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Jarek WosikView profile

Research Professor

• Biomedical Engineering
• Superconductivity
• Magnetic Resonance Imaging
• +2 more

Jarek Wosik is a Research Professor in the Department of Electrical and Computer Engineering at the University of Houston's Cullen College of Engineering. He holds a Ph.D. in Physics from the Institute of Physics, Polish Academy of Science and an M.S. in Solid State Physics from Warsaw University. Dr. Wosik's research focuses on electromagnetic applications in biomedicine and materials science, including: interaction of RF/static magnetic fields with biological systems; RF/microwave characterization of superconducting materials; time-reversal focusing techniques for medical applications; RF heating of nanoparticles for cancer hyperthermia; and high-resolution MRI technology development using cryogenic/superconducting coils. His funded research includes projects on magnetic field-induced cell alteration for transplant rejection prevention and electromagnetic devices for biomedical applications. Dr. Wosik has authored over 90 publications and holds multiple patents in MRI technology and electromagnetic sensing. Patent: Cryogenic cooling of MRI surface coils (US 9,594,131) Patent: Intraluminal magneto sensor system (US 8,212,554B2) Patent: Superconducting array of surface MRI probes (US 7,511,497)

Fan YeView profile

Professor

• Mobile and embedded sensing systems
• AI/ML algorithms
• Data-centric wireless communication
• +3 more

Fan Ye is a Professor in the Department of Electrical and Computer Engineering at Stony Brook University, serving as Graduate Program Director. His research focuses on mobile/embedded sensing systems, AI/ML for Computational Screening and Surveillance (CSS), data-centric wireless communication, edge computing, and IoT. He leads projects in health monitoring infrastructure (e.g., Proteus) and vehicular peer model training (e.g., Roadtrain), emphasizing scalability and manageability. His work bridges hardware-software integration for real-world applications like non-contact vital signs monitoring and aging-in-place sensor tech. Research trends reflect a strong emphasis on practical systems: 2024 publications highlight RF-based health monitoring innovations, edge computing optimizations, and user-centric sensor development. Earlier work includes contributions to decentralized machine learning, self-calibrating indoor tracking, and UWB-depth sensor fusion. Collaborations span academia and industry, addressing challenges in privacy, energy efficiency, and real-time data processing. Ye’s lab develops scalable solutions for pervasive edge environments, addressing issues like multicast rate control, optimal producer selection (OPSEL), and blockchain resource allocation. His teaching contributions include collaborative approaches to aging technology education. Current projects aim to engage older adults in shaping low-cost sensor systems and improving post-COVID health monitoring through unobtrusive home sensors. Notable infrastructure includes the Proteus health monitoring platform and SCALING for plug-and-play indoor tracking. His systems emphasize robustness and adaptability, leveraging acoustic, radar, and vision modalities for multi-factor authentication and indoor mapping.

Hervé RivanoView profile

Professor

• Network Design
• Wireless Networks
• Combinatorial Optimization
• +4 more

Hervé Rivano is a University Professor at INSA Lyon and the head of the Inria/INSA Lyon CITI Agora team, focusing on wireless networking challenges in urban environments. He leads the computer science teaching at the FIMI department, overseeing a dynamic curriculum reform. His research interests include combinatorial optimization for network design, energy-efficient urban cellular networks, and low-cost wireless sensor networks for environmental monitoring. He co-supervises PhD students in areas like IoT and pollution monitoring. Rivano is involved in educational programs like the SMART international initiative and has contributed to MOOCs on Smart Cities. His work spans academic leadership, research innovation, and pedagogical advancements in digital urban systems. Education: PhD from University of Nice-Sophia Antipolis (2003), supervised by Afonso Ferreira and Jérôme Galtier. Graduated from École Normale Supérieure de Lyon. Research Teams: Agora team (6 faculty, 10-15 PhDs, 2-5 postdocs/engineers) addressing urban wireless networks and Smart Cities. Teaching Roles: Coordinates IoT and urban networks modules, leads FIMI's computer science discipline, and contributed to the 'Smart Cities' MOOC. Key Projects: Urbanet (predecessor of Agora), participatory air quality monitoring systems, and interdisciplinary urban data initiatives. His work emphasizes sustainable, data-driven urban solutions.

Shannon David BluntView profile

Professor

• Radar Signal Processing
• Waveform Design and Optimization
• Cognitive Radar Systems
• +3 more

Shannon David Blunt is the Roy A. Roberts Distinguished Professor at the University of Kansas, affiliated with the School of Engineering's Department of Electrical Engineering and Computer Science. His research focuses on advanced radar signal processing, waveform design, cognitive radar systems, and radar-communications integration. He leads experimental projects such as the Waveform Diversity Experimentation System (WaDES) and the SMART Hub initiative addressing spectrum crisis challenges. His work emphasizes spectral efficiency, adaptive processing, and real-time cognitive radar solutions. Blunt holds editorial roles, including founding the IEEE Transactions on Radar Systems, and has contributed to over 100 peer-reviewed articles since 2017. Research Interests: Radar signal processing innovations include optimizing radar waveforms for multifunction digital arrays, developing random FM techniques, and advancing clutter suppression algorithms. His research bridges radar and communications via initiatives like Phase-Attached Radar-Communications (PARC) and Multi-User Radar/Communications (MURC). Key areas include waveform diversity, spectrum sharing, and real-time spectral notching for cognitive radar. He explores bio-inspired systems and medical signal processing applications, though his primary focus remains radar systems engineering. Recent Trends in Articles: Recent work (2023–2025) emphasizes hybrid FM waveforms, reiterative super-resolution algorithms, and physical waveform optimization. Publications address challenges in Doppler robustness, waveform recycling, and experimental validation of spectrum-sharing technologies. Collaborations with industry and government labs highlight applied research in spectrum management and mm-wave radar for automotive/urban mobility. Awards & Recognition: Roy A. Roberts Distinguished Professorship Leadership in the IEEE Radar Journal and Special Sections Grants & Labs: Directs the SMART Hub (Solving the Spectrum Crisis) and oversees WaDES. His lab's experimental systems demonstrate real-time cognitive radar and spectrum-sharing solutions. Advises on federal grants for radar spectrum engineering and vehicular RF convergence projects. Labs & Teams: Active in the University of Kansas's radar engineering group, collaborating with the SMART Hub consortium and industry partners like Raytheon and Boeing.

• Computer Networking
• Machine Learning
• Wireless Sensor Networks
• +3 more

Dr. Mahmood Safaei is an Assistant Professor of Instruction in the Department of Computer Information Systems at The University of Akron's College of Engineering and Polymer Science. His research focuses on wireless communication systems, machine learning applications, and sensor network technologies. He has contributed to advancements in antenna design, obesity evaluation through hybrid MCDM methods, and remote sensing image classification using deep learning algorithms. His work spans diverse domains including metamaterials, acoustic signal processing for industrial supervision, and anomaly detection in wireless networks. Notable projects include reconfigurable intelligent surfaces for 5G/6G networks and the development of SmartSim, a simulation tool for TinyOS-based systems. His academic contributions bridge theoretical research with practical applications in healthcare, telecommunications, and manufacturing. Dr. Safaei's publications highlight interdisciplinary approaches, combining engineering principles with data science techniques to address challenges in modern communication systems and healthcare technology adoption.

Nam NguyenView profile

Professor

• Complex Network Analysis
• Mobile Computing
• Social Data Analysis
• +5 more

Nam Nguyen is a Professor in the Department of Computer and Information Sciences at Towson University. He holds a Ph.D. in Computer Science from the University of Florida (2013), an M.S. from Ohio University (2009), and a B.S. from Vietnam National University (2007). His research focuses on complex network analysis, mobile computing, social data analysis, and data mining with applications in cybersecurity and big data. Education: Ph.D., Computer Science, University of Florida (2013) M.S., Computer Science, Ohio University (2009) B.S., Computer Science, Vietnam National University (2007) Research Interests: His work explores network vulnerability assessment, dynamic community detection, and applications in cybersecurity, mobile systems, and social computing. Recent projects include analyzing misinformation containment in social networks and developing robust algorithms for adaptive network structures. Professional Contributions: Nguyen has authored over 30 publications in top-tier venues like IEEE INFOCOM and IEEE Transactions journals. He serves as Associate Editor for Computational Social Networks and has organized conferences like CSoNet 2015. His reviews span multiple IEEE journals and conferences, emphasizing computational methods in social systems and network science. Labs/Teams: Engages in interdisciplinary collaborations on network resilience, mobile computing, and big data analytics through Towson University’s research initiatives.

Yuhong LiuView profile

Associate Professor

• Trustworthy Generative AI
• Blockchain Security
• IoT Anomaly Detection
• +3 more

Yuhong Liu is an Associate Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering. She holds a B.S. and M.S. from Beijing University of Posts and Telecommunications (2004, 2007) and a Ph.D. from the University of Rhode Island (2012). Her research focuses on trust, security, and privacy in emerging technologies including Generative AI, IoT, blockchain, and social media. She leads the Trustworthy Computing Lab, which develops solutions for IoT security, misinformation detection, and energy-efficient systems. Her research spans: Generative AI : Trustworthy synthetic data generation and multi-agent collaboration Blockchain : Multi-signature schemes and decentralized consensus IoT Security : Anomaly detection and lightweight cryptography Social Media : Misinformation mitigation and privacy preservation Recent publications emphasize blockchain-enabled security, IoT anomaly detection, and AI fairness, reflecting a trend toward practical, cross-domain solutions for cyber-physical systems. Her work frequently integrates machine learning with cryptographic techniques to address real-world vulnerabilities. Awards & Honors: IEEE Rising Star Service Award (2023) APSIPA Distinguished Lecturer (2021-2022) Researcher of the Year, Santa Clara University (2019) Best Paper Awards at IEEE SocialCom 2010 & UMEDIA 2016 She advises 7+ graduate students on IoT security, blockchain, and social media analytics. She co-leads the NSF-funded EuReCa Global Center for clean energy research and has organized panels on AI ethics and disinformation. Her lab collaborates with industry partners to deploy secure edge computing solutions.

Noam HarelView profile

Professor

• Neuroimaging
• Deep Brain Stimulation (DBS)
• Magnetic Resonance Imaging (MRI)
• +6 more

Noam Harel is a Professor in the Department of Radiology at the University of Minnesota Medical School and a core member of the Center for Magnetic Resonance Research (CMRR). His research focuses on advancing neuroimaging techniques, particularly high-field MRI (7T and above), and their clinical applications in neurological disorders such as Parkinson’s disease and essential tremor. He leads efforts in developing novel methods for deep brain stimulation (DBS) targeting, motion correction in medical imaging, and segmentation of subcortical structures using AI-driven approaches. Dr. Harel’s work integrates advanced MRI technologies with neurophysiological studies, emphasizing patient-specific models for DBS lead placement and safety. His group contributes to non-human primate neuroimaging research, advancing comparative models for brain development and function. Key innovations include methods for predicting RF-induced heating in DBS electrodes during MRI and creating brain charts for rhesus macaques. His publications highlight trends in DBS mechanism elucidation, high-resolution anatomical segmentation, and translational applications of ultra-high-field MRI. While no specific awards are listed, his contributions are reflected in over 100 peer-reviewed articles and active clinical trials. Collaborations span radiology, neurology, and biomedical engineering to optimize neuromodulation therapies and neuroimaging pipelines.

Gregory MetzgerView profile

Professor

• Medical Physics
• Magnetic Resonance Imaging (MRI)
• Radiology
• +3 more

Gregory Metzger, PhD, is a Professor in the Department of Radiology at the University of Minnesota, School of Medicine. He serves as a faculty member in the PhD Program in Medical Physics and a preceptor in the Medical Scientist Training Program (Combined MD/PhD). His research focuses on advancing MRI technologies, particularly at ultrahigh fields (e.g., 7T and 10.5T), RF coil design, and applications in prostate cancer imaging, neuroimaging, and clinical diagnostics. Dr. Metzger leads the Center for Magnetic Resonance Research, driving innovations in quantitative MRI, RF engineering, and translational imaging solutions. Key research interests include optimizing signal-to-noise ratios (SNR) for high-resolution imaging, developing novel RF coil arrays, and applying machine learning to improve diagnostic accuracy in prostate cancer. His work addresses challenges in clinical MRI safety, such as thermal noise reduction and RF shimming for parallel transmission systems. Recent studies explore in vivo metabolic imaging of the brain at 10.5T and non-invasive evaluation of meniscus degeneration using T2*-mapping. Dr. Metzger has contributed to the development of advanced imaging protocols, including universal mode acquisition methods and Bayesian spatial partitioning techniques for lesion detection. His interdisciplinary collaborations span radiology, biomedical engineering, and oncology, aiming to translate cutting-edge MRI innovations into clinical practice.

• Space Engineering
• Earth Observation
• Satellite Communications
• +3 more

Roger Birkeland is a Researcher at the Department of Electronic Systems , Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering . His work focuses on the design and development of small satellites for Earth observation and communication, with an emphasis on maritime and Arctic applications. Co-founder and former leader of the NTNU Student Satellite Project Key contributor to the establishment of the NTNU Small Satellite Lab Research Interests include: Small satellite systems (CubeSats) Hyperspectral imaging payloads Software-defined radios (SDRs) for space communication Arctic sensor networks Integration of unmanned surface vehicles (USVs) with satellite systems Additive manufacturing for space components Recent publications highlight advancements in: Agile satellite maneuvering for improved imaging On-board processing for hyperspectral data Interference measurement in Arctic radio bands Low-cost prototyping materials via 3D printing

Dirk PeschView profile

Professor

• Artificial Intelligence
• Data Analytics
• Algorithmics
• +9 more

Professor Dirk Pesch is a faculty member at the School of Computer Science and Information Technology , University College Cork. His research focuses on Internet of Things (IoT) , Cyber-Physical Systems , and Smart Manufacturing , with applications in Smart Communities , Health & Wellbeing , and Industrial Automation . As Director of the SFI Centre for Research Training in Advanced Networks for Sustainable Societies and Co-Principal Investigator of the CONNECT Centre , he leads large-scale research initiatives. He has secured over €80M in research funding and authored 250+ scientific publications. His leadership in the Cork Smart Gateway initiative and founding of the Nimbus Research Centre highlight his industry-focused impact. His recent work explores 5G/6G integration with Time-Sensitive Networking (TSN) , machine learning for loneliness detection , and interoperability solutions for IoT ecosystems . He contributes to international conferences as Technical Programme Co-Chair (IEEE SmartComp 2024) and General Chair (IEEE SmartComp 2025).

• Accelerator Physics
• Synchrotron Radiation
• Particle Beams
• +2 more

Mark Boland is Professor of Physics and Engineering Physics at the University of Saskatchewan, previously serving as Machine Director at the Canadian Light Source (2017-2024). He holds a PhD from the University of Melbourne and conducted postdoctoral research at Lund University. His career includes significant contributions to accelerator systems at the Australian Synchrotron. Research expertise includes: Ultra-low emittance electron beam measurement Synchrotron radiation instrumentation Particle accelerator design for future colliders Neural network applications in beam control Boland has published extensively on particle accelerator physics and synchrotron technology. He currently serves as Vice Chair of the American Physical Society's Division of Physics of Beams and chaired the International Particle Accelerator Conference in 2019.

• Analog Circuit Design
• RF Circuit Design
• mmWave Communication Systems
• +4 more

Georgios Panagopoulos is an Assistant Professor at the School of Electrical and Computer Engineering (ECE) of the National Technical University of Athens (NTUA). He earned his Diploma in Computer and Communication Engineering from the University of Thessaly in 2006 (with honors) and his Ph.D. in Electrical and Computer Engineering from Purdue University in 2012, focusing on variability and reliability modeling of CMOS and SPIN-based devices. His research spans analog, RF, and mmWave circuit design for communication systems, with expertise in wireless front-end modules, device characterization, variability modeling, and spin-based devices for machine learning. Recent work includes III-V material components, buried power rail applications, and tunable transmission lines. Key Trends: Advanced semiconductor structures, reliability in sub-terahertz communication, and co-design for energy-efficient RF systems. He has received awards including the Bakalas Scholarship and Technical Chamber of Greece Award. At NTUA, he teaches courses on VLSI design, analog circuits, and digital systems.

Michalas LoukasView profile

Research Fellow

• AI for Electronics
• RF MEMS Design
• Memristors
• +5 more

Michalas Loukas is a Research Fellow in the Department of Physics at the University of Crete. He holds a Ph.D. in Physics from the University of Athens (2009), and has held research positions including Senior Research Fellow at the Zepler Institute for Photonics and Nanoelectronics (2018–2019), Research Fellow at the University of Southampton (2016–2018), and Marie-Curie Fellow at IMM-CNR, Rome (2015). His work focuses on AI-driven micro/nano electronics, RF MEMS design, memristor characterization, and semiconductor materials. Education: 2009: Ph.D., Physics Department, University of Athens 2004: M.Sc., Physics Department, University of Athens 2002: B.Sc., Physics Department, University of Athens Research Interests: AI integration in manufacturing for Industry 5.0 and sustainability Predictive reliability analysis for high-power RF MEMS Electrical characterization of memristors and semiconductor interfaces Microwave microscopy for material property analysis Advising/Grants: Marie-Curie Fellowship (2015) Extensive collaboration with international institutes including the University of Southampton and IMM-CNR Labs/Teams: Zepler Institute for Photonics and Nanoelectronics (2018–2019) Electronics & Computer Science (ECS), University of Southampton (2016–2018)

• Retail Economics
• Labor Economics
• Game Theory
• +5 more

Zhen He is an Assistant Professor in the Department of Economics at McMaster University, where he focuses on retail economics, labor markets, and applied microeconomics. His interdisciplinary research bridges economic theory with advanced sensing technologies, particularly in human activity recognition and wearable devices. Key teaching areas: Intermediate Microeconomics, Public Sector Economics, Labour Economics Recent work explores sedentary behavior mapping in aging populations and acoustic sensing applications His scholarly output spans both traditional economic studies and cutting-edge technological implementations, suggesting a unique cross-disciplinary approach. While primarily affiliated with McMaster's Economics department, his research extends into domains like wireless sensing systems and edge computing analytics. Notable trends in his publications include: Acoustic sensing innovations on commodity hardware mmWave radar applications for health monitoring Behavioral pattern analysis in commercial environments