Welcome to my personal webpage
About Me
I am an Associate Professor of Geophysics at King Fahd University of Petroleum and Minerals (KFUPM), where I lead the Smart Earth Exploration and Monitoring (SEEM) research group. My research lies at the crossroads of geoscience, applied mathematics, and machine learning. I seek multidisciplinary collaborations in developing solutions to challenging geoscientific problems that allow a better understanding of the subsurface processes to ensure a sustainable, reliable, and affordable energy future for our planet.
Note: I have openings for graduate students and postdocs in my group. If you have a passion for innovation and research, and if you are interested in opportunities arising at the intersection of applied geoscience and machine learning, please get in touch.ociate
Education
Ph.D., Earth Science & Engineering, KAUST, 2015
M.S., Electronic Engg., Politenico di Torino, 2010
B.E., Electronic Engg. NED University of Engg. & Technology, 2008
Research Interests
Geophysical modeling
Inverse Problems
Induced seismicity
Physics-informed machine learning
Applied deep learning
Research Themes
SciML for geophysical modeling and inversion
Our ability to identify subsurface resources and use them in an environmentally friendly manner relies on the accuracy of geophysical imaging. Using advances in the field of scientific machine learning, I develop geophysical modeling and inversion algorithms focusing on improving their robustness, resolution, and accuracy.
Understanding and mitigating induced seismicity risk
Many industrial activities needed to sustain human society have the potential to induce earthquakes. I seek a better understanding of the subsurface processes in reservoirs leading to induced seismicity and manage the risk it poses by developing tools that enable real-time microseismic monitoring.
Machine learning for multidisciplinary geosciences
Extracting maximum value from geoscientific data requires novel approaches for combining data-driven methods, physical modeling, and algorithms capable of learning from limited, weak, or biased data. I collaborate with geoscientists from different sub-disciplines to address challenging geoscientific problems that are cross-cutting in nature, using advanced machine learning algorithms.
News
- 31/10/2022: Promoted to Associate Professor at KFUPM
- Our paper on Deep learning for low-magnitude earthquake detection using a multi-level sensor network in Groningen is now published in Sensors. Scripts and trained model are available here.
- I will be presenting our work on seismic tomography using PINNs at the AGU fall meeting. Dec. 13, 9:55 am (CST), S12B: Theoretical and Computational Advances in Seismology II Oral.
- Our paper on a versatile framework to solve the Helmholtz equation using PINNs is now published in GJI.
- Our paper on data-driven microseismic event localization is now published in IEEE TGRS.
- I am lead guest editing a special issue on applied machine learning in geophysical exploration and monitoring for Geophysical Prospecting. Consider submitting an article before March 1, 2022.
- Our paper on PINNeik: eikonal solution using PINNs is now published in Computers & Geosciences. Codes are available here.