Find Academic Supervisors

Armando Espindola CarmonaView profile

Research Fellow

• Geophysics
• Seismic Tomography
• Waveform Inversion
• +3 more

Armando Espindola Carmona is a Research Fellow at Princeton University , currently serving as a Postdoctoral Research Associate in the Theoretical & Computational Seismology and Global Geophysics groups. His work focuses on seismic tomography, numerical simulations of wave propagation, and waveform inversion. He is affiliated with Guyot Hall, where he can be reached at office 314 via phone (609-258-3933) or email. Education: Ph.D. in Earth Science and Engineering from King Abdullah University of Science and Technology (KAUST) M.S. in Geophysics from Universidad Nacional Autónoma de México (UNAM) B.E. in Geophysics from UNAM Research Interests: Full-Waveform Inversion (FWI) techniques, particularly anelastic FWI with source encoding 3-D seismic wave propagation models Global and regional-scale seismic tomography Marine seismic data analysis with multicomponent ocean-bottom-node systems Trade-off analysis in inversion methodologies His recent work addresses critical challenges in crustal and mantle structure imaging, including the Red Sea's Zabargad Fracture Zone and the Arabian plate. He also investigates earthquake mechanisms, such as the 2023 Kahramanmaraş-Syria seismic events. Publications: His articles emphasize anelastic FWI, marine acquisition strategies, and earthquake dynamics. Key themes include optimizing global FWI workflows, analyzing inversion resolution, and applying adjoint tomography to volcanic complexes like Colima. Grants/Advising: No information on grants, advising, or mentorship roles is explicitly provided in the text. Labs/Teams: Engages with the Theoretical & Computational Seismology and Global Geophysics groups at Princeton, focusing on computational seismology and field deployments like the Red Sea Ocean Bottom Seismometer network.

Eran TreisterView profile

Assistant Professor

• Computational Science
• Scientific Computing
• Numerical Methods
• +8 more

Eran Treister is an Assistant Professor at the Ben Gurion University of the Negev in the Department of Computer Science. He completed his postdoctoral fellowship at the University of British Columbia (2014-2016) and earned his PhD from the Technion in 2014 under Prof. Irad Yavneh. His research spans computational science, numerical methods, and machine learning, with a focus on: Scalable algorithms for inverse problems Graph Neural Networks (GNNs) optimization Seismic and optical imaging via PDE solvers Low-precision deep learning acceleration Multilevel preconditioning techniques Recent work explores: Graph neural networks for PDEs with adaptive meshes Deep learning approaches to Helmholtz equation modeling 3D shape reconstruction via parametric level sets He serves on editorial boards: SIAM Journal on Scientific Computing (2024-) Copper Mountain Conference on Multigrid Methods (2025) International Conference on Machine Learning (ICML) as Area Chair (2025) Current teaching: Optimization Methods for Data Science (Spring 2025) Deep Learning Mini-Project (Winter 2024/5) Advanced Numerical Optimization (Spring 2025)

• Geophysics
• Seismology
• Earthquake Science
• +4 more

Debora Presti is a Full Professor in the Scientific-Disciplinary Sector GEO/10 "Solid Earth Geophysics" (Competition Sector 04/A4) at the University of Messina. She has been actively involved in geophysics research since her 2001 Bachelor's degree in Physics (University of Messina) and obtained her PhD in Geophysics for the Environment and Land from the same university in 2006. Author of 44 publications (SCOPUS, 2023) h-index: 21 with 1125 citations Published 4 volumes and 2 popular science articles Project Manager for INGV-DPC/S1 2014/2015 on seismogenic potential of Italy Research Focus: Seismotectonic analysis of Southern Italy, earthquake localization methodologies, focal mechanism calculation, seismic tomography for crust-upper mantle characterization, and tsunami risk assessment. Her work integrates geodynamic perspectives with stress field modeling. Public Engagement: Organized and participated in 10+ outreach activities (2019-2024) including school collaborations, public lectures, and scientific dissemination initiatives like "Collana editoriale La condivisione dei saperi".

Scott KeatingView profile

Lecturer

• Seismic Inversion Methodology
• Uncertainty Quantification
• Numerical Optimization
• +4 more

Dr. Scott Keating is a Lecturer at ETH Zurich’s Department of Earth and Planetary Sciences (D-EAPS), affiliated with the Institute of Geophysics. His research focuses on seismic inverse problem methodologies, particularly uncertainty quantification, numerical optimization, and the development of automated workflows for regional inversion updates. Current projects include full-waveform inversion of ambient noise measurements and CO2 storage monitoring using advanced sensor technologies like distributed acoustic sensing (DAS) and accelerometers. His work integrates cutting-edge computational methods, such as probabilistic inversion frameworks and adjoint-based optimization, to address challenges in subsurface imaging and parameter estimation. Applications span environmental seismology, carbon sequestration, and reservoir characterization, with a strong emphasis on practical, cost-effective solutions for real-world problems such as CO2 storage validation. Publications highlight contributions to elastic full-waveform inversion (FWI), including multiparameter analysis using combined geophone and DAS data, and innovative techniques like targeted nullspace shuttling to enhance inversion reliability. His research also addresses data sparsity and modeling uncertainties, advancing methodologies for robust subsurface monitoring and decision-making.

• Spatio-temporal statistics
• Computational statistics
• Earth sciences
• +5 more

Jo Eidsvik is a Professor at the Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU). He holds a MSc in applied mathematics from the University of Oslo (1997) and a PhD from NTNU (2003). His research focuses on spatio-temporal statistics, computational statistics, and their applications in Earth sciences, including geophysics and oceanography. He leads projects like the Center for Geophysical Forecasting (SFI-CGF) and Maritime Autonomous Sampling and Control (MASCOT). Eidsvik has supervised over 60 graduate students and is an associate editor for *Mathematical Geosciences* and *Statistics and Computing*. His work bridges theory and practice, addressing challenges in data assimilation, value of information analysis, and autonomous systems for environmental monitoring. **Education & Background**: MSc (University of Oslo), PhD (NTNU). Industry experience includes roles at Statoil and the Norwegian Defense Research Establishment. Visiting scholar at Stanford University, Duke University, and SAMSI. **Research Themes**: Spatio-temporal modeling, machine learning for irregular time series, and decision analysis in geological contexts. Key projects include geophysical forecasting, CO₂ storage monitoring, and autonomous underwater vehicle (AUV) sampling strategies. His book *Value of Information in the Earth Sciences* (Cambridge Press) synthesizes methodologies for optimizing data-driven decisions. **Awards & Recognition**: While no specific awards are listed, his editorial roles and project leadership reflect scholarly impact. His work emphasizes interdisciplinary collaboration, with applications in climate science, energy systems, and robotics. **Advising & Grants**: Supervised 60+ MSc students and 12 PhD students. Active in NTNU’s Physics and Mathematics program and Industrial Mathematics initiatives. Projects funded by SFI, EU, and industry partners. **Teams & Labs**: Involved with NTNU’s GEOPARD (data assimilation in geological models), Havvarsel (oceanographic data assimilation), and ML4ITS (machine learning for irregular time series). Collaborates with international institutions like Stanford and Duke.

Houssem HaddarView profile

Researcher

• Inverse Problems
• Applied Mathematics
• Electromagnetic Scattering
• +5 more

Houssem Haddar is a Research Director at the Applied Mathematics Unit (UMA) of ENSTA Paris , a leading institution in applied mathematics and inverse problems. He is a key figure in the development of theoretical and computational methods for wave scattering and inverse problems, with applications spanning medical imaging, non-destructive testing, and industrial engineering. Research Focus: Inverse scattering theory, transmission eigenvalues, eddy current tomography, diffusion MRI models, and numerical methods for wave propagation. Collaborations: Works extensively with institutions like LOA, U2IS, and external researchers across France and internationally. Publications highlight his expertise in solving complex inverse problems using innovative mathematical frameworks, including duality principles, level-set methods, and asymptotic models. His work bridges theoretical advancements with practical applications in seismic imaging, material characterization, and electromagnetic scattering.

• Seismology
• Global Seismology
• Earth's Deep Interior
• +7 more

Dr. Su Talavera Soza is a Researcher at the Faculty of Geosciences, University of Utrecht, specializing in the DES - Seismology group. Their work bridges seismology, machine learning, and geophysical inversion to study Earth's crust, mantle, and inner core. They employ seismic normal modes and surface waves with advanced instruments like superconducting gravimeters and ocean bottom seismometers. Key Expertise Areas: Seismology, Global Seismology, Earth's Deep Interior, Machine Learning, Inverse Problems, Tomography Skills: Python, Fortran, MATLAB, Data Analysis, Visualization Current research focuses on physics-informed machine learning for full-waveform inversion and planetary-scale structure analysis. They collaborate internationally across the USA and Europe, contributing to 15+ publications between 2020-2025, including high-impact journals like Nature and Nature Geoscience . Notably, they developed the FrosPy Python toolbox for normal mode seismology. While no formal awards are listed, their work on mantle attenuation models and inner core dynamics has been widely shared (214+ X posts) and discussed in Wikipedia. They hold a 2021 PhD from Utrecht University titled Observing seismic attenuation in the Earth’s mantle and inner core using normal modes , supervised by A. Deuss.

• Seismology
• Subduction Zones
• Mantle Dynamics
• +4 more

Dr. Yajian Gao is a Researcher at the Geophysics group of the Karlsruhe Institute of Technology (KIT), focusing on seismic waveform inversion and subduction zone geodynamics. His work employs spectral element methods for 2D/3D modeling of crustal and upper mantle structures. Institution: Karlsruhe Institute of Technology (KIT) Department: Geophysics group at Geophysical Institute Research Interests: His studies center on subduction zones (Central Andes, Central Asia), mantle hydration/dehydration processes, and distributed deformation analysis using passive seismic data and ambient noise interferometry. Publication Trends: Recent articles emphasize full waveform inversion applications, mantle dynamics, and microseism source characterization, reflecting expertise in computational geophysics and tectonic-geodynamic interactions.

Lu ZhangView profile

Assistant Professor

• Numerical Analysis of Partial Differential Equations (PDEs)
• Discontinuous Galerkin Methods
• Computational Mathematics
• +5 more

Lu Zhang is an Assistant Professor in the Department of Computational Applied Mathematics and Operations Research at Rice University. She joined Rice in 2023 after serving as the Ju Tang Chu and Wu Ping Chu Assistant Professor at Columbia University's Department of Applied Physics and Applied Mathematics. Zhang holds a Ph.D. in computational and applied mathematics from Southern Methodist University (2020) and has conducted summer research at Argonne National Laboratory (2018) and Lawrence Livermore National Laboratory (2019). Her research focuses on numerical and theoretical analysis of partial differential equations (PDEs), particularly developing high-order discontinuous Galerkin methods for PDEs with physical and biological applications. Key areas include advective wave equations, seismic imaging, chemotaxis models, population dynamics, and inverse problems. Her work emphasizes energy-stable, computationally efficient algorithms and their theoretical underpinnings. Zhang's recent publications (2021–2024) explore advanced numerical methods for wave equations, electromagnetic systems, and elastic media, with applications in geophysics, structural mechanics, and crime modeling. Her methods address challenges in high-order accuracy, stability, and computational efficiency across diverse scientific domains. No scientific awards or grants are explicitly mentioned in the provided text. She currently advises no listed students but has extensive experience in collaborative research through national laboratory partnerships.

Michele PaulattoView profile

Research Fellow

• Marine Geophysics
• Tectonics
• Volcano Seismology
• +3 more

Michele Paulatto is a NERC Independent Research Fellow at Imperial College London's Department of Earth Science & Engineering within the Faculty of Engineering. His research focuses on active volcanic and tectonic processes at plate margins, integrating geophysical imaging, rock physics, and laboratory experiments. He holds a PhD in Marine Geophysics from the University of Southampton and has held postdoctoral positions at the University of Oxford and Géoazur in France. His work includes studies on the Lesser Antilles subduction zone, seismic imaging of magma systems, and fluid dynamics in subduction zones. Education: PhD in Marine Geophysics, National Oceanography Centre Southampton, 2011 MSc in Physics, University of Trieste, Italy, 2007 Research Interests: Paulatto specializes in marine geophysics, tectonics, volcano seismology, and seismic tomography. His current project explores magma/water interactions in oceanic lithosphere using advanced imaging techniques. Recent studies include deformation mechanisms in the Lesser Antilles, fluid circulation impacts on seismicity, and imaging magma chambers beneath volcanoes like Montserrat and Santorini. Scientific Contributions: He has pioneered seismic tomography methods to map subduction zone processes, including slab dehydration and mantle wedge dynamics. His work on the 2016 Ecuador earthquake highlighted the role of subduction relief in megathrust slip. Paulatto also investigates hydrothermal systems at mid-ocean ridges and volcanic microseismicity as precursors to eruptions. Grants & Awards: Recipient of the AXA Postdoctoral Fellowship (2014-2016) and currently holds a NERC Independent Research Fellowship. He leads a PhD project funded by the SSCP DTP and SmartSolo on teleseismic imaging of active volcanoes. Labs/Teams: Collaborates with international teams including the National Oceanography Centre, Géoazur, and the University of Oxford. Active in field experiments like the SEA-CALIPSO volcano imaging project at Montserrat and seismic surveys in the Mid-Atlantic Ridge.

• Petroleum Geoscience
• Reservoir Engineering
• Seismic Data Analysis
• +3 more

Asghar Shams is an Associate Professor at Heriot-Watt University's School of Energy, Geoscience, Infrastructure and Society, affiliated with the Institute for GeoEnergy Engineering. His research focuses on reservoir characterization, seismic data analysis, and application of artificial intelligence in petroleum engineering. He has extensive experience in carbonate reservoir modeling, fluid flow dynamics, and integration of geophysical data with reservoir engineering workflows. Research interests include reservoir simulation, production optimization, fracture network modeling, and machine learning applications. His work spans global basins like the Sirt Basin (Libya), Gulf of Mexico, and Middle East carbonate systems. He has published over 52 peer-reviewed articles and actively participates in international conferences such as SEG and EAGE. Professional activities include membership in committees at Imperial College London and Italy's Istituto Nazionale di Oceanografia e di Geofisica Sperimentale. His research emphasizes bridging geoscience and engineering through advanced computational methods.

Weihua SuView profile

Associate Professor

• Aeroelasticity
• Structural Dynamics
• Flight Dynamics and Control
• +15 more

Dr. Weihua Su is an Associate Professor of Aerospace Engineering and Mechanics at The University of Alabama , where he also serves as Associate Department Head and Director of Undergraduate Programs. He directs the Aeroelasticity and Structural Dynamics Research Laboratory . Education: Ph.D. in Aerospace Engineering, University of Michigan, 2008 M.S. in Aerospace Engineering, Beijing University of Aeronautics and Astronautics, 2002 B.S. in Aerospace Engineering, Beijing University of Aeronautics and Astronautics, 2000 Research Focus: Dr. Su’s expertise lies at the intersection of aeroelasticity, structural dynamics, and advanced control theory . His work spans nonlinear aeroelastic modeling , robust control of flexible aircraft , and Urban Air Mobility (UAM) vehicle design. Recently, he has integrated machine learning and deep learning techniques—including generative AI & LLMs —to enhance flight control and diagnostics. Core topics include gust alleviation , vibration suppression , energy harvesting multifunctional structures , and real-time hybrid simulations . Recent Publication Trends: Over 2023-2025, Dr. Su’s publications emphasize nonlinear model predictive control (NMPC) for Urban Air Mobility aircraft , addressing gust disturbances , control effector failures , and trajectory tracking under uncertainty . Concurrently, he has leveraged deep learning to advance ultrasound computed tomography for material characterization, reflecting a cross-disciplinary thrust into AI-driven diagnostics. Scientific Awards & Honors: ASME/Boeing Structures and Materials Award (2011) NASA Group Achievement Award (2018) Elevated to AIAA Associate Fellow (2023/2024) Funding & Collaborations: His research has been continuously supported by NASA Aeronautics Research Mission Directorate , NASA Ames Research Center , NASA Kennedy Space Center , and industry partners in aerospace and automotive sectors. He holds leadership roles on the AIAA Structural Dynamics Technical Committee and the ASME Aerospace Division Executive Committee . Laboratory & Teams: As director of the Aeroelasticity and Structural Dynamics Research Laboratory , Dr. Su mentors graduate researchers and oversees experimental facilities dedicated to nonlinear aeroelastic testing, multifunctional structures, and advanced control prototyping for next-generation flexible aircraft and UAM platforms.

• Seismic Hazard Analysis
• Crustal Scale Tomography
• Seismic Wave Propagation
• +4 more

Dr. Daniel Bowden is a Lecturer at the Department of Earth and Planetary Sciences (D-EAPS) at ETH Zurich, where he leads research in seismic hazard analysis and crustal tomography. He holds a PhD from Caltech and a Bachelor’s degree from UCSD, with prior experience at the U.S. Geological Survey. His work focuses on improving 3D crustal structure understanding and seismic wave propagation modeling using advanced techniques like distributed acoustic sensing (DAS) and fiber-optic technologies. Research Interests: Seismic hazard mitigation in sedimentary basins Development of novel DAS-based seismic sensors for urban and cryosphere environments Computational methods for ambient noise inversion and subsurface imaging Recent Contributions: Advancing urban DAS data workflows for shallow subsurface velocity modeling Optimizing computational domains for full waveform ambient noise inversion Calibrating DAS systems in complex near-source environments Laboratory Affiliation: Member of the Seismology and Wave Physics group at ETH Zurich’s Institute of Geophysics.

Hejun ZhuView profile

Associate Professor

• Seismology
• Structural Geology
• Geophysics
• +5 more

Dr. Hejun Zhu is an Associate Professor of Geosciences at The University of Texas at Dallas (UTD), affiliated with the School of Natural Sciences and Mathematics. He holds a PhD in Geoscience from Princeton University (2013), following a Master’s in Geophysics from Peking University and a Bachelor’s in Geology from Sun Yat-sen University. His research focuses on structural seismology, exploration seismology, and earthquake seismology, with specialties in seismic full-waveform inversion, mantle dynamics, and viscoacoustic modeling. Key professional milestones include the NSF CAREER Award (2021) and the J. Clarence Karcher Award (2019). His work has led to breakthroughs such as imaging 3D mantle flows in subduction zones and developing advanced seismic models for North America. Dr. Zhu’s research is funded by major grants, including a $536,729 NSF award for multi-parameter seismic modeling. His publications span high-impact topics like seismic monitoring of groundwater changes in Yellowstone, viscoacoustic reverse-time migration algorithms, and structural analysis of cratonic lithosphere. He advises doctoral students in geosciences, with notable advisees including Jaewook Lee, Jidong Yang, and Mengli Zhang. Dr. Zhu’s lab integrates computational seismology and field data to advance understanding of Earth’s subsurface processes.

Mrinal SenView profile

Professor

• Geophysics
• Seismic Imaging
• Machine Learning
• +5 more

Mrinal Sen is a Professor at The University of Texas at Austin, holding the Shell Companies Foundation Centennial Chair in Geophysics. He is affiliated with the Jackson School of Geosciences, specifically the Department of Earth and Planetary Sciences and the Institute for Geophysics. Sen is a pioneer in machine learning applications for seismic imaging and has developed methods combining physics-based models with computational techniques. He was named the SEG’s 2024-2025 Distinguished Instructor Short Course (DISC) lecturer for his course on physics and data-driven seismic analysis. Education: PhD from University of Hawaii at Manoa, M.Sc. from IIT Dhanbad. His research focuses on seismic wave propagation, inversion, and uncertainty quantification, with emphasis on unconventional reservoirs and physics-assisted machine learning. He led the development of the Jackson School’s machine learning certificate program in geosciences. Research Interests: Exploration geophysics, seismology, full waveform inversion (FWI), Bayesian methods, and high-performance computing. His work bridges cutting-edge computational techniques with traditional geophysical principles. Key Achievements: Virgil Kauffman Gold Medal (SEG, 2018), SEG Honorary Membership, Distinguished Educator Award (UT Austin). Recent Work: Hybrid quantum neural networks for seismic inversion, starting-model-independent FWI algorithms, and trans-dimensional Bayesian inversion. Global Outreach: DISC course presentations across 8+ locations including Houston, Norway, France, India, and virtual platforms. Grants & Labs: Active in research funded by industry and academic partnerships, leading the Sen Research Group focused on seismic imaging and machine learning integration.