As a doctoral candidate in the Electrical and Computer Engineering department at Virginia Tech, I am privileged to work with Dr. Lamine Mili. My research focus lies in the areas of robust estimation, uncertainty quantification, Bayesian inference, and Koopman operator. I am particularly interested in exploring the vast potential of interpretable Gaussian processes combined with the robust estimation theory. My ultimate goal is to develop robust and trustworthy models for diverse applications, from power systems steady state and dynamic state estimation to astrophysics, in order to advance our understanding of complex systems and improve uncertainty cognizant decision-making. I began my Ph.D. journey in January 2021, after completing a master's degree in the same lab in December 2020. During my master's program, I focused on power systems and advanced machine learning. Prior to my graduate studies, I earned my bachelor's degree from the College of Engineering in Pune, India in 2017.

News

1. Nov 2023: Paper got accepted at ISGT NA 2024.
2. Oct 2023: Gave a talk on "Data-driven Time-series Uncertainty Quantification Models" at UT Austin.
3. May 2023: Started internship at NREL: Quantifying measurement uncertanty in Koopman operator.
4. March 2023: Conference paper selected for best paper session at the IEEE PES GM 2023.
5. Jan 2023: Journal paper accepted at the IEEE transactions on Power Systems.