جست‌وجوی استاد و پژوهشگر

Joan Brunaمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Signal Processing
• +۵ مورد دیگر

Joan Bruna is a Full Professor of Computer Science, Data Science, and affiliated Mathematics at New York University's Courant Institute and Center for Data Science. He leads the CILVR group and co-founded the MaD group. His research focuses on mathematical foundations of machine learning, deep learning, signal processing, and their applications in computational science, climate modeling, and geophysics. He holds a Ph.D. in Applied Mathematics from École Polytechnique and has held roles at UC Berkeley, the Institute for Advanced Study, and the Flatiron Institute. Education: Ph.D. (2013) and M.Sc. (2005) in Applied Mathematics, École Polytechnique and ENS Cachan; dual B.Sc./M.Sc. in Telecommunications and Mathematics from UPC Barcelona (2002–2004). Awards include the NSF CAREER Award (2019) and Alfred P. Sloan Fellowship (2018). Research interests span theoretical aspects of deep learning, optimization, and statistical methods, with applications to climate science and inverse problems. He has advised numerous PhD students and postdocs, contributing to seminal work on scattering networks, geometric deep learning, and neural ODEs. Professional service includes editorial roles at TMLR, JMLR, and TPAMI, plus program chairs for major conferences. His work bridges mathematics and machine learning, emphasizing rigorous analysis and real-world impact.

John Paisleyمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Statistics
• Data Science
• +۳ مورد دیگر

John Paisley is an Associate Professor of Electrical Engineering at Columbia University's Fu Foundation School of Engineering and Applied Science, and a member of Columbia's Data Science Institute (DSI). He holds a B.S., M.S., and Ph.D. in Electrical and Computer Engineering from Duke University (2004-2010), followed by postdoctoral research in Computer Science at Princeton University and UC Berkeley. His research focuses on Bayesian models, posterior inference techniques for Big Data, and applications in data analysis, recommendation systems, information retrieval, and compressed sensing. He has pioneered methods like Bayesian Gaussian Process ODEs and Double Normalizing Flows, with recent work emphasizing uncertainty quantification in environmental modeling and neuroimaging analysis. His collaborative workflows (e.g., bneR ) address air pollution exposure and PM2.5 concentration uncertainties, combining Bayesian nonparametric ensembles with geospatial data. He has also developed frameworks for neural network interpretability, image denoising, and compressed sensing MRI. Paisley's work bridges statistical theory and applied machine learning, with applications in healthcare, environmental science, and geophysics. His academic contributions include over 50 publications since 2016, spanning topics like deep metric learning, adversarial learning, and variational inference optimization. He maintains an active research group and serves on editorial boards for machine learning and signal processing journals.

• Geochemistry
• Geophysics
• Petrology
• +۴ مورد دیگر

Jonathan Snow is a Professor and Chair of the Department of Geology and Geophysics at Louisiana State University (LSU), College of Science. Previously, he held faculty positions at the University of Houston, including roles as Assistant Professor (2005–2008), Associate Professor (2008–2014), and Professor (2014–2019), and served as President of the Faculty Senate (2016). His academic journey includes a Bachelor’s in Geology from Indiana University (1983), Master’s from the University of Rochester (1986), PhD in Oceanography from MIT/WHOI (1993), and a Habilitation in Mineralogy from Universitat Mainz, Germany. Research interests focus on the Earth’s lithosphere formation, mantle melting processes, and oceanic crustal accretion. Key areas include mid-ocean ridge basalt petrogenesis, mantle noble metal geochemistry (Os, Re), and tectonics of fracture zones. Notable contributions include studies on the Arctic Ocean’s Gakkel and Lena Troughs, Hess Deep, and Shikoku Basin oceanic core complexes. Professional recognitions include NSF Graduate Fellowship (USA), Alexander von Humboldt Foundation Fellowship (Germany), DFG Heisenberg Program (Germany), and Japan Society for the Promotion of Science Fellowships. His work integrates field expeditions (e.g., ARKTIS cruises), laboratory geochemistry, and computational models to advance understanding of mantle dynamics and crustal evolution.

Muhammad Gulzariمشاهده پروفایل

استادیار

• Finite Element Modelling
• Structural Dynamics
• Applied Mechanics
• +۷ مورد دیگر

Dr. Muhammad Gulzari is an Assistant Professor at the School of Civil Engineering, University College Dublin (UCD). Previously, he held positions as Lecturer/Assistant Professor at the University of Galway (2023–2024), Adjunct Assistant Professor at Trinity College Dublin (2022–2023), and a Research Fellow at Trinity College Dublin (2021–2023). He earned his Ph.D. in Civil Structural Engineering from City University of Hong Kong (2021) and a B.Sc. in Civil Engineering from the University of Engineering and Technology Lahore (2017). Education: Bachelor of Engineering, Civil Engineering, University of Engineering and Technology Lahore Ph.D., Civil Structural Engineering, City University of Hong Kong Research Interests: His work focuses on structured materials and dynamics, including finite element modeling, phononic crystals, acoustic and mechanical metamaterials, vibration and noise control, and applications in structural health monitoring. He leads the Structured Materials and Dynamics Lab at UCD, exploring nonlinear and nonreciprocal metamaterials. Teaching and Awards: He has taught courses in Fluid Mechanics, Thermodynamics, and Combustion Engineering. Notable recognitions include the Seal of Excellence Award from the EU-Horizon MSCA Postdoctoral Fellowship (2021) and nominations for teaching excellence awards at Trinity College Dublin and University of Galway. Grants: TimberFlow: Enhancing Efficiency in Mass Timber Construction (Enterprise Ireland, 2025) Indoor Acoustic Quality via Acoustic Metamaterials (Enterprise Ireland, 2025) RUBBERPAVE: ELT Integration in Pavement Construction (Enterprise Ireland, 2024–2026) Deep Learning for Metamaterial Design (Irish Research Council, 2021–2023) Labs and Collaborations: His research group collaborates with industry partners like Amplitude Acoustics and G-frame Structures Ltd. Key projects include developing metamaterials for noise/vibration control and sustainable construction materials.

• Earthquake Seismology
• Seismic Tomography
• Subduction Zone Processes
• +۴ مورد دیگر

Andreas Rietbrock is Professor and Director of the Geophysical Institute (GPI) at the Karlsruhe Institute of Technology (KIT) , Germany, where he also serves as Dean of Studies for Geophysics . He is a leading expert in earthquake seismology, seismic tomography, and subduction zone dynamics, with a strong focus on integrating advanced observational techniques and computational methods. Education: While specific degrees are not listed in the provided text, his extensive publication record and leadership roles indicate advanced academic training in geophysics and seismology. Research Interests: His work spans a wide range of topics including: Seismic imaging of subduction zones (e.g., Nazca, Lesser Antilles) Earthquake rupture dynamics and fault mechanics Volcanic seismology and magma transport Full waveform inversion and AI-enhanced seismic analysis Distributed Acoustic Sensing (DAS) applications Induced seismicity and reservoir monitoring Research Trends: His recent publications (2022–2025) emphasize the use of dense seismic arrays, AI-based data processing, and multi-method tomography to study complex tectonic environments. Key themes include high-resolution imaging of slab structures, fluid migration in subduction zones, and the integration of DAS and machine learning for seismic monitoring. Scientific Contributions: Andreas has led major international projects such as the ANTICS Large-N deployment in Albania and the VoiLA project in the Lesser Antilles. He has published extensively in top-tier journals like Nature , Geophysical Research Letters , and Journal of Geophysical Research , with over 200 peer-reviewed articles. Teaching and Supervision: He teaches courses such as "Introduction to Geophysics II", "Seismology", and "Current Topics in Seismology and Risk". While specific student names are not listed, his role as Dean and principal investigator on numerous projects indicates active supervision of graduate students and postdocs. Labs and Teams: He leads the seismology group at GPI, coordinating large-scale deployments of seismic instruments, including ocean-bottom seismometers and fiber-optic DAS systems. His team collaborates globally with institutions in Europe, South America, and Asia.

Yimin D. Zhangمشاهده پروفایل

دانشیار

• Statistical Signal Processing
• Array Processing
• Radar Signal Processing
• +۱۰ مورد دیگر

Yimin D. Zhang is an Associate Professor in the Department of Electrical and Computer Engineering at Temple University's College of Engineering, where he leads the Advanced Signal Processing (ASP) Lab. His research spans statistical signal processing, array processing, radar, wireless communications, and convex optimization. Research Interests: Dr. Zhang's work focuses on cutting-edge signal processing techniques including compressive sensing, sparse arrays, time-frequency analysis, and robust beamforming. These are applied to radar systems, satellite navigation, assisted living, and wireless networks. His research addresses core challenges in target localization, direction-of-arrival estimation, and spectrum-efficient joint radar-communication systems. The recent publications highlight a strong trend in exploiting sparsity, virtual arrays, and deep learning to enhance resolution and robustness in radar and communication systems. Themes include multi-frequency processing, low-rank matrix recovery, and optimized OFDM waveforms for dual-function systems. Scientific Awards: 2016 IET Radar, Sonar and Navigation Premium Award 2017 IEEE Aerospace and Electronic Systems Society Harry Rowe Mimno Award 2018 IEEE Signal Processing Society Young Author Best Paper Award (coauthor) Advising and Grants: Dr. Zhang has served as Principal or Co-Principal Investigator on over $6 million in research funding from the NSF, AFRL, ONR, and DARPA. While student advisees are not listed, his leadership of the ASP Lab suggests active mentorship of graduate researchers. He contributes extensively to the academic community as an associate editor for IEEE Transactions on Signal Processing and editor for Signal Processing journal, and serves on key IEEE technical committees. Labs and Teams: He directs the Advanced Signal Processing (ASP) Lab at Temple University, which focuses on developing novel algorithms for real-world applications in radar, communications, and navigation. Previously, he led the Wireless Communications and Positioning Lab and the RFID Lab at Villanova University.

• Glaciology
• Remote Sensing
• Geodesy
• +۳ مورد دیگر

Tobias Bolch is a full Professor at the Institute of Geodesy, Graz University of Technology (TU Graz), Austria, specializing in cryospheric research with a focus on High Mountain Asia and the Tibetan Plateau. His work integrates advanced geodetic and remote sensing methodologies to address critical climate change impacts on glaciers and related systems. His research spans: Glacier dynamics and mass balance monitoring using InSAR and optical satellite data Rock glacier kinematics and permafrost interactions Glacial lake evolution and outburst flood hazards Climate-glacier-hydrology linkages in Central Asian river basins Long-term cryosphere reconstruction using historical satellite archives Analysis of his 2023-2025 publications reveals dominant trends in quantifying ice loss acceleration, particularly from lake-terminating glaciers, and the application of multi-sensor approaches (Sentinel, ASTER, UAV) for decadal-scale change detection. His work consistently emphasizes the hydrological consequences of glacier retreat for downstream water security across High Mountain Asia. No scientific awards or specific grant programs were documented in the provided materials. While student supervision details are absent, his position at TU Graz's Institute of Geodesy indicates active mentorship within geospatial and cryospheric research programs. His homepage (https://ifg.tugraz.at) serves as the primary hub for research dissemination through the university's PURE portal.

• Electromagnetic Compatibility (EMC)
• Lightning Electromagnetics
• Electromagnetic Time Reversal
• +۴ مورد دیگر

Farhad Rachidi-Haeri is a Titular Professor and Head of the Electromagnetic Compatibility (EMC) Group at EPFL. His expertise spans EMC research, lightning electromagnetics, time reversal techniques, and fault location in power systems. He has led the EMC Group since the 1980s, with funding from the Swiss National Science Foundation, European Union, and private sector collaborations. His work involves international partnerships with institutions like the University of Toronto and KTH. Education: PhD in Electrical Engineering from EPFL (1991), M.S. from EPFL (1986). Roles: President of Swiss National Committee of URSI (2012–2020), Editor-in-Chief of IEEE Transactions on EMC (2013–2015), and member of the Academy of Sciences of Bologna Institute (2019). Research Focus: Lightning interaction with infrastructure, electromagnetic field modeling, time reversal applications for fault detection, and high-frequency transient analysis. His work bridges theoretical physics and engineering, addressing challenges in power systems, lightning protection, and aerospace. Awards: IEEE EMC Technical Achievement Award (2005), Berger Award (2016), and Distinguished Honorary Professor at Tsinghua University (2024). Over 400 peer-reviewed papers and 500 conference contributions reflect his prolific research output. Labs/Teams: Leads the EMC Laboratory at EPFL, focusing on experimental and numerical studies of electromagnetic phenomena. Collaborates with global networks on projects like Laser Lightning Control and structural lightning protection for wind turbines.

Peter K. Kitanidisمشاهده پروفایل

استاد

• Groundwater Flow
• Hydrologic Modeling
• Inverse Problems
• +۳ مورد دیگر

Peter K. Kitanidis is a Professor in the Department of Civil and Environmental Engineering and the Institute for Computational and Mathematical Engineering at Stanford University . His research focuses on groundwater flow , hydrologic forecasting , and stochastic inverse modeling , with applications to pollutant remediation and CO₂ storage monitoring . Education : Diploma, National Technical University of Athens (1974) M.S., MIT (1976) Ph.D., MIT (1978) Research Interests : Groundwater modeling and contaminant transport Hydraulic tomography and aquifer characterization Stochastic methods for uncertainty quantification Bioremediation and enhanced in-situ pollutant decay Dilution and mixing processes in heterogeneous media Real-time river flow forecasting Scientific Awards : L.G. Straub Award (1979) W.L. Huber Research Prize (1994) ISI Highly Cited Researcher (2001) AGU Hydrologic Sciences Award (2011) ASCE Pioneers in Groundwater Lecturer (2011) Advising and Grants : Advised 20+ PhD and MS students (1978–2018) Principal investigator on NSF, EPA, and DOE-funded projects Developed software for groundwater data analysis and CO₂ monitoring Contributed to bioremediation protocols and hydraulic tomography algorithms Labs and Teams : Kitanidis Laboratory for groundwater crisis solutions Collaborated with Oak Ridge National Laboratory and Stanford Hydrogeology Group Mentored postdocs (2000–2017) in reactive transport and inverse modeling

Amilcare Porporatoمشاهده پروفایل

استاد

• Ecohydrology
• Soil-Atmosphere Interaction
• Hydrologic Time Series
• +۲ مورد دیگر

Amilcare Porporato is the Thomas J. Wu '94 Professor of Civil and Environmental Engineering at Princeton University, with joint appointment at High Meadows Environmental Institute. His research integrates hydrology, ecology, and thermodynamics to study soil-water interactions and sustainable resource management. Education includes: Ph.D. Polytechnic of Milan (1996) M.S. Civil Engineering, Polytechnic of Milan (1992) Research explores nonlinear hydrologic systems, soil moisture dynamics, ecohydrology, and environmental complexity using theoretical and experimental approaches. His work advances understanding of water-biota interactions across scales from pore-level processes to landscape evolution. Honors and Awards: Hydrologic Sciences Award, AGU Borland Lecturer American Geophysical Union Fellow Inaugural Landolt Chair, EPFL Teaches courses on Environmental Thermodynamics (ENV 385/CEE 385) and Ecohydrology (CEE 587/ENV 587).

• Multiphase Flow in Porous Media
• Phase-Field Modeling
• Reactive Transport
• +۶ مورد دیگر

Xiaojing (Ruby) Fu is an Assistant Professor of Mechanical and Civil Engineering at the California Institute of Technology and a William H. Hurt Scholar (2024-present). Her research focuses on multiphase fluid mechanics in porous media, integrating theory, computation, experiments, and field observations to address geoscience and engineering challenges. Her educational background includes: B.S. in Engineering from Clarkson University (2011) M.S. from Massachusetts Institute of Technology (2015) Ph.D. from Massachusetts Institute of Technology (2017) Professor Fu's research centers on cryosphere hydrology, subsurface engineering, and phase transitions in porous media. She investigates multiphase flow dynamics in contexts like permafrost thaw, snow metamorphism, and carbon sequestration using phase-field modeling and experimental techniques. Her work bridges fundamental physics with applications in environmental resilience and energy systems, emphasizing predictive capabilities for large-scale phenomena through simplified multiscale theories. Analysis of her 15 most recent publications reveals intense focus on cryosphere processes (snow, permafrost) using advanced phase-field modeling and fiber-optic sensing. Key trends include freezing infiltration patterns, meltwater transport in layered snow, and seismic monitoring of soil moisture. Her work increasingly integrates field validation with computational models for environmental applications like drought monitoring and carbon sequestration. Her scientific recognition includes: William H. Hurt Scholar (2024) Professor Fu actively mentors graduate students, as evidenced by qualified students in her research group. She teaches core courses including Thermal Science (ME 11 abc) and Computational Methods for Flow in Porous Media (ME/CE/Ge/ESE 146), training students in both theoretical foundations and applied techniques for subsurface flow problems. She leads the Fu Research Group on Mechanics and Physics of Porous Media Flow, which develops multiscale theories to predict large-scale environmental and energy system behaviors. The group combines mathematical modeling, laboratory experiments, and field observations to address problems in geologic carbon storage, cryosphere dynamics, and subsurface resource management, with recent emphasis on climate change impacts and monitoring technologies.

Mary Silberمشاهده پروفایل

استاد

• Dynamical Systems
• Bifurcation Theory
• Climate Modeling
• +۳ مورد دیگر

Mary Silber is a Professor in the Department of Statistics and the College at the University of Chicago, and serves on the Executive Committee of the Committee on Computational and Applied Mathematics (CCAM). Her research focuses on dynamical systems and bifurcation theory, with applications to climate science, ecological dynamics, and pattern formation. She investigates tipping points in climate systems and self-organized vegetation patterns in drylands, exploring mathematical mechanisms behind abrupt transitions and noise-driven instability. Her work bridges theoretical mathematics with real-world phenomena, including Arctic sea ice melt processes and feedback mechanisms in ecosystems. Notable grants include a $50M interdisciplinary initiative between Northwestern and UChicago for life sciences data science and a collaborative Institute for Foundational Data Science. Silber’s contributions span bifurcation theory, spatio-temporal chaos, and control of unstable dynamical systems, with a focus on symmetry-breaking and model reduction techniques. Her recent research emphasizes resilience in dryland ecosystems under climate variability and the role of percolation thresholds in Arctic melt pond dynamics. Despite no formal student listings, her work is supported by interdisciplinary collaborations and federal grants in applied mathematics and environmental science.

• Radar System Design
• Signal Processing
• MIMO Radar
• +۶ مورد دیگر

Professor Kim Eun-hee is a faculty member in the Department of Defense Systems Engineering at Sejong University, specializing in advanced radar technologies and signal processing. Her work bridges theoretical research and practical applications in defense systems. Ph.D. in Mechanical Engineering (2004), KAIST M.Sc. in Engineering (1996), KAIST B.Sc. in Precision Engineering (1994), KAIST Her research focuses on radar system design, including airborne active phased array radar, automotive radar, broadband noise radar, and over-the-horizon radar. She explores waveform optimization, MIMO architectures, and signal processing algorithms to enhance radar performance in complex environments. Publications highlight her expertise in MIMO radar configurations, Doppler-insensitive waveforms, and machine learning integration for signal analysis. She leads industry-academic collaborations with organizations like Hanwha Systems and LIG Nex1. She contributes to technical committees, including the Sensor and Signal Processing Division of the Korean Society of Military Science and Technology. Her laboratory (Defense Radar Technology Laboratory) focuses on radar design, signal processing, and sensor integration.

Aydin Babakhaniمشاهده پروفایل

استاد

• Terahertz (THz) Technology
• Wireless Sensors
• Medical Implants
• +۵ مورد دیگر

Aydin Babakhani is a Professor in the Department of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA), affiliated with the College of Life Sciences. He directs the Integrated Sensors Laboratory (ISL), which focuses on the design and implementation of integrated sensors and systems. His research spans high-speed wireless communication, terahertz technology, medical implants, radar systems, and industrial monitoring solutions. Research Interests: Prof. Babakhani's work integrates silicon-based technologies with applications across multiple domains. Key areas include: Silicon mm-Wave/THz transceivers and on-chip antennas for communication and sensing Wirelessly powered medical implants for biopotential monitoring and neural stimulation THz radar systems for micrometer-resolution imaging and vibration detection Energy harvesting solutions for batteryless sensors in industrial and biomedical applications CMOS-based optoelectronic systems and photonic computing accelerators His recent publications (2021-2025) demonstrate a strong emphasis on terahertz systems, wireless power transfer, and miniaturized medical electronics. Over 80% of his latest articles involve silicon-integrated solutions for biomedical implants or THz sensing, with emerging focus on AI-accelerated photonic computing and multi-Gbps wireless links.

• Earthquake Early Warning
• Real-Time Seismology
• Seismic Instrument Design
• +۶ مورد دیگر

Dr. John Francis Clinton is the Director of Seismic Networks and Head of the Earthquake Monitoring Section at the Swiss Seismological Service (SED), ETH Zurich. He leads the Marsquake Service for NASA's InSight mission and oversees Switzerland's broadband and strong-motion seismic networks. His expertise spans earthquake early warning systems, seismic instrumentation, and glacial seismology. Clinton is also a Co-Investigator on the Mars InSight mission and involved in international projects like EPOS and RAMSIS. Education PhD in Civil Engineering (Minor in Geophysics), California Institute of Technology (2004) MSc in Civil Engineering, California Institute of Technology (1998) BEng in Civil Engineering, University College Dublin (1997) Research Interests Dr. Clinton focuses on real-time seismology, seismic instrument design, structural health monitoring, and glacial seismology. His work bridges engineering applications with geophysical data analysis, particularly in earthquake early warning systems and induced seismicity studies. He collaborates internationally on projects such as the Valais Near Fault Observatory and Nicaragua’s Earthquake Early Warning development. Publications Overview His 15 most recent papers (2011–2015) highlight advancements in seismic network optimization, Marsquake detection algorithms, and glacial icequake mechanisms. Key themes include improving early warning accuracy, understanding subglacial dynamics, and validating high-rate GPS for structural monitoring. Awards & Memberships Member, Swiss Academy of Sciences (since 2008) Member, IRIS Quality Assurance Advisory Committee (since 2013) Chair, European Integrated Data Archives (EIDA) (2013–2015) Labs & Teams Clinton directs the SED’s Earthquake Monitoring team and collaborates with ETH Zurich’s Geophysics Masters Program. His group manages Switzerland’s seismic networks and leads the Marsquake Service, which analyzes InSight lander data for Martian seismic events.