I am a 5th year PhD candidate in Geophysics at the Department of Earth and Environmental Sciences at University of Minnesota, Twin Cities, USA.

For my PhD I am working under supervision of Dr. Ikuko Wada on analysis of long-term stresses and deformation in the forearc region of subduction zones, using finite element modeling and geophysical observations.
I have also worked on applying scientific machine learning approaches such as physics informed neural networks and fourier neural operators to problems in Geosciences.

Additionally I have worked on zero-shot convolution neural networks for geophysical data denoising such as GPR and seismic. Findings from this work is under review.

Recently I have worked on a Bayesian Neural Network algorithm for estimating uncertainty in system criticality for maintenance and reliability scheduling expanding on my previous work from BITS Pilani as a research student.

I consider myself a scientist before a geo-scientist. Hence, I am interested in solving real life problems even if they are simple. Leveraging the ongoing research in the field of machine learning I wish to make contributions by developing machine learning models, making them deployable and accessible for the researchers in the geoscience community.