I am currently the Stephen Timoshenko Distinguished Postdoctoral Fellow in the Mechanics and Computation Group at Stanford University. Earlier I completed my Ph.D. in the Aerospace and Mechanical Engineering department at USC under the supervision of Prof. Assad Oberai.
My research interest lies at the intersection of physics-based and data-driven modeling, deep learning, inverse problems, and uncertainty quantification with applications to computational science and engineering, computer vision, and medical imaging. I am particularly interested in the question of how to optimally combine physics-guided models with modern machine learning algorithms to develop more data efficient and accurate hybrid models.
PhD in Mechanical Engineering
University of Southern California
MTech in Applied Mechanics
Indian Institute of Technology, Delhi
BE in Mechanical Engineering
L. D. College of Engineering, Ahmedabad
Feb 2022: New preprint on Efficacy and Generalizability of Conditional GANs for Solving Physics-based Bayesian Inverse Problems
Dec 2021: Will present a poster at Deep inverse workshop at NeurIPS on Conditional GAN-based Bayesian inversion.
Dec 2021: Giving a talk at AGU21 on efficient subsurface inversion using deep learning and multi-fidelity modeling.
Nov 2021: New preprint on Multi-fidelity Hamiltonian Monte Carlo method - to be presented at AAAI'21 (symposium on science guided AI).
Oct 2021: Giving an invited talk at the ERE gradute seminar, School of Earth, Energy, and Environmental Sciences, Stanford.