جست‌وجوی استاد و پژوهشگر

Matthew O'Tooleمشاهده پروفایل

دانشیار

• Computer Graphics
• Robotics
• Computer Vision
• +۵ مورد دیگر

Matthew O'Toole is an Associate Professor at Carnegie Mellon University's School of Computer Science, holding joint appointments in the Robotics Institute and Computer Science Department. His research focuses on computational imaging, integrating optics, electronics, and computational processing to innovate visual information capture and display. Education: PhD (Computer Science, University of Toronto, 2016), MSc (2009), BSc (Honors Computer Science and Mathematics, University of British Columbia, 2007). Prior roles include Banting Postdoctoral Fellow at Stanford University and visiting scholar at MIT Media Lab's Camera Culture group. Research interests emphasize programmable imaging systems, transient imaging, non-line-of-sight sensing, and holographic displays. Key innovations include vibration sensing via dual-shutter optics and radar super-resolution for autonomous vehicles. Awards include runner-up best paper recognitions at ICCV 2007, CVPR 2014, and SIGGRAPH 2017 dissertation honors. Advisees include Dorian Chan and Arjun Teh. Grants supported by Canadian Banting Fellowships. Active in workshop organization (CVPR Computational Cameras 2016-2017) and course development on computational imaging at SIGGRAPH 2014. Labs/Teams: Leads research in computational imaging and robotics at CMU, collaborating with industry partners like NVIDIA and MDA. Current projects explore LiDAR-radar fusion, holographic projection systems, and dynamic scene reconstruction.

• Radar Remote Sensing
• Synthetic Aperture Radar (SAR)
• Forest Biomass Mapping
• +۳ مورد دیگر

Lars Ulander is a Professor at Chalmers University of Technology specializing in radar remote sensing. His research focuses on synthetic aperture radar (SAR) signal processing, particularly for applications in forest biomass mapping and ground imaging using VHF/UHF-band systems. He is a key proposer for ESA's BIOMASS satellite mission (launching 2025) and leads the BorealScat project, utilizing a 50-meter tower-based tomographic radar to study boreal forest dynamics. His work spans radar system development, SAR tomography techniques, and environmental monitoring of forests and sea surface currents. Current research areas include vegetation water content estimation, bistatic radar configurations, and optimization of SAR data processing algorithms for multi-temporal analysis. Recent publications demonstrate expertise in P-band/L-band SAR for biomass retrieval, passive radar systems, and interferometric techniques. His articles investigate radar backscatter sensitivity to forest structure, moisture parameters, and seasonal changes, while contributing to mission design frameworks like SLAINTE and SESAME.

Aurora Maccaroneمشاهده پروفایل

پژوهشگر ارشد

• Single-Photon Imaging
• Underwater LiDAR
• Quantum Sensing
• +۴ مورد دیگر

Aurora Maccarone serves as an RAEng Research Fellow within the Institute of Photonics and Quantum Sciences at Heriot-Watt University's School of Engineering & Physical Sciences. Her work focuses on advanced photonics applications for challenging environments, particularly underwater and obscured conditions. Her research expertise spans: Single-photon LiDAR systems for underwater 3D imaging Photon-counting detector arrays for depth profiling Real-time reconstruction algorithms for obscurant-penetrating imaging Quantum sensing applications in marine environments Recent publications demonstrate consistent innovation in single-photon imaging techniques, with emphasis on underwater applications (2023-2024) and obscurant penetration (2022). Her work shows strong interdisciplinary connections between optical engineering, computational imaging, and environmental sensing. Key publications reveal growing impact in underwater LiDAR technology, with multiple high-citation papers on photon-efficient imaging systems. Dr. Maccarone actively supervises PhD students and has created significant research datasets. Her collaborations span international institutions, with notable contributions to sensor hardware development and computational imaging algorithms. Recent work shows increasing integration of machine learning techniques with traditional photon-counting approaches.

Cathryn Mitchellمشاهده پروفایل

استاد

• Radio Science
• Space Weather
• Position, Navigation and Timing (PNT)
• +۴ مورد دیگر

Cathryn Mitchell is a Professor of Radio Science and Royal Society Industry Fellow at the University of Bath, specializing in ionospheric physics, position, navigation, and timing (PNT). She leads research in the Space & Telecoms Research Group (STAR), focusing on radio propagation, data assimilation, and space weather impacts on communication systems. Her work bridges theoretical, computational, and experimental approaches, with applications in satellite navigation, climate monitoring, and defense sectors. Her research interests include ionospheric tomography, HF communications, and the development of robust PNT systems. Mitchell collaborates extensively with industry partners like Spirent Communications on future navigation technologies and space weather resilience. She has held roles such as Academic Director of the Doctoral College and contributes to interdisciplinary projects like the DRIIVE initiative exploring ionospheric variability with EISCAT-3D radar. Recent work emphasizes ionospheric effects during geomagnetic storms (e.g., the 2024 Gannon Storm) and cooperative autonomous systems under communication constraints. Her projects are funded by the Royal Society, Natural Environment Research Council (NERC), and ESA, addressing challenges in space weather forecasting and PNT system reliability. Awards: Royal Society Industry Fellow (2022–present) Key Projects: Royal Society Industry Fellowship on Future PNT Technologies DRIVERS (DRIIVE): Ionospheric Variability Studies EISCAT-3D FINESSE: Ionospheric Structuring Analysis Mitchell’s lab, STAR, integrates academic and industrial partnerships to advance space weather applications and sustainable navigation systems, contributing to UN Sustainable Development Goals related to climate action and innovation.

Kamal Sarabandiمشاهده پروفایل

استاد

• Applied Electromagnetics
• Radar Remote Sensing
• Antenna Design
• +۶ مورد دیگر

Kamal Sarabandi is the Rufus S. Teesdale and Fawwaz T. Ulaby Distinguished University Professor of Electrical Engineering and Computer Science at the University of Michigan. He leads the Radiation Laboratory, renowned for research in applied electromagnetics, radar remote sensing, and antenna technology. His academic rank is Professor, and he holds affiliations with the College of Engineering. His research spans radar systems for environmental monitoring (e.g., soil moisture, snowpack), automotive radar for autonomous vehicles, metamaterials for antenna miniaturization, and security applications like concealed weapons detection. He has advised over 60 PhD students, many of whom hold academic or industry leadership roles globally. Awards and Recognition: National Academy of Engineering member, IEEE Picard Medal, Humboldt Award, Ellis Island Medal of Honor, and Stephen S. Attwood Award. His work bridges fundamental science with practical innovations, including NASA collaborations and military/defense applications. Labs and Teams: Directs the Radiation Laboratory, a hub for applied electromagnetics and radar innovation. Collaborates with industry (e.g., Qualcomm, SAIC) and government agencies (NASA, Army Research Lab) on projects like the COMBAT center for autonomous systems. Education: Earned his PhD in Electrical Engineering from the University of Michigan (1989). Alumni of his lab include professors at UW-Madison, Purdue, and international institutions.

• Wireless Communications
• Optical Communications
• Radar Signal Processing
• +۶ مورد دیگر

Saleh A. Alshebeili is a Professor in the Department of Electrical Engineering at King Saud University's College of Engineering, Riyadh, Saudi Arabia. With over 139 publications spanning from 1991 to 2024, his research demonstrates significant contributions across multiple engineering disciplines. His academic profile shows consistent collaboration with Saudi research institutions and international partners, particularly in communications and signal processing fields. Dr. Alshebeili's research interests span wireless communications, optical networks, radar systems, and biomedical signal processing. His work bridges theoretical signal processing with practical applications in 5G/6G communications, IoT security systems, and healthcare monitoring. The interdisciplinary nature of his research connects electrical engineering with computer science, particularly through machine learning applications for signal analysis and system optimization. His publications demonstrate expertise in both traditional signal processing techniques and emerging AI-driven approaches to engineering problems. Analysis of his recent publications (2021-2024) reveals a strong focus on next-generation communication technologies including 6G systems, optical wavelength conversion, and OAM-SDM communication. Simultaneously, he maintains active research in biomedical applications, particularly EEG signal processing for seizure detection and biometric authentication using physiological signals. His work consistently appears in top IEEE journals including IEEE Access, IEEE Transactions on Wireless Communications, and IEEE Journal of Biomedical and Health Informatics, reflecting the high quality and relevance of his research. Dr. Alshebeili has established extensive collaborations with researchers across King Saud University, particularly with Fathi E. Abd El-Samie (29 co-authored papers), Turky N. Alotaiby (22 papers), and Amr Ragheb (21 papers). These long-term collaborations suggest leadership in research groups focusing on communications systems and biomedical signal processing. His work spans theoretical development, simulation, and experimental validation, as evidenced by publications with 'Experimental Investigation' and 'Experimental Demonstration' in their titles.

• Information Theory
• Wireless Communications
• Signal Processing
• +۳ مورد دیگر

Prof. Slawomir Stanczak is a Full Professor in Network Information Theory at Technische Universität Berlin and Head of the Wireless Communications and Networks department at Fraunhofer Heinrich-Hertz-Institut (HHI). His expertise spans wireless communications, signal processing, and machine learning, with a focus on 5G/6G networks and reconfigurable intelligent surfaces. He has held visiting roles at RWTH Aachen University and Stanford University, and leads initiatives like the 6G Research & Innovation Cluster and the xG-Incubator project. Education: Dipl.-Ing. in Electrical Engineering, TU Berlin (1998) Dr.-Ing. (summa cum laude), TU Berlin (2003) Habilitation (venia legendi), TU Berlin (2006) Research & Awards: Recipient of the Best Paper Award from the German Communication Engineering Society (2014) Research grants from the German Research Foundation Co-authored over 200 peer-reviewed papers and two books Chair of the ITU-T Focus Group on Machine Learning for Future Networks (2017-2020) Leadership & Projects: Chairman of 5G Berlin association since 2020 Coordinator of 6G Research & Innovation Cluster and CampusOS flagship project Project lead of xG-Incubator (StartUpConnect initiative) Teaching: Offers courses on Machine Learning and Wireless Communication at TU Berlin.

• Compact and reconfigurable antennas
• Antenna arrays
• Microwave components
• +۷ مورد دیگر

Dimitrios E. Anagnostou is Associate Professor in the Institute of Sensors, Signals & Systems within Heriot-Watt University’s School of Engineering & Physical Sciences, Edinburgh. He directs an anechoic-chamber & microwave characterisation facility, leads a thriving research group, and is currently recruiting PhD candidates. Education & Career: BSEE, Democritus University of Thrace, Greece (2000) MSEE, University of New Mexico, USA (2002) PhD, University of New Mexico, USA (2005) Post-doc, Georgia Tech (2005-2006) Assistant → tenured Associate Professor, South Dakota School of Mines & Technology (2007-2016) Associate Professor, Heriot-Watt University (2016-present) Research Focus: His work spans compact & reconfigurable antennas, 5G Massive-MIMO arrays, metasurfaces, metamaterials, functional materials (VO 2 ), RF-MEMS, microwave packaging, radar sensing for assisted-living, and AI/deep-learning applications in electromagnetics. He pursues “green” RF electronics printed on paper/organic substrates and hybrid integration of antennas on solar cells. Recent Publication Trends (2022-2025): Output is dominated by metasurface-enabled beam-steering antennas, VO 2 -based reconfigurable devices, radar absorbers/rasorbers, biomedical radar for vital-sign monitoring, and AI-assisted signal processing, with strong emphasis on experimental validation and open-access dissemination. Scientific Awards & Fellowships: IEEE John D. Kraus Antenna Award DARPA Young Faculty Award Marie Skłodowska-Curie Individual Fellowship (H2020) ASEE Campus Star Award Young Alumni Award, University of New Mexico Honored Faculty Award, SDSMT (×4) Distinguished Scientist Living Abroad, Hellenic Ministry of Defense Advising & Grants: He has mentored numerous PhD and MSc researchers; his students have won Best PhD Thesis and faculty-wide Engineering Prizes. He is supported by EU and UK research grants and continuously seeks motivated doctoral applicants. Facilities & Teams: He manages the Microwave Facility (anechoic chamber, mm-wave measurement systems) and collaborates with international academic/industry partners across Europe, North America and beyond.

Vivek Boominathanمشاهده پروفایل

استاد پژوهشی

• Computational imaging
• Computer vision
• Machine learning
• +۷ مورد دیگر

Vivek Boominathan is an Assistant Research Professor in the Department of Electrical and Computer Engineering at Rice University. He is affiliated with the GLEE lab (Geometry, Light, & Imaging lab). His research focuses on computational imaging, combining computer vision, machine learning, applied optics, and nanofabrication to develop innovative imaging systems for applications such as robotics, medical sensing, and virtual/augmented reality. He has contributed to projects like PhlatCam (a lensless camera) and NeuWS (neural wavefront shaping). His work bridges optics, algorithms, and materials science to overcome traditional limitations in imaging systems. Boominathan's research interests include lensless imaging, optical meta-devices, turbulence mitigation, and bio-inspired imaging systems. He has developed systems like Foveated thermal imaging prototypes and real-time lensless microscopes. His lab emphasizes interdisciplinary approaches, integrating hardware design with machine learning. Key projects include: NeuWS: Neural wavefront shaping for imaging through scattering media CoIR: Compressive implicit radar for sensing applications FlatCam and PhlatCam: Ultra-thin lensless imaging devices Bioluminescence imaging in marine species His work has been published in top venues like Science Advances, Optica, and IEEE TPAMI. He collaborates with institutions like NASA JPL and industry partners on applied imaging solutions. Current research trends emphasize sensor-algorithm co-design and high-speed imaging systems for AR/VR applications. Boominathan holds a PhD in Electrical Engineering and has extensive postdoctoral experience in computational imaging. He advises projects in the GLEE lab and mentors students in hardware-software co-design for imaging systems. His lab focuses on translating theoretical innovations into practical devices with commercial potential.

• Antenna Measurement
• Electromagnetic Field Theory
• Near-Field to Far-Field Transformation
• +۵ مورد دیگر

Dr. Alexander Paulus serves as a Researcher at the Chair of High-Frequency Engineering within the Department of Electrical Engineering at the Technical University of Munich (TUM), School of Computation, Information and Technology. Working under Prof. Dr.-Ing. Thomas Eibert, he contributes to advanced electromagnetic research and measurement systems development at TUM's Arcisstr. 21 campus in Munich. Research Expertise His core specialization lies in near-field antenna measurement and transformation techniques, with significant contributions to phase retrieval algorithms, inverse source methods, and UAV-based electromagnetic field measurements. He addresses critical challenges including probe correction with unknown antennas, sparse sampling for directive antennas, and electromagnetic modeling of environmental effects like rain attenuation. His work bridges theoretical electromagnetics with practical antenna characterization solutions. Publication Trends From 2014-2025, Paulus has published 25+ papers focusing on near-field to far-field transformations, particularly in phaseless and multi-probe scenarios. Recent work (2023-2025) demonstrates innovation in spectral filtering, sparse reconstruction, and UAV-based systems for defect localization and wet antenna modeling. His research increasingly integrates computational techniques to solve complex inverse problems in antenna measurements. Scientific Recognition No formal awards documented in available information Academic Contributions Student Mentoring: No advisees listed in provided materials Research Funding: Grant details not specified in source text Research Environment Paulus operates within TUM's Chair of High-Frequency Engineering facilities, which include advanced near-field measurement ranges, UAV-based electromagnetic characterization systems, and laboratories for metamaterials research and electromagnetic compatibility testing. His work supports applications in 5G/6G communications, aviation navigation systems, and precision antenna diagnostics.

Ali Yaparمشاهده پروفایل

استاد

• Electromagnetics
• Microwave Engineering
• Antenna Technologies
• +۳ مورد دیگر

Professor Ali Yapar is a faculty member at Istanbul Technical University in the Electronics and Communication Engineering department. His research focuses on Electromagnetics , Microwave Engineering , and Antenna Technologies , with a particular emphasis on inverse scattering problems and microwave imaging for biomedical applications. He has supervised numerous graduate students and led projects related to breast cancer treatment and rough surface imaging. PhD in Electronics and Communication Engineering from Istanbul Technical University (1997) MSc in Electronics and Communication Engineering (1995) His recent publications analyze advanced techniques for microwave hyperthermia systems, reverse time migration methods, and Newton-based solutions for electromagnetic inverse scattering. Key projects include TUBITAK-funded initiatives on microwave tomography and brain stroke imaging. He serves as a project investigator and executive for electromagnetic research programs. Research areas span Electromagnetic Wave Propagation , Green's Function Applications , and Dielectric Material Analysis . Collaborations include IEEE members and international researchers in computational electromagnetics.

Tim Weyrichمشاهده پروفایل

استاد

• Visual Computing
• Computer Graphics
• Cultural Heritage Analysis
• +۵ مورد دیگر

Tim Weyrich is Professor of Visual Computing (part-time) at University College London and Professor of Digital Reality at Friedrich-Alexander University Erlangen-Nürnberg. He leads the Digital Reality Lab and has affiliations with the Virtual Environments and Computer Graphics group at UCL, Eurographics, and the EPSRC Doctoral Training Centre (SEAHA). Previously, he held a Postdoctoral Teaching Fellowship at Princeton University. Research Interests: Content creation and computational photography Appearance modeling and fabrication Point-based graphics and cultural heritage analysis Digital humanities and 3D printing Article Trends: Recent work focuses on neural radiance fields (FruitNeRF++), 3D Gaussian splatting, mmWave radar inverse rendering, and texture anomaly detection. Applications span autonomous systems, cultural heritage, and medical imaging. Scientific Awards: Best Paper Honourable Mention (BMVC 2022) Best Student Paper Award (EG Workshop on GCH 2014) Honorable Mention (Eurographics 2011) Best Student Paper Honourable Mention (BMVC 2018) ACM SIGCHI Best Paper Honourable Mention (CHI 2013)

• Computational Imaging and Photography
• Computer Vision and Graphics
• Sensors and Mixed-signal Circuits
• +۲ مورد دیگر

Suren Jayasuriya is an Associate Professor at Arizona State University's The GAME School, with joint appointments in the School of Electrical, Computer and Energy Engineering (ECEE) and the Department of Arts, Media and Engineering (AME). He is also an Affiliate Faculty Member at the Mary Lou Fulton College for Teaching and Learning Innovation. His lab, the Imaging Lyceum, focuses on transdisciplinary research bridging computational imaging, computer vision, sensors, and STEAM education. Education Ph.D. Electrical and Computer Engineering, Cornell University (2017) M.S. Electrical and Computer Engineering, Cornell University (2015) B.S. Mathematics, University of Pittsburgh (2012) B.A. Philosophy, University of Pittsburgh (2012) Research Focus Dr. Jayasuriya's work integrates optics, computational photography, and machine learning to develop novel imaging systems. His research spans: Computational cameras and light transport analysis Atmospheric turbulence modeling and video restoration Neural volumetric reconstruction for sonar/radar STEAM education frameworks for K-12 teachers Philosophical aspects of imaging and representation His lab emphasizes interdisciplinary collaboration across engineering, arts, and humanities. Publication Trends Recent publications demonstrate strong focus on computational imaging (45%), AI/ML applications (30%), and educational technology (25%). Dominant themes include turbulence mitigation in videos, neural rendering for sonar/radar, sensor fusion, and AI curriculum development for middle schools. Work frequently appears in top venues like CVPR, SIGGRAPH, and IEEE Transactions. Awards Image Electronics Technology Excellence Award (IIEEJ, 2021) Best Demo Awards: IEEE ICCP 2019, MIRU 2018 Best Paper Award: IEEE ICCP 2014 ASEE Diversity Paper Finalist (2020) Teaching Honors: Fulton Top 5% Award (2019, 2021), ASU Game Changing Faculty (2021) Teaching & Advising Teaches graduate/undergraduate courses including Machine Vision (EEE 515), Minds and Machines (AME 400), and thesis supervision. Leads NSF-funded projects on computational imaging education and AI teacher training. Mentors students through the Imaging Lyceum lab with projects spanning optics, philosophy, and educational technology. Lab & Collaborations Directs the Imaging Lyceum, emphasizing Aristotle-inspired collaborative research. The lab works on: computational cameras, STEAM education, sensor development, and philosophical inquiries into imaging. Collaborates with Carnegie Mellon Robotics Institute and international partners. Funded by NSF, NEH, and industrial partners for projects in sonar imaging, heat resiliency sensing, and educational AI.

Irena Hajnsekمشاهده پروفایل

استاد

• Satellite Radar Data
• Electromagnetic Wave Propagation
• Radar Polarimetry
• +۳ مورد دیگر

Prof. Dr. Irena Hajnsek is a Full Professor at the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich. She heads the Polarimetric SAR Interferometry research group at the German Aerospace Center (DLR) and serves as Scientific Coordinator for the TanDEM-X satellite mission. Her work focuses on electromagnetic wave propagation, radar polarimetry, and SAR data processing for environmental monitoring. IEEE Fellow (2014) DLR Science Award (2014) Multiple Best Paper Awards (VDE EUSAR, IEEE GRSS) Co-chair IEEE IGARSS Technical Program (2012, 2019) Founder IEEE GRSS REACT Technical Committee (2021) Her research spans geophysical parameter estimation from SAR data, with applications in soil moisture monitoring, glacier ice analysis, and agricultural crop mapping. She serves as Associate Editor for the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Tayfun Günelمشاهده پروفایل

استاد

• Microwave Circuits
• Radar Systems
• Antennas
• +۱۲ مورد دیگر

Tayfun Günel is a Professor in the Department of Electronics and Communication Engineering at Istanbul Technical University (ITU) , Faculty of Electrical and Electronics Engineering. He holds a PhD (1993), MSc (1988), and BSc (1986), all from ITU. His research spans microwave circuits, radar systems, antennas, and optimization using genetic algorithms and soft computing. His research interests include Microwave Circuits , Radar and Antennas , Optimization , and Genetic Algorithms . His work focuses on impedance matching, microstrip antennas, noise modeling, and metamaterial-based microwave components. He has taught courses such as Electromagnetic Fields, Radar Systems, and Satellite Communication Systems. The recent publications reflect a strong trend in microwave circuit design , antenna miniaturization , and the application of evolutionary algorithms (genetic algorithms, PSO) and machine learning (neural networks, SVR) in electromagnetic design and optimization. There is a consistent focus on practical microwave components like transmission lines, patches, and amplifiers, often using nanomaterials (e.g., carbon nanotubes) and metamaterials . His work bridges theoretical modeling with computational optimization for real-world RF and radar applications. Email: gunelmur@itu.edu.tr Professor Günel has supervised 2 completed PhD theses, 2 ongoing PhD theses, 23 completed master's theses, and 1 ongoing master's thesis, demonstrating a significant contribution to student mentoring. There are no specific grants or funding sources mentioned in the provided text. He is affiliated with research in microwave systems and antenna design , likely operating within the broader research ecosystem of the Electronics and Communication Engineering Department at ITU, which includes labs such as the Microwave Systems and Antennas Laboratory and the Radar and Microwave Technologies Research Laboratory.