جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Dynamical Systems
• Control Systems
• +۴ مورد دیگر

Priyabrata Saha is a Research Fellow at the Georgia Institute of Technology, affiliated with the College of Engineering and the Department of Electrical and Computer Engineering. Research interests include: Deep learning applications in ocean acoustics Control systems for autonomous vehicles Reduced-order modeling of partial differential equations Robust perception in autonomous systems Spatiotemporal dynamics prediction His work spans interdisciplinary domains, combining machine learning with physical modeling for applications in oceanography , robotics , and sensor systems . Key trends in his publications highlight: Integration of physics-based models with generative deep learning Real-time control algorithms for multi-agent systems Resource-efficient architectures for autonomous perception Hybrid methods in dynamical system modeling

• Cognitive Psychology
• Embodied Cognition
• Legal Concepts
• +۳ مورد دیگر

Luisa Lugli is a Full Professor in the Department of Philosophy at the University of Bologna. Her research focuses on embodied cognition, legal and institutional concepts, perception, and social psychology. She explores how abstract concepts are shaped by cultural, sensory, and motor experiences, with particular attention to gender representation, gesture influence, and spatial-numerical associations. Research Interests : Embodied Cognition Legal Conceptualization Sensory-Motor Interaction Cross-Cultural Semantics Gestural Effects in Cognition Attention and Perception Her recent work examines how manual gestures influence random number generation, the role of sound in speed perception, and cultural variability in gender conceptualization. She has contributed to advancing methodologies in online experimental psychology, particularly during pandemic constraints. No scientific awards are explicitly listed, though her extensive publication record highlights significant contributions to cognitive and legal psychology. Advising & Grants : No advisees or grants explicitly mentioned. Collaborations focus on interdisciplinary teams in cognitive science and legal studies. Labs/Teams : Engaged in experimental psychology and legal jurisprudence research groups at the University of Bologna.

• Cognitive Modelling
• Artificial Intelligence
• Decision-Making
• +۳ مورد دیگر

Dr. Leendert van Maanen is an Associate Professor at the Department of Experimental Psychology, Utrecht University, where he studies cognitive mechanisms underlying information processing and decision-making. His research focuses on developing and validating computational cognitive models, with applications in human-machine interaction and cognitive neuroscience data analysis. Research Themes: Cognitive Modeling, Decision-Making, Human-Centered Artificial Intelligence, Applied Data Science Labs: Leads the COBRA (Cognitive and Behavioral Research in Artificial Intelligence) lab His work spans three levels of cognitive integration in AI: model development, human-machine deployment, and neural data analysis. Recent projects include cognitive strategy detection, digital twin user modeling, and neural event detection using multivariate time series. For collaborations and publications, see leendertvanmaanen.com or Utrecht University Research Portal.

• Wave Physics
• Ultrasonic Imaging
• Optical Microscopy
• +۴ مورد دیگر

Alexandre Aubry is a Research Director at CNRS affiliated with the Institut Langevin in Paris. His work focuses on imaging through complex media using wave physics principles, with applications in ultrasonic imaging, optical microscopy, seismic imaging, and radar technology . He leads projects supported by the ERC Consolidator Grant REMINISCENCE and ANR COPPOLA , and has co-founded the biomedical imaging company OWLO . Education: Habilitation à Diriger des Recherches, Université Paris Sciences & Lettres (2022) Post-Doc under John Pendry, Imperial College London (2008-2010) PhD under Arnaud Derode, Université Pierre et Marie Curie (2008) Engineer's Degree, ESPCI ParisTech (2005) Research Highlights: He developed 3D ultrasound matrix imaging to overcome wavefront distortions in biomedical applications, and pioneered passive seismic matrix imaging for volcanic structure mapping. His theoretical contributions include distortion matrix formalism for aberration correction and multiple scattering analysis in heterogeneous media. Scientific Awards: ERC Consolidator Grant REMINISCENCE ANR COPPOLA grant Research Team: Currently supervising 9 active PhD students and 5 postdoctoral researchers , with a track record of mentoring 12 former team members including prominent researchers like François Legrand and Laura Cobus.

• Medical Imaging
• Ultrasound Tomography
• Image Registration
• +۴ مورد دیگر

Torsten Hopp is a Research Associate at the Institute for Data Processing and Electronics (IPE) at Karlsruhe Institute of Technology (KIT). His work focuses on advanced medical imaging technologies, particularly 3D ultrasound computer tomography (USCT) and its integration with MRI and X-ray modalities for breast cancer diagnosis. Research Interests: Ultrasound tomography system development Image registration algorithms Machine learning applications in medical imaging Biomechanical and computational modeling GPU-accelerated image reconstruction Multimodal imaging for clinical workflows Publication Trends: Torsten Hopp has contributed extensively to the evolution of 3D USCT, with recent work emphasizing deep learning integration , refraction correction , and patient-specific modeling . His research bridges hardware innovation (e.g., PtQube device) with computational methods for clinical translation. Labs & Teams: Affiliated with KIT's Institute for Data Processing and Electronics , he collaborates on projects like the High Data Rate Processing and Analysis Initiative , advancing ultrasound tomography for breast cancer screening.

• Engineering Acoustics
• Acoustic Measurement
• Communication Acoustics
• +۴ مورد دیگر

Yasuhiro Oikawa is a Professor at the School of Fundamental Science and Engineering, Faculty of Science and Engineering, Waseda University. He holds a Doctor of Engineering degree from Waseda University and has been actively contributing to acoustics, signal processing, and optical measurement techniques. His research spans Sound field visualization using parallel phase-shifting interferometry Phase-aware audio signal processing algorithms Acoustic calibration and microphone sensitivity analysis Real-time sound event localization systems His recent publications focus on advanced time-frequency analysis, optical methods for sound measurement, and deep learning applications in acoustics. Key trends include Improving resolution in spectrogram-based signal processing Integration of physical models with neural networks Development of wearable acoustic sensor arrays Scientific awards recognizing his work include The Fumio Okano Best 3D Paper Awards CSS2018 Best Paper Award Acoustical Society of Japan Contribution Award Institute of Electronics, Information and Communication Engineers Human Communication Award He has served as a committee member for the Acoustical Society of Japan and is affiliated with organizations such as ACM, IEEE, and Acoustical Society of America. His research has been supported by collaborations with institutions like Technical University of Denmark and applications in robotics, museum exhibits, and consumer electronics.

• Extractive Metallurgy
• Green Steel Technology
• Hydrogen Ironmaking
• +۸ مورد دیگر

Dr. Shabnam Sabah is a Postdoctoral Research Engineer at Swinburne University of Technology, affiliated with the School of Engineering and actively contributing to the Green Steel Alliance and HILT CRC projects. Her research is centered on hydrogen-based iron and steel production, with a strong focus on sustainable and decarbonized metallurgical processes. Research Interests: Her work spans green steel technology , hydrogen ironmaking , flash smelting , extractive metallurgy , and high-temperature process modeling . She investigates techno-economic feasibility, energy efficiency, and emissions reduction in next-generation steelmaking pathways. Her recent publications demonstrate a strong trend toward hydrogen-based direct reduced iron (H2-DRI) , flash reduction processes , and low-grade ore utilization , with increasing emphasis on modeling, pilot testing, and sustainability metrics. She has published extensively in journals such as Metallurgical and Materials Transactions B , Ironmaking & Steelmaking , and Cell Reports Sustainability . Scientific Contributions: Developed models for H2-DRI shaft furnaces and flash reactors. Conducted techno-economic assessments of green steel pathways. Pioneered cold modeling studies on splashing in oxygen steelmaking. Explored CO2 emissions linked to gangue content in decarbonized routes. Advising and Grants: She is available to supervise PhD students and has been involved in major CRC-funded projects such as HILT, focusing on hydrogen integration in ironmaking. Her work bridges experimental research, process simulation, and industrial applicability. Labs and Teams: She is part of the Green Steel Alliance at Swinburne, collaborating with experts like Prof. Geoffrey Brooks and Dr. M Akbar Rhamdhani. Her research leverages advanced modeling tools (Aspen Plus, HSC Chemistry) and experimental cold models to validate industrial-scale processes.

Guillaume Renaudمشاهده پروفایل

استادیار

• Ultrasound Physics
• Acoustical Physics
• Nonlinear Ultrasound Propagation
• +۶ مورد دیگر

Guillaume Renaud serves as Assistant Professor in the Imaging Physics department at Delft University of Technology's Faculty of Applied Sciences. He simultaneously holds a tenured position as CNRS scientist at Laboratoire d'Imagerie Biomédicale in France since 2014, and has been an invited scientist at TU Delft since 2020. His academic credentials include: PhD from Université de Tours, France (2005-2008) M.Sc. in Acoustics from Université du Maine, France (2004-2005) Engineering degree from ICAM (graduate school), France (1999-2004) Dr. Renaud's research centers on ultrasound and acoustical physics , specializing in nonlinear ultrasound propagation, ultrasound imaging techniques, and tissue characterization. His work bridges fundamental physics with clinical applications, particularly in bone ultrasound physics and blood flow quantification. He has developed innovative approaches for ultrasound image reconstruction and artifact correction in heterogeneous tissues, addressing critical limitations in conventional ultrasound techniques for bone and complex biological media. His recent publications demonstrate a clear trajectory toward solving practical clinical challenges through advanced ultrasound methodologies. His work increasingly integrates multimodal approaches, combining photoacoustics with traditional ultrasound techniques to enhance blood flow measurement and bone imaging capabilities. The research shows particular emphasis on accurate bone thickness measurement, blood flow quantification in microfluidic environments, and correction of image degradation in complex biological tissues. At TU Delft, Dr. Renaud teaches Electromagnetism and Acoustical Imaging courses across undergraduate and graduate programs, contributing significantly to physics and biomedical engineering education. He leads the Renaud research group within Imaging Physics, focusing on advancing ultrasound imaging technologies for medical diagnostics with applications in osteoporosis screening and cardiovascular disease assessment.

Yuyang Guمشاهده پروفایل

استادیار

• Acoustics
• Ultrasound Imaging
• Wave Control
• +۴ مورد دیگر

Yuyang Gu is an Assistant Professor in the Department of Mechanical Engineering at Binghamton University. His research focuses on acoustics, wave control, ultrasound imaging, microfluidics, and biomedical micro/nano systems. Previously, he conducted postdoctoral research at Harvard Medical School (HMS) and Massachusetts General Hospital (MGH), where he worked on ultrasound imaging and elasticity imaging using advanced acoustic wave control. Education: BS and MS in Acoustics, Nanjing University, China PhD in Mechanical Engineering and Materials Science, Duke University Research Interests: Dr. Gu's work emphasizes the development of acoustic tweezers, acoustofluidics, and microfluidics for biomedical applications. His lab explores novel methods for particle manipulation, diagnostic imaging, and therapeutic systems. Recent advancements include acoustic-based separation technologies for exosomes, viruses, and extracellular vesicles, as well as physics-inspired machine learning approaches for ultrasound elastography. Grants & Collaborations: His research is supported by projects in medical imaging, nanotechnology, and biomedical engineering. Collaborations include work at HMS/MGH and Duke University, with a focus on translating acoustic technologies into clinical applications.

Valery Vishnevskiyمشاهده پروفایل

مدرس

• Biomedical Imaging
• Magnetic Resonance Imaging (MRI)
• Ultrasound Imaging
• +۳ مورد دیگر

Dr. Valery Vishnevskiy is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich , affiliated with the Biomedical Imaging Group . His research focuses on advanced medical imaging techniques, particularly in cardiac MRI , ultrasound , and machine learning applications . He contributes to projects involving 4D flow MRI reconstruction , speed-of-sound imaging , and motion-corrected diffusion tensor analysis . Primary Affiliation : ETH Zürich, Department of Information Technology and Electrical Engineering Research Interests : Biomedical Imaging, MRI Reconstruction, Ultrasound Physics, Cardiac Imaging, Deep Learning His recent work emphasizes self-supervised learning for medical imaging, including the development of FlowMRI-Net for accelerated 4D flow MRI and Speed-of-Sound Imaging using diverging waves. Publications span hyperpolarized 13C metabolic imaging , viscoelasticity reconstruction , and probabilistic sampling optimization . Dr. Vishnevskiy's contributions to deformable image registration include methods for handling sliding interfaces in abdominal and cardiac imaging, with applications in respiratory motion compensation and tissue ablation monitoring . He also explores mathematical models for enzyme activity analysis and behavioral pattern detection.

Alfred Yuمشاهده پروفایل

استاد

• Biomedical Ultrasound
• Medical Imaging Technologies
• Vector Flow Imaging
• +۴ مورد دیگر

Alfred Yu is a Professor and Assistant Vice-President (Research and International) at the University of Waterloo. His research focuses on advancing biomedical ultrasound imaging technologies, particularly in vector flow imaging, sonoporation mechanisms, and real-time diagnostic systems. He leads efforts in developing innovative imaging modalities for clinical applications, including flow dynamics analysis, microbubble-mediated drug delivery, and high-resolution vascular imaging. Yu's work bridges theoretical acoustic modeling with practical medical device development, emphasizing translational research. His research contributions span ultrasound system design, signal processing algorithms, and phantom models for validation. Key areas include improving the accuracy of speed-of-sound estimation, optimizing Doppler ultrasound systems, and investigating cellular responses to sonoporation. Yu collaborates closely with clinical partners to ensure technologies address unmet medical needs, such as non-invasive flow visualization and enhanced drug delivery mechanisms. Leveraging artificial intelligence and deep learning, his team develops adaptive clutter filtering and real-time feedback control systems to enhance imaging resolution and reduce artifacts. The lab's work is supported by collaborations with industry and clinical institutions, aiming to translate cutting-edge research into clinical tools.

• Blind Signal Processing
• Bayesian Estimation
• Particle Filters
• +۳ مورد دیگر

Ayşın Baytan Ertüzün is a Professor at Boğaziçi University, specializing in signal processing and statistical methodologies. Their research focuses on blind signal processing, Bayesian estimation techniques, particle filters, and seismological applications. They have contributed extensively to defect detection in textiles using advanced signal processing methods like wavelet transforms and independent component analysis, as well as geophysical signal analysis through Bayesian deconvolution approaches. Over 25 years of academic work includes pioneering work in non-Gaussian processes, time-varying autoregressive models, and particle filtering algorithms for complex signal environments. Their research bridges theoretical advancements with practical applications in manufacturing quality control and seismic data analysis. Key technical contributions include hybrid deconvolution methods for Bernoulli-Gaussian processes, subband domain subspace analysis for texture defects, and entropy-based 2D lattice filter structures. Their work often emphasizes robust statistical frameworks for non-stationary and non-Gaussian signal environments, with applications spanning from environmental forecasting (wind speed modeling) to medical signal analysis (respiratory sound coherence). Publications span from foundational 1990s lattice filter innovations to modern Bayesian approaches. Their methodologies are characterized by interdisciplinary fusion of signal processing theory with real-world industrial and geophysical challenges. No specific awards are listed in the provided materials, though their extensive publication record indicates sustained academic impact.

Brian Elbingمشاهده پروفایل

استاد

• Fluid Mechanics
• Flow Control
• Drag Reduction
• +۵ مورد دیگر

Brian Elbing is the Tom Cunningham Chair and Professor in the School of Mechanical and Aerospace Engineering at Oklahoma State University (OSU). His research focuses on fluid mechanisms, particularly tornado infrasound, drag reduction for ships, helicopter wake dynamics, and atmospheric turbulence. He has been recognized with prestigious awards, including the Gordon and Betty Moore Foundation's Experimental Physics Investigator award (2022-present) and the Regents Distinguished Research Award (2024). Education: Ph.D., Mechanical Engineering, University of Michigan, 2009 M.S.E., Mechanical Engineering, University of Michigan, 2005 B.S., Mechanical Engineering, Western Michigan University, 2003 Research Interests: Elbing's work spans fluid dynamics, flow control, and acoustics. His tornado research explores infrasound generated by tornadoes, while his drag reduction studies focus on naval applications. He also investigates atmospheric turbulence and multiphase flows. His research has been featured in Physics Today , Wall Street Journal , and WIRED . Grants & Awards: Lead investigator for grants including NASA-funded balloon-based seismic studies and tornado infrasound monitoring. Recipient of the Tom J. Cunningham Chair (2024–present) and Moore Foundation support. Labs & Teams: Directs the Experimental Flow Physics Lab, collaborating with NASA, JPL, and international teams on projects like the OSIRIS-REx sample return capsule re-entry observations and stratospheric balloon-based sensing.

• Deep Learning
• Audio-Visual Learning
• Multi-Modal Video Understanding
• +۳ مورد دیگر

Vladimir Iashin is a Postdoctoral Research Fellow at the Visual Geometry Group (VGG), University of Oxford . He earned a PhD with distinction in EECS from Tampere University and holds MSc in Applied Mathematics and Computer Science and BSc in Economics from HSE University . PhD (with distinction), Tampere University MSc (with distinction), HSE University BSc, HSE University His research focuses on deep learning for multi-modal video understanding , particularly audio-visual synchronization and visually guided sound generation . He develops transformer-based architectures for cross-modal sequence modeling and neural audio codecs for efficient spectrogram generation. His recent publications analyze techniques like codebook-based audio generation and sparse synchronization , with applications in open-domain sound synthesis and automatic evaluation metrics (e.g., Melception, MKL). Key trends include transformer scalability on large datasets (VGGSound) and visual-conditioned sampling trade-offs between fidelity and speed. Scientific awards include his PhD with distinction . He contributed to open-source tools like Video Features for GPU-accelerated video processing and co-authored benchmarks for container property estimation in robotics.

Sabah Badri-Höherمشاهده پروفایل

استاد

• Digital Signal Processing
• Underwater Robotics
• Sonar and Image Processing
• +۴ مورد دیگر

Sabah Badri-Höher is a Professor at the Kiel University of Applied Sciences (UAS Kiel) in the Department of Digital Signal Processing. She leads the AUV team 'TomKyle' in collaboration with GEOMAR Helmholtz Centre for Ocean Research Kiel and oversees projects like MAUS (autonomous underwater vehicles) and UFOTriNet (automated fish detection). Research Focus: Her work spans digital signal processing, underwater robotics, sonar data interpretation, acoustic communication, and computer vision. Key applications include AUV navigation, fish tracking, and underwater sensor networks. Publications: Recent articles emphasize sonar-based fish detection, AUV collision avoidance, cooperative swarm navigation, and signal processing for underwater environments. Trends include machine learning integration (e.g., Kalman filters, deep learning) and multi-sensor fusion. Student Advising & Projects: She supervises doctoral candidates in signal processing, computer vision, and underwater systems. Major grants include: MAUS: Development of interconnected AUVs for coordinated missions. UFOTriNet: Automated fish population monitoring using low-light cameras/sonar. Labs & Teams: Heads the DSV research group, collaborating with GEOMAR on student AUV teams. The lab focuses on underwater robotics, sensor algorithms, and participates in competitions like SAUC-E.