Bio 

I am a Post Doctoral Research Associate at Los Alamos National Laboratory in T-5 Division at Advanced Network Science Initiative (ANSI). I am working with Deepjyoti Deka and Sidhant Misra.  

I have completed my Ph.D. from the School of Electrical and Electronic Engineering, Nanyang Technological University supervised by Hung D. Nguyen. Before joining NTU, I worked with Ashu Verma for my M.Tech in Energy Studies at Department of Energy Science and Engineering (previously Centre for Energy Studies), Indian Institute of Technology Delhi (IITD).

My primarily research focus on developing efficient algorithms and frameworks to address challenges power systems operations under uncertainty. I have extensive experience in employing Bayesian learning-based tools for various applications such as analytical power flow approximation, optimal power flow, and incorporating empirical battery models into optimal dispatch strategies. Notably, I recently introduced a novel kernel structure to effectively learn large-scale network flows with minimal samples, perform active learning and developed a multi-task learning framework to handle N-1 contingencies. My current research endeavors involve establishing probabilistic guarantees for Bayesian learning tools and devising systematic approaches to integrate prior power system physics knowledge into AI-based solutions. Furthermore, I am currently exploring the potential use of GPUs to enhance ML model training and validation, particularly in risk assessment for electrical markets using a combined ML+Optimization approach. Additionally, I am investigating the potential quantum advantage for addressing power system problems, further broadening my research scope.

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