جستجوی استاد راهنمای دانشگاهی

• Wireless Communications
• 5G/6G Networks
• Massive MIMO
• +۶ مورد دیگر

Maged Elkashlan is a Professor in the Department of Electronic Engineering at Queen Mary University of London, UK. He specializes in wireless communications, with a focus on 5G/6G systems, massive MIMO, reconfigurable intelligent surfaces (RIS), and ultra-reliable low-latency communication (URLLC). His research spans physical layer security, energy-efficient networks, and non-orthogonal multiple access (NOMA). He has authored over 200 papers in top-tier journals and conferences and holds editorial roles in IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, and others. He has supervised numerous PhD students, including current scholars working on RIS and cell-free MIMO. His teaching includes courses on digital signal processing, communication theory, and wireless communications at Queen Mary, the University of Sydney, and the University of New South Wales. He has organized major symposiums at IEEE ICC and VTC, and his work has been recognized through best paper awards and industry collaborations. Editorships: IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Molecular, Biological and Multi-Scale Communications Key Research Areas: Cell-Free Massive MIMO, RIS-aided systems, NOMA, URLLC, physical layer security Recent Activities: Symposium co-chair for IEEE VTC 2018 and ICC 2018, guest editor of IEEE Communications Magazine special issues on millimeter-wave and green media Grants & Funding: China Scholarship Council (CSC) for PhD students, various research grants supporting RIS and URLLC projects

Ebroul Izquierdoمشاهده پروفایل

استاد

• Multimedia Signal Processing
• Machine Vision
• Image Processing
• +۷ مورد دیگر

Professor Ebroul Izquierdo holds a position at Queen Mary University of London's School of Electronic Engineering and Computer Science. His academic background includes a BSc, MSc, and PhD. He specializes in Multimedia Signal Processing, Machine Vision, and Mathematical models in image processing. His research focuses on video coding, computer vision, AI applications in agriculture, and security systems. He leads major grants such as the £305k Smart Farm project and the £370k SHIFT initiative. His work includes innovations in camera calibration for sports videos, self-supervised learning models, and federated learning architectures. He is affiliated with the Centre for Multimodal AI and collaborates with organizations like BBC and Innovate UK. His email is ebroul.izquierdo@qmul.ac.uk . Research Grants : Smart Farm and Agri-environmental Big Data Space (£305,116 EPSRC) SHIFT Project (£370,577 EPSRC) KTP: Machine Learning for Sport Broadcast Graphics (£214,061 Innovate UK) Labs & Teams : Centre for Multimodal AI, collaborating with BBC and EU Horizon 2020 initiatives.

Clive Pariniمشاهده پروفایل

استاد

• Microwave and Millimeter-Wave Antenna Measurements
• Compact Antenna Test Ranges
• Array Antenna Design
• +۵ مورد دیگر

Clive Parini is a Professor of Antenna Engineering at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science and leading the Antennas & Electromagnetics Research Group. He holds a BSc(Eng) and PhD from Queen Mary College, University of London. His career includes significant contributions to antenna design, measurement techniques, and metamaterials. He has authored over 300 papers and co-authored the book 'Principles of Planan Near-Field Antenna Measurements' (2008). His research focuses on microwave/millimeter-wave antennas, compact test ranges, array design, and body-centric communications. Prof. Parini has received notable awards, including the IEE Measurements Prize (1990) and BAE Systems Bronze Award (2002). He is a Fellow of the IET and Royal Academy of Engineering. His leadership roles include Director of Research for the School of Electronic Engineering & Computer Science and past Chair of the IET Antennas & Propagation Professional Network. Research highlights include metamaterials for antennas, on-body communication systems, and high-frequency imaging. His work bridges academic and industrial applications, with contributions to 5G, satellite antennas, and compact test range technologies. Recent articles emphasize advanced measurement techniques, compressive sensing, and drone-based systems for antenna testing. Teaching spans undergraduate and postgraduate levels, covering satellite systems, microwave electronics, and research techniques. His work integrates computational electromagnetics, antenna diagnostics, and emerging 5G/6G challenges, ensuring his research remains impactful across academia and industry.

Yi Maمشاهده پروفایل

استاد

• Semantic Communication
• Machine Learning for RF Design
• MIMO Technology
• +۶ مورد دیگر

Prof. Yi Ma is a Chair Professor at the Institute for Communication Systems (ICS) and the Home of the 6G Innovation Centre (6GIC) at the University of Surrey. He holds a Professorial rank in the School of Computer Science and Electronic Engineering. His research focuses on semantic/effective communication, machine learning for RF and physical layer design, MIMO technology, and opportunistic networking. Current PhD students include Yupeng Zheng, Ashkan Jafari, Zohre M. Bakhsh, and Mehdi Tafazolli. Research interests span scalable quantum-based wireless communications, distributed hybrid beamforming, and satellite communication systems. Recent publications highlight advancements in SA-MIMO, non-uniform quantization, and distributed MIMO-LEO networks. Prof. Ma teaches courses such as EEEM017 and EEE3006, and serves as an EEE examination officer. His work integrates theoretical contributions with practical applications, emphasizing future wireless systems and sensing technologies. Collaborations with industry and academia, including projects on 6G innovation, underscore his commitment to cutting-edge research.

Kimberly Brewerمشاهده پروفایل

دانشیار

• Molecular Imaging
• Cancer Immunotherapy
• MRI Cell Tracking
• +۲ مورد دیگر

Dr. Kimberly Brewer is an Associate Professor at Dalhousie University with joint appointments in the School of Biomedical Engineering, Department of Diagnostic Radiology, Department of Physics and Atmospheric Science, and Department of Microbiology & Immunology. She serves as the scientific lead of the Biomedical MRI Research Lab (BMRL), a core facility within the Biomedical Translational Imaging Centre (BIOTIC) located at the IWK Health Centre. Her research program focuses on molecular imaging technologies for therapeutic development, with particular emphasis on: Developing novel MRI/PET techniques for quantitative cell tracking Evaluating cancer immunotherapies in preclinical models Creating diagnostic and prognostic biomarkers for clinical translation Advancing multi-modality PET/MRI methodologies Current projects include MRI monitoring of immune cell populations in cancer immunotherapy, development of quantitative cell tracking algorithms, and preclinical applications of PET/MRI technology. Her recent publications (2017-2021) demonstrate strong focus on quantitative imaging techniques for therapeutic monitoring, particularly using MRI and PET to track immunotherapy responses, develop novel contrast agents, and optimize dosimetry for radioembolization therapies. Dr. Brewer actively seeks students interested in interdisciplinary research projects at the intersection of biomedical engineering, oncology, and medical physics.

• Materials Engineering
• Medical Physiology
• Sports Science and Exercise
• +۷ مورد دیگر

Dr. Braid Macrae is a Senior Research Fellow in the Department of Fashion & Textiles at RMIT University, specializing in advanced textile applications for extreme environments, biomedical engineering, and human physiological systems. His work integrates material science with clinical and aerospace applications, particularly focusing on compression garments, thermal regulation systems, and extravehicular activity (EVA) technologies for space exploration. Research interests include: Textile-based solutions for spaceflight (e.g., skinsuits, pressure garments) Thermal physiology and sensor technology validation Cerebrovascular autoregulation and cardiovascular dynamics Material properties of protective clothing for firefighting and occupational safety Notable contributions include developing mechanical-loading countermeasure skinsuits to mitigate post-spaceflight sensorimotor dysfunction and advancing methodologies for contact thermometry in clinical and environmental settings. His interdisciplinary approach bridges fashion design, biomedical engineering, and aerospace systems. Collaborations involve international teams in aerospace medicine, materials engineering, and physiology, with active participation in conferences such as the International Conference on Environmental Systems. Current research emphasizes optimizing wearable technology for extreme environments and translational applications in healthcare and space exploration.

Mitch Marcusمشاهده پروفایل

استاد

• Statistical natural language processing
• Cognitively plausible models
• Linguistic structure acquisition

Mitch Marcus is a Professor Emeritus in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science. He earned his Ph.D. from MIT in 1978 and joined Penn in 1987 after working at AT&T Bell Laboratories. His research focuses on statistical natural language processing and cognitively plausible models for automatic acquisition of linguistic structure. Dr. Marcus created and led the Penn Treebank Project, which revolutionized natural language parsing accuracy. He has served as PI on multiple major projects including DARPA LORELEI and GAILA AIX, focusing on unsupervised morphology acquisition and child language acquisition simulations. Awards: Fellow of American Association for Artificial Intelligence (1992) Founding Fellow of Association for Computational Linguistics (2011) Advising: His former PhD students hold positions at institutions including MIT, Johns Hopkins, Google, and Microsoft Research. Research groups: Directed the Penn Treebank Project and co-led the OntoNotes Project. Currently collaborates on natural language understanding for human-robot interaction.

• Synthetic Aperture Radar (SAR)
• Interferometric SAR (InSAR)
• Coherent Change Detection (CCD)
• +۱۱ مورد دیگر

Dr Daniel Andre is a Lecturer in Radar at Cranfield University, affiliated with the Centre for Electronic Warfare, Information and Cyber within the Cranfield Defence and Security school. He leads the Cranfield Ground-Based SAR Laboratory (GBSAR Lab), conducting cutting-edge research in Synthetic Aperture Radar (SAR), interferometry, and multistatic imaging. Education: PhD in Applied Mathematics Joint Honours BSc in Mathematics and Physics His research interests span Synthetic Aperture Radar (SAR) , Interferometric SAR (InSAR) , Coherent Change Detection (CCD) , Bistatic and Multistatic Radar , Through-Wall Imaging , Polarimetry , and Remote Sensing . His work integrates applied mathematics with radar phenomenology to solve complex defense and security challenges. The recent publications reveal a strong trend in experimental and computational SAR research, particularly in multistatic 3D imaging , polarimetric coherence analysis , near-field effects , and through-wall transmission modeling . His team leverages laboratory-based SAR systems to validate novel algorithms under controlled conditions. Scientific Awards: John Benjamin Memorial Prize (UK Civil Service Scientist Innovation Award, 2011) Simon Fellowship, Isaac Newton Institute for Mathematical Sciences (2023) Dr Andre actively supervises PhD students and secures funding for advanced radar research. He collaborates with key defense and research institutions including Dstl, ESA, BAE Systems, QinetiQ, ATI, and the Sir Bobby Charlton Foundation. His projects often involve experimental validation, algorithm development, and real-world applications in intelligence and surveillance. He heads the GBSAR Lab, a unique facility enabling precise control over SAR geometries for fundamental research in radar coherence, imaging, and change detection. The lab supports both academic inquiry and defense technology development.

Evelyn Otero Solaمشاهده پروفایل

دانشیار

• Sustainable Aviation
• Air Traffic Management
• Emissions Reduction
• +۵ مورد دیگر

Dr. Evelyn Otero Sola is an Associate Professor in Aeronautical Engineering at KTH Royal Institute of Technology, serving as Vice-Director of the Centre for Sustainable Aviation (CSA) and a member of the Executive Board of the Environmentally Compatible Air Transport System (ECATS) International Association. Her research focuses on sustainable aviation, particularly optimizing air traffic management (ATM) to reduce emissions (CO2 and non-CO2) and noise, with projects involving sustainable aviation fuels (SAF), hydrogen, AI, and drones. She leads the doctoral course FSD3831 Future Sustainable Aviation and the master’s course SD2830 Aircraft Performance and Air Traffic Management , emphasizing interdisciplinary approaches to sustainability. Key collaborations include the Swedish Aerospace Research Center (SARC) and initiatives like TREVOL, TRACE, CIDER, and KLIMAFLY. Her work bridges research, education, and industry to drive sustainable aviation solutions globally. Education details are not explicitly provided, but her academic contributions include over 15 publications since 2009, spanning CFD optimization, climate modeling, and aviation environmental impact. She advises 11 doctoral students in the first iteration of her course and plans to expand access internationally. Her initiatives aim to create a skilled workforce for sustainable aviation through holistic education and cross-sector networks.

Luc Florackمشاهده پروفایل

استاد

• Medical Imaging
• Differential Geometry
• MRI Techniques
• +۵ مورد دیگر

Luc Florack is a Full Professor in the Applied Differential Geometry group at Eindhoven University of Technology (TU/e). His research focuses on multiscale and differential geometric representations of medical imaging data, particularly in MRI techniques like diffusion and tagging MRI. He applies these methods to connectomics and myocardial function analysis. He holds an MSc in theoretical physics and a PhD in medical image analysis from Utrecht University. He has authored nearly 200 peer-reviewed papers and served on editorial boards and conference committees. His work includes developing the Sheet Probability Index (SPI) for white matter analysis and stability metrics for optic radiation tractography. Affiliations: EAISI, EAISI Health, Center for Analysis, Scientific Computing & Appl., Applied Differential Geometry Research interests include differential geometry applications to image analysis, tensor calculus, and partial differential equations. His recent work emphasizes clinical workflow integration of mathematical techniques. He has contributed to international conferences and holds roles in Dutch academic organizations like 3TU.AMI and NWO's Mathematics Advisory Board. Publications span neuroimaging, cardiovascular MRI, and tractography validation. His methods address challenges in quantifying brain sheet structures and improving surgical prediction accuracy.

Paul Hughesمشاهده پروفایل

پژوهشگر

• Magnetic Resonance Imaging (MRI)
• Pulmonary Physiology
• Lung Disease
• +۳ مورد دیگر

Dr. Paul Hughes is a Research Scientist & Project Manager in Magnetic Resonance Physics at the School of Medicine and Population Health , University of Sheffield. His work focuses on advanced MRI techniques for pulmonary disease assessment, particularly using hyperpolarized xenon-129 to study ventilation, perfusion, and gas exchange abnormalities in conditions like COPD , asthma , and Long-COVID . He collaborates on multicenter studies (e.g., C-MORE, EXPLAIN) and develops AI-driven segmentation tools for functional lung imaging. Radiation-Induced Lung Injury in oncology patients Chronic Thromboembolic Pulmonary Hypertension standardization Xenon-129 MRI for interstitial lung disease His contact details include: Paul.Hughes@sheffield.ac.uk , Polaris, 18 Claremont Crescent, Sheffield S10 2TA.

• Signal Processing
• Acoustic Sensor Networks
• Machine Learning
• +۳ مورد دیگر

Roberto Gil Pita is a Professor at the University of Alcalá (Spain), affiliated with the Department of Signal Theory and Communications. He leads the AES3 research group focusing on acoustic and electromagnetic smart sensor networks and signal processing applications. His doctoral work (2006) centered on radar target classification using statistical and AI methods under the supervision of Dr. Manuel Rosa Zurera. His research spans signal processing, machine learning, and their applications in aerospace, biomedical systems, and smart cities. Key areas include UAV detection, emotion recognition from speech, and acoustic localization using microphone arrays. His academic background includes a doctorate from the University of Alcalá and extensive contributions to wireless acoustic sensor networks, hearing aid signal processing, and bioimpedance spectroscopy. He has developed energy-efficient algorithms for real-time audio analysis, acoustic violence detection systems, and robust methods for speech enhancement in noisy environments. His work bridges theoretical signal processing with practical engineering solutions for defense, healthcare, and urban monitoring. Research interests extend to aeroelastic flutter analysis in aviation, wearable biomedical sensors for stress assessment, and data-driven approaches for sound environment classification. He has pioneered the use of deep learning in flutter testing and acoustic event classification, contributing to datasets like REALISED for benchmarking machine learning models. Notable projects include acoustic localization of drones using microphone arrays, real-time emotion detection systems, and collaborative research in smart healthcare technologies. His work emphasizes computational efficiency and energy conservation, particularly for embedded systems and battery-operated devices.

• VLSI Design
• Digital Circuit Testing
• Test Data Compression
• +۴ مورد دیگر

Χρ. Καβουσιανός is a Professor at the Department of Computer Engineering & Informatics, University of Patras (Polytechnic School). His research focuses on VLSI design, digital circuit testing, and test data compression. He holds a Diploma (1996) and PhD (2000) from the same department, with notable scholarships including the Maritsas Doctoral Scholarship (1999). Key roles include leading the Heraclitus II and Pythagoras II research programs as principal investigator. Collaborations include Duke University (USA) with Prof. Krishnendu Chakrabarty. Research highlights: Pioneered techniques in scan-based testing, test set embedding, and low-power testing. Over 45 publications in top journals/conferences (e.g., IEEE TCAD, DAC). Notable work includes defect-oriented testing methods and Huffman-based compression schemes. Has supervised 9 advisees across doctoral/postgraduate levels. Holds a 2010 US patent application on power switch design.

Marc CASTELLAمشاهده پروفایل

مدرس

• Signal Processing
• Blind Source Separation
• Neural Networks
• +۳ مورد دیگر

Prof. Marc CASTELLA is a Lecturer at Telecom SudParis, part of the SOP (Signal and Optimization Processing) unit. His research focuses on signal processing, particularly in blind source separation, nonlinear reconstruction, and optimization techniques. He has extensively contributed to areas such as sparse signal recovery, neural networks, and tensor decomposition. His work often addresses challenges in noisy environments and nonlinear systems. Recent publications include advancements in clipped signal recovery, motor torque estimation, and global optimization methods. Though no specific awards are listed, his prolific publication record reflects his impactful contributions to signal processing and applied mathematics. He collaborates with researchers like Jean-Christophe Pesquet and Arthur Marmin on projects involving polynomial systems and neural network models. His work is applied in diverse fields from industrial electronics to data analysis.

Stefano FORTUNATIمشاهده پروفایل

استادیار

• Signal Processing
• Radar Systems
• Machine Learning
• +۴ مورد دیگر

Stefano Fortunati is an Assistant Professor at Telecom SudParis within the ISTeC research centre. His work focuses on advanced signal processing, radar systems, and machine learning applications in communication and sensing. He has contributed to robust statistical methods, MIMO radar technologies, and environmental monitoring using underwater gliders. His research interests include semiparametric estimation, reinforcement learning for cognitive systems, and performance bounds in parametric models. Notable contributions address elliptical distributions, target detection in dynamic environments, and distributed sensor networks. Recent work explores integrated sensing and communication (ISAC) systems, massive MIMO radar architectures, and anomaly detection algorithms. He has published extensively on topics such as compressed sensing applications and sensor calibration in airborne systems.