We apply integrated approaches that leverage a combination of geophysics, remote sensing, machine learning, numerical modeling, and GIS techniques to investigate a wide range of complex geological and environmental challenges. Our current research endeavors revolve around the utilization of geophysical data from spaceborne, airborne, and ground-based sources (including GRACE, gravity, magnetic, GPR, and resistivity data), as well as remote sensing data encompassing optical, microwave, and thermal sensors. We employ numerical modeling techniques, specifically rainfall-runoff models, and harness the power of machine learning methods like deep neural networks, gradient boosting machines, generalized linear models, and distributed random forests. Using these data and techniques, our research focus revolves around addressing a diverse range of geological, hydrological, geophysical, and environmental issues. Particularly, we are dedicated to studying the availability and variability of groundwater resources, along with the assessment of land deformation within arid and coastal environments. By integrating these multidisciplinary techniques, we aim to gain comprehensive insights into these complex problems and contribute to a deeper understanding of the intricate interactions between Earth’s systems.
We encourage you to examine the section titled “Research” to see the current projects that we are working on!.