

• Integrated Circuit Design
• Wireless Sensor Networks (WSN)
• Machine Learning
• +۸ مورد دیگر

Per Lynggaard is a Professor of Electronics at the Technical University of Denmark (DTU) , leading the B.Eng. program in Electronics. Previously, he held an Associate Professor role at Aalborg University, combining academic excellence with a robust industrial career in technical-scientific research and development. Education: M.Sc. in Electrical Engineering and Information Technology (EE and IT) Ph.D. in Electronics from Aalborg University Research Interests: Focus on Integrated Circuit Design, Wireless Sensor Networks (WSN), Machine Learning, IoT, and Smart City Technologies . His work emphasizes energy-efficient systems, cybersecurity in IoT, AI-driven interference mitigation, and sustainable energy harvesting solutions. He has contributed to UN Sustainable Development Goals through projects addressing smart infrastructure and environmental monitoring. Projects & Collaborations: Leads and participates in EU-funded initiatives such as InnoTech (2023–2025) for green transition solutions and TransportTech (2023–2026) for Industry 4.0 logistics. Active in cybersecurity research via projects like Jamming Against Critical Wireless Communication , aiming to protect critical infrastructure. Awards: Recognized with multiple honors and rewards during his industrial career, though specific names are not listed. His work has been cited widely, with notable impact in IoT security and energy-efficient systems. Advising & Grants: Supervises Turnip T.N. in a PhD project on 6G security protocols. Engaged in securing funding for projects like F2D2: The Community for Dynamic Data (2021–2030), focusing on dynamic data systems and cybersecurity. Labs & Teams: Collaborates in interdisciplinary teams such as the InnoTech TaskForce and F2D2 Community , advancing IoT and AI integration. His research bridges academia and industry, with outputs spanning smart cities, healthcare IoT, and sustainable energy systems.

Davi V. Q. Rodriguesمشاهده پروفایل

استادیار

• Signal Processing
• Microwave/Millimeter-Wave Circuits
• Radar Systems
• +۷ مورد دیگر

Dr. Davi V. Q. Rodrigues is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). His research focuses on microwave/millimeter-wave circuits and signal processing for radar, communication systems, and smart living applications. He holds a B.S. in Communications Engineering from the Military Institute of Engineering (Brazil) and a Ph.D. in Electrical Engineering from Texas Tech University. Prior to academia, he served in the Brazilian Navy and Army, and worked at Uhnder, Inc., Abbott Laboratories, and Dell Technologies. His work emphasizes radar-based smart home, healthcare, and autonomous systems, with contributions in structural health monitoring, human activity recognition, and joint communication-sensing technologies. Dr. Rodrigues has received prestigious awards including the 2022 IEEE MTT-S Tom Brazil Fellowship and the 2023 Texas Tech Horn Distinguished Professors Award. His research group, the Microwave Circuits & Sensing Systems Group, develops algorithms and hardware for biomedical sensing, non-contact health monitoring, and 6G-enabled applications. He actively seeks motivated graduate students interested in radar systems, signal processing, and wireless technologies. Education: B.S., Communications Engineering, Military Institute of Engineering (2017) Ph.D., Electrical Engineering, Texas Tech University (2023) Research Interests: Microwave/mm-wave radar systems Human activity monitoring and gesture recognition Structural health monitoring 6G/ B5G communication-sensing fusion Passive and opportunistic RF sensing His publications span radar-based smart living solutions, biomedical sensors, and reconfigurable intelligent surfaces (IRS). He is an IEEE MTT-S member and has contributed to industry partnerships through collaborations with Uhnder and Dell Technologies. Current projects integrate AI-driven radar signal analysis and low-cost sensor networks for healthcare and infrastructure monitoring.

Y. Charlie Huمشاهده پروفایل

استاد

• Mobile Systems
• Distributed Systems
• Operating Systems
• +۵ مورد دیگر

Y. Charlie Hu is the Michael and Katherine Birck Professor of Electrical and Computer Engineering and Professor of Computer Science (by courtesy) at Purdue University, where he leads the PurNET Lab and contributes to the Systems and Networking Group. His research spans Mobile Systems, Distributed Systems, Operating Systems, and Computer Networks , with a focus on energy-efficient AI systems and edge computing. His groundbreaking work on smartphone energy management has been widely adopted by the mobile industry and recognized with multiple test-of-time awards , including from ACM SIGOPS and ACM SIGMOBILE . He has received prestigious honors like the NSF CAREER Award , Honda Initiation Grant , and industry accolades from Google Research and Qualcomm . Notable Funded Projects: NSF's NeTS: Black-box Optimization of White-box Networks (2023-2026) Intel -NSF's SPLICE initiative His research has produced 15+ PhD graduates now in academia (University of Arizona, Virginia Tech) and industry (Google, Apple, Qualcomm). The articles reflect a career-long focus on edge computing , 5G network optimization , and energy-aware systems , with recurring themes in mobile AR/VR , video analytics , and network protocol design . Scientific Awards Honda Initiation Grant NSF CAREER Award Purdue Early Career Research Award Google Research Award Qualcomm Faculty Award ACM SIGOPS EuroSys Best Student Paper Award ACM MobiCom Best Community Paper Award IEEE Fellow ACM Distinguished Scientist Purdue PRF Innovator Hall of Fame

Dong S. Haمشاهده پروفایل

استاد

• Analog IC Design
• RF ICs
• Power Management Circuits
• +۷ مورد دیگر

Dong S. Ha is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. As Founding Director of the Multifunctional Integrated Circuits & Systems (MICS) Lab, he focuses on advanced circuit design for energy harvesting, RF systems, and high-temperature electronics. His work spans analog/RF ICs, power management circuits, and wireless IoT solutions with machine learning integration. Education: PhD (1986) and MS (1984) in Electrical and Computer Engineering from the University of Iowa; B.S. (1974) in Electrical Engineering from Seoul National University. Research interests include energy harvesting (piezoelectric, thermal, RF), high-temperature RF circuits for oil/gas/spacecraft applications, and smart IoT systems. He actively seeks students for projects in RF design, energy harvesting, and embedded systems. His lab develops cutting-edge solutions for harsh environment communication, sustainable energy systems, and smart agriculture monitoring. Awarded IEEE Fellow (2008) for contributions to VLSI design/test. Key publications span energy harvesting circuits, GaN-based high-temperature systems, and low-power IoT architectures. Current projects include self-sustaining smart farm networks using federated learning and attack-resistant sensor systems. Labs/Teams: Leads MICS Lab focusing on integrated circuits and systems. Collaborates on cross-disciplinary projects involving machine learning, embedded systems, and sustainable energy. Active in industry partnerships for aerospace and automotive applications.

• Cybersecurity
• Data Security and Privacy
• Context-Aware Access Control
• +۵ مورد دیگر

Dr ASM Kayes serves as Senior Lecturer in Cybersecurity and Cyber Curriculum Lead at La Trobe University's Department of Computer Science and Information Technology, where he shapes cybersecurity education programs including Master's, Bachelor's, and Double Degrees. His academic journey began with a PhD from Swinburne University of Technology in 2015, followed by postdoctoral research at La Trobe before joining as Lecturer in 2019 and promotion to Senior Lecturer in 2022. His research spans critical cybersecurity domains including data security, privacy preservation, context-aware access control, malware/ransomware defense, and IoT/fog/cloud security leveraging AI/ML techniques. Dr Kayes has established himself as a leading voice in blockchain security frameworks, privacy policy analysis, and cyber incident response through publications in top-tier venues like ACM Computing Surveys, IEEE Internet of Things Journal, and Computers & Security. His recent publications reveal a strong trajectory toward integrating AI with traditional security frameworks, particularly in blockchain risk assessment (2025), cross-domain access control (2025), and IoT behavior prediction (2024). The research demonstrates consistent focus on practical security solutions addressing ransomware mitigation, privacy breaches, and emerging threats in decentralized systems. Over $880,000 secured as Chief Investigator for cybersecurity projects Australian Government Department of Social Services grant (2023-2026) for cyberbullying prevention AustCyber research funds with industry partners (2020-2023) SmartSat CRC and ASCRIN PhD scholarship grants (2021) Dr Kayes has successfully supervised 5 PhD candidates to completion and currently mentors 5 doctoral students across diverse topics including AI-driven threat hunting, satellite network security, and blockchain risk frameworks. His collaborative network spans UK, USA, Europe, and Asia, with active industry partnerships through Westpac, BHP, and Quantum Victoria. He serves on editorial boards for leading cybersecurity journals and has examined HDR dissertations globally, reflecting his significant standing in the academic community.

David Stoneمشاهده پروفایل

استاد

• Power Electronics
• Energy Storage
• Renewable Energy Systems
• +۵ مورد دیگر

Professor David Stone is a faculty member in the School of Electrical and Electronic Engineering at the University of Sheffield, where he holds the position of Professor in Electrical Engineering and serves as Theme Lead for Electrical Machines. He earned his BEng (Hons) in Electronic Engineering from the University of Sheffield (1982–1985) and a PhD in Automatic Weld Penetration Control from Liverpool University (1989). Since joining the University of Sheffield in 1989, he has been affiliated with the Electrical Machines and Drives (EMD) Group, advancing to full professorship in 2013. His research focuses on power electronics , energy storage systems , and their applications in electric vehicles (EVs) and renewable energy integration . Notable work includes leading the CREESA initiative, which operates the UK's largest grid-connected lithium titanate battery storage system. Current projects explore hybrid energy storage, EV battery second-life applications, and high-frequency resonant converters for industrial heating. Research interests span: Simulation of energy systems and hybrid storage technologies Electric vehicle energy consumption modeling using dashcam telemetry Smart battery management for EVs and grid support High-efficiency wireless EV charging systems Advanced control strategies for power converters His publications (2020–2025) reflect contributions to: Energy storage system design and control Electric machine fault detection and diagnostics Grid integration of renewable energy sources Piezoelectric transformer-based power supplies Microgrid optimization with hybrid energy storage He collaborates with industry through initiatives like the EPSRC Prosperity Partnership in Offshore Wind and the TransEnergy project linking road-rail energy exchange. His work addresses challenges in sustainable energy systems and smart grid technologies.