جستجوی استاد راهنمای دانشگاهی

Moussa Tembelyمشاهده پروفایل

استادیار

• Multiphase Flows
• CFD
• Flow in Porous Media
• +۳ مورد دیگر

Moussa Tembely is an Assistant Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University. His research focuses on Multiphase Flows, Computational Fluid Dynamics (CFD), Flow in Porous Media, Machine and Deep Learning, Thermal Spray, and Icing phenomena. He supervises graduate students in Mechanical Engineering (MASc and PhD programs). His work integrates advanced computational methods and AI-driven approaches to solve complex problems in fluid dynamics, reservoir engineering, and materials science. Key research interests include predictive modeling of droplet dynamics, enhanced oil recovery (EOR) optimization using machine learning, and the analysis of porous media flow. He leads the Multiphase Thermofluids Learning Lab , which explores interdisciplinary solutions for energy and environmental challenges. Recent studies emphasize data-driven derivation of governing equations and analytical solutions for fluid-structure interactions. Teaching responsibilities include courses such as HEAT TRANSFER I (MECH 352), DYNAMICS (ENGR 243), and FLUID MECHANICS II (MECH 361). His publications span over two decades, showcasing contributions to multiphase flow physics, thermal spray technology, and AI applications in geoscience and engineering.

Paul Savaمشاهده پروفایل

استاد

• Seismic Imaging
• Planetary Geophysics
• Wavefield Tomography
• +۵ مورد دیگر

Paul Sava is a Professor and C.H. Green Chair of Exploration Geophysics at the Colorado School of Mines, serving as Department Head of Geophysics since 2019. He holds a PhD in Geophysics from Stanford University (2005), an MSc from Stanford (1998), and an Engineer Geophysicist degree from the University of Bucharest (1995). His research focuses on seismic and radar wavefield imaging, planetary geophysics, and infrastructure monitoring. Notable contributions include advancements in wave-equation migration and planetary radar tomography. Education: PhD in Geophysics, Stanford University, 2005 MSc in Geophysics, Stanford University, 1998 Engineer Geophysicist, University of Bucharest, 1995 Research interests emphasize wavefield-based methods for subsurface imaging, planetary resource exploration, and autonomous data acquisition. Recent work explores seismic imaging of asteroids and Mars, leveraging orbital radar systems. His publications span seismic inversion, microseismic monitoring, and elastic wavefield tomography. Awards include the Reginald Fessenden Award (2007), T.K. Young Leadership Award (2020), and multiple Top 30 presentations at SEG Annual Meetings. He leads the Center for Wave Phenomena and actively collaborates with NASA and industry consortia on grants totaling over $6 million. Advising and grants involve mentoring over 30 students and postdocs, with grants focused on planetary radar imaging, seismic FWI, and Mars subsurface analysis. Key projects include the Planetary Orbital Radar Processing and Simulation System (PORPASS) and autonomous seismic exploration systems. Labs/Teams: Directly leads the Center for Wave Phenomena and the Seismic Imaging Team at CWP, advancing open-source tools like Madagascar for reproducible geophysical research.

Mahmood Azimi-Sadjadiمشاهده پروفایل

استاد

• Digital Signal Processing
• Machine Learning
• Distributed Sensor Networks
• +۳ مورد دیگر

Dr. Mahmood Azimi-Sadjadi is a full Professor in the Department of Electrical and Computer Engineering at Colorado State University (CSU), affiliated with the Walter Scott, Jr. College of Engineering. He leads the Digital Signal/Image Processing Laboratory , focusing on advanced signal processing, machine learning, and underwater acoustics research. His work spans sonar systems, distributed sensor networks, and remote sensing applications. Educational Background: B.S. in Electrical Engineering, University of Tehran (1977) M.S. and Ph.D. in Electrical Engineering, Imperial College of Science and Technology, University of London (1978, 1982) Research Focus: His research emphasizes statistical signal/image processing, machine learning, and underwater target detection/classification using sonar. He has pioneered methods like manifold-based UXO classification and Bayesian occupancy grids. His lab develops both theoretical frameworks (e.g., canonical correlation analysis) and applied systems (e.g., acoustic tomography). Recent Publications Trends: Recent work includes adaptive machine learning for underwater UXO classification, wildfire prediction via satellite data, and autonomous systems navigation. His publications blend signal processing fundamentals with cutting-edge AI techniques. Awards & Affiliations: 1999 Abell Faculty Teaching Award (College of Engineering) Fellow of CIRA (Center for Information and Remote Sensing Research) Member of IEEE (Life Member) and IEEE Neural Network Society Advising & Labs: Directs the Digital Signal/Image Processing Lab, which collaborates on projects like acoustic source localization and sensor network optimization. His research has been supported by grants from agencies like SERDP (e.g., MR-2416 project).

Salavat Aglyamovمشاهده پروفایل

استاد پژوهش

• Elastography
• Biomechanics
• Biomedical Imaging
• +۷ مورد دیگر

Dr. Salavat Aglyamov is a Research Professor in the Department of Mechanical and Aerospace Engineering at the University of Houston. His work focuses on biomechanical imaging and elastography techniques such as optical coherence elastography (OCE), Brillouin microscopy, and ultrasound. He leads the Biomedical Optics Laboratory and teaches courses in biomedical engineering. Research interests include corneal biomechanics, tissue stiffness analysis in diseases like glaucoma and keratoconus, and developmental biology applications in embryos and zebrafish models. Key innovations involve multimodal imaging systems combining OCT with other modalities for non-invasive tissue characterization. Recent studies address age-related lens changes, drug delivery monitoring, and the biomechanics of neural tube defects in mouse embryos. Education: Ph.D., Institute of Theoretical and Experimental Biophysics, Pushchino, Russia His research applies machine learning (CNNs) to improve strain estimation in OCE and explores clinical applications like glaucoma detection and corneal crosslinking treatment efficacy. He collaborates on projects involving systemic sclerosis assessment via OCT/OCE/OCTA and has developed novel methods for safe acoustic radiation force-based measurements on ocular tissues. His lab’s work spans from fundamental material science (e.g., Brillouin frequency shifts under environmental conditions) to translational medicine (e.g., drug delivery tracking). Publications emphasize high-resolution 3D elasticity mapping of embryos, alcohol’s impact on embryonic development, and nanobomb OCE for glioblastoma studies. His work bridges engineering and medicine through advanced optical techniques for understanding tissue mechanics in health and disease.

Matthew Clarkمشاهده پروفایل

استاد

• Remote Sensing
• Geographic Information Systems
• Biogeography
• +۵ مورد دیگر

Matthew Clark is a Professor and Director of the Center for Interdisciplinary Geospatial Analysis (CIGA) in the Department of Geography, Environment, and Planning at Sonoma State University. He holds a PhD in Geography from UC Santa Barbara (2005) and prior degrees from UC Berkeley and the University of Washington. His research focuses on conservation, remote sensing, and geospatial technologies applied to biodiversity monitoring, wildfire impacts, and environmental change. Key projects include drone-based canopy fuel analysis, acoustic biodiversity surveys, and satellite remote sensing of forest structure. He has secured over $4M in grants from NASA and Cal Fire for projects like Soundscape-to-Landscapes biodiversity monitoring and GEDI-based wildfire impact studies. Clark’s work appears in top journals like Remote Sensing of Environment and Frontiers in Remote Sensing. He advises students on geospatial analysis and leads the CIGA lab, collaborating internationally on South African acoustic biodiversity projects and Latin American forest conservation efforts. His teaching and research emphasize practical solutions for coupled human-environment systems, integrating citizen science with advanced technologies like lidar, hyperspectral imaging, and machine learning. Clark’s office is Stevenson Hall 3503, with hybrid advising hours via Zoom and in-person.

Fumie Costenمشاهده پروفایل

مدرس

• Computational Electromagnetics
• Ultra-WideBand Systems
• Microwave Imaging
• +۲ مورد دیگر

Dr. Fumie Costen is a Lecturer in the School of Electrical and Electronic Engineering at the University of Manchester, specializing in computational electromagnetics and medical imaging applications. With a research career spanning ATR Laboratories and Kyoto University, she develops advanced algorithms for electromagnetic wave modeling. Education: PhD in Informatics, Kyoto University MEng, Kyoto University BEng, Kyoto University Her research integrates electromagnetic theory with machine learning, focusing on: Ultra-wideband systems and FDTD methods Microwave imaging for medical diagnostics GPU-accelerated electromagnetic simulations Precision agriculture applications Recent publications demonstrate her pivot toward biomedical applications, using convolutional neural networks for brain tumor analysis, stroke classification, and age prediction from MRI data. This work bridges electromagnetic expertise with clinical diagnostics. Awards: ATR Excellence in Research Award (1996) Best Paper Award at International Conference (2000) Supervision and Collaboration: Supervised 25+ PhD students in electromagnetics and computing Collaborates internationally with RIKEN, ESPCI, and Kyushu University Leads projects on medical image classification and electromagnetic sensor systems

• Ecology
• Environmental Science and Management
• Ecological Applications
• +۷ مورد دیگر

Robert Ewers is a Professor of Ecology at Imperial College London’s Department of Life Sciences (Silwood Park), part of the Faculty of Natural Sciences. His research focuses on integrating data science with ecological systems to address biodiversity and environmental challenges. He leads the Virtual Ecosystem initiative and collaborates with the SAFE Project, BUGG, and the Grantham Institute. Affiliations include the Georgina Mace Centre for the Living Planet, Centre for Infrastructure Robotics Ecosystems, Earth Observation Network, and Earth Observation Network. His expertise spans biodiversity conservation, ecosystem modeling, and sustainable land use. He advises industries on carbon strategies and environmental assessments. Ewers emphasizes inclusive research group dynamics, mentoring students toward academic and professional success. His work bridges ecology with technology through innovations like the MAARU acoustic monitoring system. Research interests include tropical forest dynamics, ecoacoustic monitoring, climate impacts, and land-use policy. His recent articles analyze logging effects, deforestation governance, and biodiversity monitoring technologies. Ewers advocates for holistic conservation strategies and equitable data access in ecological research. Key projects include the SAFE Acoustics network in Borneo and studies on African Swine Fever spread. His work frequently intersects policy, technology, and field ecology, emphasizing real-world applications for sustainability.

Jörg Nickمشاهده پروفایل

پژوهشگر

• Partial Differential Equations
• Wave Phenomena
• Numerical Analysis
• +۳ مورد دیگر

Jörg Nick is a Postdoctoral researcher at the Seminar for Applied Mathematics at ETH Zurich, Switzerland. His academic journey includes a Doctorate degree in Mathematics from the University of Tübingen (2023) under Prof. Christian Lubich and an MSc in Mathematics from the same institution (2018). He previously held a postdoctoral position at the University of Tübingen (2023) and was a doctoral researcher there from 2018 to 2023, associated with the Deutsche Forschungsgemeinschaft (DFG) project Wave phenomena: analysis and numerics , specifically Project A2 on numerical methods for wave problems with nontrivial boundary conditions. His research focuses on the numerical analysis of partial differential equations (PDEs), particularly wave scattering and metamaterials. Key areas include integral equations for PDEs, dynamical parametric approximation, numerical methods for time-dependent metamaterials, and inverse problems in wave phenomena. His work often integrates the Boundary Element Method (BEM) and Convolution Quadrature (CQ) to analyze wave scattering and subwavelength resonators. Notable contributions include studies on electromagnetic scattering from dispersive materials, time-periodic coefficients in wave equations, and regularized parametric approximation techniques. His research bridges theoretical developments with practical applications in metamaterials and medical imaging (e.g., anomaly detection in capsule endoscopy using ensemble learning). His academic affiliations include the Collaborative Research Center (CRC) 1173 at Tübingen and current participation in ETH Zurich’s mathematical and computational initiatives. While no formal awards are listed, his prolific publication record reflects sustained contributions to numerical mathematics and applied physics.

Prasanga Samarasingheمشاهده پروفایل

دانشیار

• Audio and Acoustic Signal Processing
• Spatial Audio
• Microphone and Loudspeaker Array Processing
• +۷ مورد دیگر

Dr. Prasanga Samarasinghe is an Associate Professor at the Australian National University (ANU) within the College of Systems & Society. Her research focuses on spatial audio, acoustic signal processing, and drone audition. She holds a B.E. in Electrical and Electronic Engineering from the University of Peradeniya (2010) and a PhD in Signal Processing from ANU (2015). Key professional achievements include a 2022 Fulbright Fellowship at Yale University and the 2023 ARC DECRA Fellowship. She has secured significant funding through ARC Linkage, Discovery grants, and industry partnerships with Sony, Dolby, and META. Her industry experience includes roles at Dolby Laboratories and collaborations with defense-related entities like the Australian Signals Directorate. Research Groups: Joint supervisor of ANU Audio and Acoustic Signal Processing Group Professional Roles: Member of IEEE Signal Processing Society's Audio & Acoustic Signal Processing TC (2021–2023), former Chair of IEEE ACT Section's COMMS/SP Chapter (2018–2020) Her work bridges theoretical advancements in spatial audio with practical applications in noise cancellation, drone audition, and virtual acoustics. She actively supervises PhD and Honours students in these areas. Awards: Fulbright Fellowship (2022), ARC DECRA (2023) Industry Collaborations: Sony-Japan, Dolby (Sydney/USA), META (USA), Australian Defence Portfolio

Michael Heilemannمشاهده پروفایل

دانشیار

• Acoustics and Vibration
• Human-Computer Interfaces
• Spatial Audio
• +۳ مورد دیگر

Michael Heilemann is an Associate Professor of Electrical and Computer Engineering at the Hajim School of Engineering & Applied Sciences, University of Rochester. He holds a PhD from the same university (2018) and has been on faculty since 2018, focusing on instructional roles. His research emphasizes acoustics and vibration, human-computer interfaces, spatial audio, and digital audio effects, funded by the NSF, ONR, and New York State initiatives. He has been awarded eight patents and multiple teaching awards. Education: B.S. Physics (Canisius College, 2013); M.S. and Ph.D. in Electrical Engineering (University of Rochester, 2015 and 2018). Research interests include structural acoustic sensing, smart surfaces, and embedded machine learning for sound analysis. Notable work includes the University of Rochester room impulse response dataset and touch-location sensing on elastic surfaces. Awards include the AES Best Technical Paper (2022) and ECE Teaching Excellence (2023-2024). His work bridges signal processing and mechanical systems, with applications in audio interfaces, tactile feedback, and smart environments. Collaborative grants support projects like smart acoustic surfaces as multimodal interfaces.

Mohd. Tasleem Khanمشاهده پروفایل

استادیار

• Machine Learning/Artificial Intelligence
• Signal Processing
• Communication Systems
• +۴ مورد دیگر

Dr. Mohd. Tasleem Khan is an Assistant Professor at the Institute of Sensors, Signals, and Systems (ISSS), School of Engineering and Physical Sciences (EPS), Heriot-Watt University. Previously, he held roles as Principal Engineer at TSMC (2019), Assistant Professor at IIT Dhanbad (2020–2021), Research Consultant at KAUST (2020–2021), and Postdoctoral Researcher at Linköping University (2021–2024). He earned his Ph.D. in VLSI for signal processing and communication systems from IIT Guwahati (2019). His research focuses on Machine Learning/AI, Signal Processing, and Communication Systems, with expertise in VLSI architectures. Key contributions include energy-efficient designs for neural networks, adaptive filtering algorithms, and 6G systems. His work bridges theoretical algorithms with hardware implementation, emphasizing low-power and high-throughput solutions. Publications span circuits, systems, and interdisciplinary areas like biochemistry, showcasing his interdisciplinary approach. He has contributed to advancements in distributed arithmetic-based architectures, LMS filters, and FPGA implementations. Current affiliations include the Microwaves and Antenna Engineering Group at Heriot-Watt University, a global leader in wireless systems research.

Fan Gang Zengمشاهده پروفایل

استاد

• Cochlear Implants
• Auditory Neuroscience
• Speech Perception
• +۶ مورد دیگر

Fan Gang Zeng is a Professor in the Department of Otolaryngology at the University of California, Irvine (UCI), and Director of the Center for Hearing Research. His academic roles span multiple disciplines, including joint appointments in Anatomy & Neurobiology, Biomedical Engineering (BME), Cognitive Sciences, and SOM-Administration. His research focuses on auditory neuroscience, cochlear implants, tinnitus, and speech perception, with a particular emphasis on improving hearing restoration technologies and understanding neural mechanisms of hearing loss. Affiliations: Director, Center for Hearing Research Member, UCI Institute for Memory Impairments and Neurological Disorders (UCI MIND) NIH-funded investigator through grants like R01 DC015587 Research Interests: Professor Zeng’s work bridges engineering and neuroscience, addressing challenges in cochlear implant optimization, tinnitus biomarkers, and speech intelligibility. Key areas include: Noninvasive ear stimulation for tinnitus suppression Cochlear implant artifact attenuation techniques Cognitive correlates of auditory brainstem responses Speech processing algorithms for hearing aids and implants Grants & Funding: His research is supported by NIH grants and industry partnerships, including collaborations with companies like Axonics, Nurotron, and Syntiant. He holds patents related to cochlear implant design and neural stimulation technologies. Labs & Teams: The Center for Hearing Research at UCI integrates multidisciplinary teams to advance audiological innovations, with a focus on translating basic science into clinical applications.

David Poeppelمشاهده پروفایل

استاد

• Auditory Cognition
• Speech Perception
• Neuroscience
• +۳ مورد دیگر

David Poeppel is a Professor of Psychology and Neural Science at New York University (NYU), affiliated with the College of Arts and Science. He holds a PhD and BS from MIT, with postdoctoral training at UCSF. His research focuses on auditory cognition, speech perception, and the neural basis of language, employing techniques like MEG, EEG, and fMRI. Key interests include the temporal dynamics of speech processing, neurophysiological mechanisms of lexical access, and multisensory integration in language. Education: PhD (1995) and BS (1990) in Psychology/Cognitive Science from MIT. Positions include Professorships at NYU (2009–present) and University of Maryland (1998–2009). Awards include a 2004 American Academy Fellowship and a 2003–2004 Berlin Wissenschaftskolleg Fellowship. Research trends emphasize neural entrainment to speech structures, auditory-motor coupling, and the interplay between perception and production. Recent work explores how temporal rhythms shape auditory processing and how brain rhythms predict speech tracking variability. The Poeppel Lab also investigates musical perception and the neural underpinnings of vocal emotion. Publications span over 200 peer-reviewed articles, with recent contributions on spectrotemporal modulation, neural chunking in language, and the role of amplitude modulation in distinguishing speech from music. His work bridges cognitive science, neuroscience, and clinical applications, such as stuttering mechanisms and speech rehabilitation.

David Borchersمشاهده پروفایل

استاد

• Ecology
• Wildlife Population Dynamics
• Spatial Capture-Recapture
• +۳ مورد دیگر

Prof. David Borchers is a Professor in the Department of Statistics at the University of St Andrews, UK, affiliated with the School of Mathematics and Statistics. He specializes in developing statistical methods for ecological applications, particularly in estimating wildlife population abundance, distribution, and dynamics using advanced survey techniques. His research integrates spatial capture-recapture, distance sampling, and hidden Markov models to address challenges in conservation and wildlife management. Key research areas include spatial capture-recapture methods, acoustic and digital survey technologies, and ecological modeling of species such as snow leopards, gibbons, and marine mammals. He collaborates with global organizations like the Snow Leopard Trust and the Global Snow Leopard & Ecosystem Protection Program. His work emphasizes methodological innovation, such as improving detection probability estimates and addressing biases in survey data. Borchers has supervised numerous PhD students and led projects funded by EPSRC and other grants. His contributions span theoretical statistics and applied ecology, with a focus on bridging gaps between data collection and ecological inference. Current projects include automated animal density estimation using AI and acoustic data, and the PAWS initiative for global snow leopard assessment. He holds leadership roles in research units and has published extensively in journals like Biometrics , Methods in Ecology and Evolution , and Frontiers in Marine Science . His methodologies are widely adopted in conservation policy and wildlife management worldwide.

Peter Tyackمشاهده پروفایل

استاد

• Marine Biology
• Acoustics
• Animal Behavior
• +۳ مورد دیگر

Prof Peter Tyack is a Research-Focused Professor at the School of Biology, University of St Andrews, with affiliations to the Scottish Oceans Institute and Centre for Social Learning & Cognitive Evolution. His work spans marine mammal bioacoustics, behavioral ecology, and conservation biology. UN Sustainable Development Goals: 14 (Life Below Water), 13 (Climate Action) Collaborations: USA, Norway, UK institutions Research focuses on vocal learning evolution in mammals , cetacean communication systems , and anthropogenic noise impacts on marine wildlife. His lab develops novel methods for continuous behavioral sampling in field conditions. Recent publications examine porpoise echolocation masking by vessel noise, neural connectivity differences in whales, and marine mammal welfare monitoring . Over 258 publications reflect his extensive work in marine bioacoustics and conservation physiology. Scientific Awards Fellow of the Royal Society of Edinburgh (2016) Supervises PhD students including Gabrielle Arrieta and Dinah Hartmann. Active in marine policy advisory roles and has participated in 80+ professional activities including invited talks and workshops.