Aswin Sankaranarayanan is a Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU) , where he leads the Image Science Lab . His research focuses on computational photography , 3D shape estimation , and novel imaging system design . He earned his Ph.D. in Electrical and Computer Engineering (2009) from the University of Maryland and completed a postdoctoral fellowship at Rice University (2012) . Research Themes: Developing imaging systems that exploit low-dimensional signal models to overcome traditional sensing limitations Co-design of optics and processing algorithms for efficient sensing Application of non-linear signal models to high-dimensional data Advancing compressed sensing and big data processing techniques Scientific Recognition: SIGGRAPH 2023 Best Paper Award (Split-Lohmann Multifocal Displays) CVPR 2019 Best Paper Award (Fermat Paths for NLOS Reconstruction) NSF CAREER Award (2017) Dean’s Early Career Fellowship (2018-2021) Herschel Rich Invention Award (2016) Technical Contributions: His recent publications reveal expertise in non-line-of-sight shape reconstruction , VR/AR display systems , and biomedical imaging . Collaborations span institutions like University College London and University of Toronto.
جستجوی استاد راهنمای دانشگاهی
برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۱۶-۳۰ از ۹۳۷ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Professor Göran Broström works at the Department of Marine Sciences at the University of Gothenburg . His research focuses on physical oceanography, marine turbulence, tidal energy systems, and biophysical processes in marine ecosystems. Current research themes include methane emissions from ocean infrastructure, turbulence in tidal flows, and wave-current interactions He utilizes advanced numerical modeling (e.g., Large Eddy Simulation, Bayesian inversion) and field observations Recent publications emphasize climate impacts (methane plumes), tidal energy innovations, and marine ecological connectivity His work appears in high-impact journals like Nature , Molecular Ecology , and Frontiers in Marine Science . Collaborative projects span oceanographic modeling, environmental monitoring, and marine renewable energy. No specific student advising information appears in the provided text.
Yukun Liمشاهده پروفایل
دانشیار
Yukun Li is an Associate Professor in the Department of Mathematics at the University of Central Florida (UCF), part of the College of Sciences. His research focuses on numerical analysis, stochastic partial differential equations, and computational finance. He holds a Ph.D. in Mathematics from the University of Tennessee, Knoxville (2010-2015), followed by postdoctoral roles at Penn State (2015-2016) and The Ohio State University (2016-2019). He has secured grants including NSF REU funding (2023-2026) and led an NSF-funded project on stochastic phase field models (2021-2025). Research interests include: Continuous/Discontinuous Finite Element Methods Numerical Solutions of Stochastic ODEs/PDEs Adaptive Algorithms and Fast Solvers Computational Finance Models Recent publications emphasize stochastic wave equations, phase field models, and financial mathematics. His work spans theoretical analysis and numerical methods for complex systems. Notable recognition includes the 2015 Achievement Award from the University of Tennessee's Mathematics Department. Teaching highlights include advanced graduate courses like Computational Methods for Financial Mathematics and Numerical Linear Algebra, alongside contributions to undergraduate mathematics education. He is proficient in computational tools including MATLAB, Python, FEniCS, and MPI.
Gabi Laske is a Professor at the Institute of Geophysics and Planetary Physics (IGPP), Scripps Institution of Oceanography (SIO), University of California, San Diego (UCSD). She is a leading researcher in seismology and geophysics, with a focus on Earth's internal structure, crustal and mantle modeling, and ocean-bottom seismology. Her work has significantly advanced global crustal models, including CRUST5.1, CRUST2.0, and CRUST1.0. Her research interests include seismology, geophysics, Earth's internal structure, surface wave tomography, normal mode analysis, crustal and lithospheric modeling, ocean bottom seismology, mantle plumes, inner core rotation, ambient noise seismology, and earthquake signal processing. She has led major projects such as the Hawaiian PLUME and SWELL experiments, utilizing ocean-bottom seismometers to study mantle dynamics and lithospheric rejuvenation. Her work on inner core differential rotation, particularly with Guy Masters, has been published in top journals like Nature and Science . The 15 most recent publications reflect a strong trend in ocean-bottom seismology, ambient noise analysis, instrument calibration, seismic signal quality, and imaging of crustal and mantle structure. Her work combines observational seismology with advanced signal processing and modeling techniques, often in collaboration with students and international teams. She has made significant contributions to understanding seismic anisotropy, normal modes, and the structure of volcanic and tectonic regions. Funded by NSF (OCE, EAR, CSEDI, MG&G) Collaborative projects with USGS, international institutions Advisor to PhD students, including Adrian Doran Lead developer of DLOPy for OBS orientation Contributor to global reference models (CRUST1.0, LITHO1.0) Gabi Laske has made enduring contributions to geophysics through her development of global crustal models, leadership in major seismic experiments, and mentorship of the next generation of seismologists. Her work continues to shape our understanding of Earth's deep interior and surface processes.
- Seismology
- Geophysics
- Earth's Internal Structure
- +۸ مورد دیگر
Jeffrey Krolik is a Professor of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. He holds a Ph.D. in Electrical Engineering from the University of Toronto (1987) and previously served as an Assistant Professor at Concordia University and Assistant Research Scientist at Scripps Institution of Oceanography. Ph.D. University of Toronto (1987) M.A. University of Toronto (1983) B.A. University of Toronto (1980) His research focuses on physics-based and statistical signal processing with applications in radar, sonar, microwave remote sensing, and medical imaging. Key projects include adaptive beamforming for ocean acoustic waveguides, aircraft height finding via HF radar, and motion-robust fMRI algorithms. Recent publications cover multipath mitigation in sonar arrays, vibrational radar backscatter communication, and CNN implementations for radar signal processing. His work spans underwater acoustics, urban radar tracking, and distributed sensor networks. He teaches advanced courses in sensor array signal processing, digital audio systems, and radar applications. His research has been supported through collaborations with institutions like Scripps and consulting roles with ONR, DARPA, and Air Force Rome Laboratories. Key contributions include waveguide invariant processing, matched-field beamforming, and novel approaches to radar clutter suppression in urban and maritime environments. His work integrates statistical signal processing with physical propagation models across diverse domains.
Alessia Ferrari is a fixed-term researcher in the Department of Engineering and Architecture at the University of Parma, Italy. She lectures on Hydrology within the Bachelor’s degree programme in Civil and Environmental Engineering and serves as the reference teacher for the same programme across multiple academic years (2020/2021 – 2025/2026). Research Focus Ferrari’s research integrates advanced numerical modelling with real-world flood-risk management. Key themes include: High-resolution 2-D shallow-water simulations using GPU-parallel codes. Porosity-based approaches for large-scale urban flood modelling. Levee-breach hydraulics and emergency-action planning. Calibration of hydraulic models using tools such as PEST. Integration of machine-learning techniques with physics-based flood forecasting. Publication Trends Across more than 25 peer-reviewed works (2015-2025), Ferrari has concentrated on computational hydraulics applied to extreme flood events in Northern Italy (e.g., Parma 2014, Lamone 2024). Her papers consistently advance numerical schemes (ADER, HLLEM Riemann solvers) and GPU acceleration while validating models against field data, thereby bridging theoretical development and practical flood-mitigation strategies. Contact & Office E-mail: alessia.ferrari@unipr.it Office: Science and Technology Campus – Pavilion 10, Engineering Scientific Headquarters, Parco Area delle Scienze 181/A, 43124 Parma, Italy.
Gheorghe Craciun is a Professor in the Department of Mathematics and the Department of Biomolecular Chemistry at the University of Wisconsin-Madison. His research focuses on mathematical and computational models in biology and medicine, particularly dynamical systems models of biological interaction networks. He has been a visiting researcher at the Max Planck Institute for Mathematics in the Sciences during the 2019-2020 academic year and has organized the Madison Workshops on Mathematics of Reaction Networks. Craciun's primary research interests include Mathematical Biology, Dynamical Systems, Chemical Reaction Networks, Computational Biology, Systems Biology, and Algebraic Geometry. He investigates systems of differential equations with polynomial right-hand sides, which are common in biochemical reaction networks, ecological interactions, and epidemiological models. His work often involves proving global stability, analyzing multistability, and characterizing steady states using tools from algebraic geometry and combinatorics. Recent publications demonstrate his focus on toric differential inclusions, endotactic networks, and the global attractor conjecture, extending to applications in biochemical networks and discrete Boltzmann equations. His extensive publication record reveals a strong trend toward algebraic and geometric methods for analyzing complex biological networks, with significant contributions to reaction network theory, stability analysis, and parameter characterization. Craciun's work bridges abstract mathematical concepts with practical applications in biochemistry, ecology, and medicine, including modeling vitellogenin production in trout and peptide mass distributions. He has collaborated extensively with international researchers including Alicia Dickenstein, Anne Shiu, Bernd Sturmfels, Casian Pantea, and Miruna-Stefana Sorea. In education, Craciun teaches graduate courses such as Math 703 and mentors students through the Madison Math Circle and Putnam Club, while organizing specialized workshops that foster collaboration in reaction network theory.
Patrick Brownمشاهده پروفایل
دانشیار
Patrick Brown is an Associate Professor at the University of Toronto , affiliated with the Department of Statistical Sciences and cross-appointed to the Centre for Global Health Research and St. Michael's Hospital . His research focuses on spatio-temporal data modeling , Bayesian inference , and non-parametric methods for spatial epidemiology and environmental sciences. Fields of Interest : Spatial Statistics, Cancer Statistics, Statistical Software Education : PhD from University of Lancaster His methodological work encompasses Bayesian inference for non-Gaussian spatial data, Gaussian Markov random fields, and computational techniques like INLA and MRA. Applied research themes include disease mapping, environmental risk assessment, and public health surveillance using real-world data sources such as electronic health records and wastewater monitoring . He has developed key R packages (mapmisc, geostatsp, diseasemapping) supporting spatial statistical applications. Current collaborative projects span diverse fields: Ultra-diffuse galaxy detection with astrophysical applications Multi-pollutant mortality studies in Canadian cities SARS-CoV-2 seropositivity tracking Homelessness population estimation using EHR Geospatial cancer risk tools for Nova Scotia His work bridges statistical innovation with global health challenges , emphasizing computationally efficient solutions for large-scale spatiotemporal datasets.
Prof. David Ham is a Professor of Computational Mathematics at the Department of Mathematics, Faculty of Natural Sciences, Imperial College London. His research focuses on high-level abstractions for scientific computation, particularly in geophysical fluids and numerical software. He leads the Firedrake project and co-developed the dolfin-adjoint framework, which received the 2015 Wilkinson Prize for Numerical Software. Ham holds a BSc (Mathematics) and LLB from The Australian National University, and a PhD from TU Delft. His career includes roles as a NERC Independent Research Fellow and Grantham Research Fellow at Imperial College. He is affiliated with the Grantham Institute, Mathematics of Planet Earth, and Software Performance Optimisation groups. His research spans computational science, including finite element methods, adjoint-based inversion, and parallel computing. Recent work emphasizes differentiable programming integration with machine learning and geophysical modeling. Ham has contributed to numerous grants and projects, including EPSRC and NERC-funded initiatives. He leads development of software tools like Firedrake and Thetis, advancing computational methods for oceanography and geodynamics.
György Hetényiمشاهده پروفایل
دانشیار
György Hetényi is an Associate Professor at the Institute of Earth Sciences, University of Lausanne, specializing in large-scale geophysics. His research focuses on mountain-building processes, earthquake dynamics, and tectonic deformation of the Himalayas and Alps. He leads the AlpArray project, deploying the largest academic seismic network in Europe. Since 2015, he has held an SNSF Assistant Professorship, advancing to his current role in 2020. Education: Bachelor's in Geophysics at Eötvös University (Budapest) Master's and PhD at École Normale Supérieure (Paris), studying Himalayan deformation Research Interests: Combining seismic and gravity data to model crustal structures, numerical modeling of orogenic processes, and educational seismology initiatives in Nepal. Active in field campaigns across Bhutan, Nepal, and the Ivrea-Verbano Zone. Publications: Over 48 peer-reviewed articles since 2007, emphasizing crustal imaging, seismic tomography, and Himalayan tectonics. Recent work includes participatory gravity modeling challenges and pan-Alpine gravity database development. Awards: Prize of the Chancellery of the Universities of Paris (2007) for doctoral research on Himalayan deformation. Teaching & Outreach: Developed the 'Geophysics Across Scales for Geologists' module in the UNIL-UNIGE program. Co-leads the Nepal School Seismology Network, integrating low-cost seismic education tools. Grants & Projects: AlpArray, DIVE (scientific drilling in Ivrea Zone), and seismic hazard assessments in Bhutan. Collaborates with international networks like ICDP and European seismic consortia. Labs/Teams: Part of the Institute of Earth Sciences (UNIL) and leads the OROG3NY project on mountain-building dynamics.
- Geophysics
- Tectonics
- Seismology
- +۵ مورد دیگر
Hans Bihs is a Professor in the Department of Civil and Environmental Engineering, Faculty of Engineering. His research focuses on computational fluid dynamics (CFD), wave hydrodynamics, and wave-structure interaction using the open-source framework REEF3D. Key Research Areas: CFD simulations, wave modeling, floating body dynamics, ocean wave energy, aquaculture hydrodynamics, sediment transport, and high-performance computing. Projects: ERC Consolidator Grant PARTRES (2023-2028), EEA Grants Portugal SurfWave (2023), NFR KPN IPIRIS (2021-2025), EEA Baltic SolidShore (2021-2024), NTNU's MAPLE (2022-2025), and DigiCoast (2021-2024). Email: hans.bihs@ntnu.no His recent publications (2025-2020) analyze fluid-structure interaction, ship-induced waves, floating offshore wind turbines, submerged vegetation, and coastal structures using advanced CFD techniques. Topics include wave hydrodynamics, turbulence, and numerical modeling for marine and aquaculture systems.
Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.
Matias Zaldarriaga is the Richard Black Professor in the School of Natural Sciences at the Institute for Advanced Study (IAS), Princeton. His research focuses on theoretical cosmology, gravitational waves, and the Cosmic Microwave Background (CMB). He has held previous faculty positions at Harvard University (2003-2009) and New York University (2001-2002). Education: Ph.D. in Physics, Massachusetts Institute of Technology, 1998 Licenciado en Ciencias Físicas, Universidad de Buenos Aires, 1994 Zaldarriaga's work centers on decoding the early universe through CMB analysis and gravitational-wave astrophysics. He investigates inflation, large-scale structure formation, and black hole dynamics, leveraging advanced statistical methods to probe fundamental physics from cosmological data. His recent publications (2023-2025) demonstrate a strong focus on gravitational-wave data analysis, including novel algorithms for detecting binary black hole mergers, constraints on inflationary physics from large-scale surveys, and modeling supermassive black hole evolution. Key themes include higher-order waveform harmonics, pulsar timing arrays, and computational innovations for gravitational-wave astronomy. Awards and Honors: Gruber Cosmology Prize (2021) MacArthur Fellowship (2006) European Physical Society Gribov Medal (2005) Sloan Fellowship (2004) Helen B. Warner Prize, American Astronomical Society (2003) Packard Fellowship (2001) He collaborates extensively with international teams (e.g., LIGO-Virgo-KAGRA, DESI) and mentors researchers in cosmology and astrophysics. His group develops open-source tools for gravitational-wave inference and cosmological parameter estimation.
Kent Yagiمشاهده پروفایل
دانشیار
Kent Yagi is an Associate Professor in the Physics Department at the University of Virginia, specializing in theoretical astrophysics, gravity, and cosmology. His research focuses on using gravitational waves from compact objects like black holes and neutron stars to probe fundamental physics, including testing General Relativity in strong-field regimes and determining the equation of state of nuclear matter. Position: Associate Professor (2023-present), previously Assistant Professor (2017-2023) Education: Ph.D. in Physics from Kyoto University (2012) Prior positions: Postdoctoral Research Scholar at Princeton University (2015-2017), Postdoctoral Research Associate at Montana State University (2012-2015) Yagi's research centers on theoretical modeling of neutron stars and gravitational wave physics. He is particularly known for discovering the 'I-Love-Q' universal relations among neutron star observables that are insensitive to the equation of state. His work enables testing strong-field gravity and probing nuclear physics through gravitational wave observations. He also investigates binary pulsar systems as precision laboratories for testing gravitational theories beyond General Relativity. His research has significant implications for multi-messenger astronomy, connecting gravitational wave observations with electromagnetic counterparts to extract fundamental physics. The field has evolved rapidly since the first gravitational wave detection in 2015, and Yagi's theoretical predictions have helped shape how we interpret these observations to test gravity and nuclear physics in extreme conditions. NSF CAREER Award (2023) Sloan Research Fellowship (2019) IUPAP Young Scientist Prize (2019) Mead Honored Faculty (2018-2019) Yagi leads an active research group at UVA with multiple graduate and undergraduate students. His group collaborates with researchers across departments, including high energy physicists, nuclear physicists, astronomers, and researchers at the National Radio Astronomy Observatory. Current research directions include multi-band gravitational wave tests of general relativity, constraining nuclear matter parameters with GW170817, and developing parameterized post-Einsteinian gravitational waveform models for various modified gravity theories. The group has received multiple student research fellowships and awards, demonstrating strong mentorship and training of the next generation of physicists.
Gianmarco Pinton is an Associate Professor in the Department of Biomedical Engineering at the University of North Carolina at Chapel Hill. His research focuses on nonlinear ultrasound and mechanical wave propagation, with applications to medical imaging and therapy. He specializes in traumatic brain injury, shear shock waves, and ultrasound therapy. Ph.D., M.S., and B.S.E. in Biomedical Engineering/Physics from Duke University His lab develops physics and simulation tools for nonlinear wave propagation, aiming to create advanced diagnostic ultrasound methods. Key areas include traumatic brain injury, transcranial imaging, and therapeutic ultrasound. His recent work explores super-resolution imaging, brain motor circuits, and Alzheimer's disease vascular mapping using ultrasound. Article trends highlight innovations in transcranial ultrasound, super-resolution techniques, lung imaging, and neuromodulation. His publications address image degradation, contrast agents, and shear wave dynamics in neurological contexts.
نمایش نتایج تا ۷۵۰ مورد اول. برای یافتن نتایج دقیقتر، جستجوی خود را با فیلترها محدود کنید.