Skip to content
GCC AI Research

Search

Results for "Wave-Equation Dispersion Inversion"

KAUST Ph.D. student wins best student presentation

KAUST ·

KAUST Ph.D. student Zhaolun Liu won the best student presentation at the 2017 Society of Exploration Geophysicists (SEG) Full-Waveform Inversion (FWI) and Beyond Workshop in Beijing. Liu's presentation was on "3D Wave-Equation Dispersion Inversion of Surface Waves," based on a paper co-authored with Jing Li and Professor Gerard Schuster. The paper describes a new method called wave equation dispersion inversion (WD) for inverting surface waves. Why it matters: This award recognizes KAUST's contributions to geophysics and seismic imaging, highlighting the university's research capabilities and access to high-performance computing.

Diffusion-BBO: Diffusion-Based Inverse Modeling for Online Black-Box Optimization

arXiv ·

This paper introduces Diffusion-BBO, a new online black-box optimization (BBO) framework that uses a conditional diffusion model as an inverse surrogate model. The framework employs an Uncertainty-aware Exploration (UaE) acquisition function to propose scores in the objective space for conditional sampling. The approach is shown theoretically to achieve a near-optimal solution and empirically outperforms existing online BBO baselines across 6 scientific discovery tasks.

Understanding the COVID wave

KAUST ·

KAUST professor David Ketcheson uses mathematical modeling to understand COVID-19 transmission. He applies differential equations to explain the progression of SARS-CoV-2, utilizing the SIR model to predict the spread. Ketcheson's analysis suggests that the reproduction number for COVID-19 could be as high as 5, emphasizing the need for social distancing. Why it matters: This highlights the role of mathematical modeling and data analysis in understanding and predicting the spread of infectious diseases, particularly in the context of pandemic response.

KAUST and the promise of reinvention

KAUST ·

J. Carlos Santamarina, a Professor of Earth Science and Engineering at KAUST, is researching geomaterial behavior and subsurface processes. His work focuses on energy geo-engineering, resource recovery, and geological storage of energy waste. He uses particle-level experiments, numerical methods, and monitoring systems to understand coupled thermo-hydro-bio-chemo-mechanically processes. Why it matters: This research contributes to energy sustainability and addresses global energy challenges through advanced geotechnology.

Groundwater composition as potential precursor to earthquakes

KAUST ·

KAUST researchers collaborated on a study in Iceland that found a correlation between changes in groundwater composition and earthquakes greater than magnitude 5. The study, published in Nature Geoscience, observed variations in dissolved element concentrations and stable isotopes prior to seismic events in 2012 and 2013. Earthquake prediction remains a challenge with differing views among scientists about its feasibility. Why it matters: Understanding earthquake precursors could lead to improved risk mitigation strategies for urban infrastructure in seismically active regions across the Middle East.