I am a dedicated and highly accomplished researcher currently working as a Postdoctoral Researcher at New Mexico State University, USA. Prior to that, I completed my Ph.D. in Electrical Engineering with a specialization in Power & Energy Systems from the Indian Institute of Technology Kharagpur.

 

I serve as an Editorial Board Member for the American Journal of Electrical Power and Energy Systems (AJEPES) and as a member of the Topical Advisory Panel of the Journal of Engineering Research and Sciences (JENRS), significantly contributing to the academic community through my editorial and review roles. Additionally, as a member of IEEE and its diverse technical communities and societies, I actively contribute to advancing research and fostering innovation in power systems and smart grids. 

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My academic endeavors have culminated in numerous high-impact publications in reputable journals and award-nominated conference papers. My research spans a comprehensive range within power systems and smart grids, with a particular focus on the followings: ​

• Artificial Intelligence (AI) for Intelligent Operations in Smart Grids: Applying AI-driven methodologies—such as ML, DL, and RL—for intelligent decision-making, predictive maintenance, and operational optimization in smart grids. This includes real-time load forecasting, fault localization, and adaptive control for enhanced grid reliability and efficiency. 

• Digital Twin for Real-Time Monitoring and Predictive Analytics: Developing Digital Twin models of power systems that mirror real-time grid behavior using live data streams. These models support predictive diagnostics, event forecasting, and system-level simulations, enabling proactive grid management and risk mitigation strategies.

• Large Language Models (LLMs) for Grid Automation and Situational Awareness: Exploring the use of LLMs to process unstructured operational data, support natural language querying, and assist in human-in-the-loop decision-making. This includes applications in automated reporting, fault explanation, and bridging human-machine interfaces in smart grid environments.

• Cyber-Physical Modelling and Cybersecurity of Smart Grids: Focusing on the development of integrated cyber-physical models that capture the interdependence between physical grid components and cyber infrastructure. Emphasis is placed on identifying vulnerabilities, simulating coordinated cyber-physical attacks, and deploying AI-enabled security frameworks to enhance the resilience and protection of modern power systems.

 

What's New​

• [30/08/2025] Our paper entitled “DeepLR: Deep Learning Assisted Load Redistribution Attack on Cyber-Physical Power System", got accepted in IEEE Transactions on Smart Grid.

• [20/08/2025] Our paper entitled “Uncertainty-Aware Deep Reinforcement Learning for Robust Autonomous Voltage Control", got accepted in NAPS 2025.

• [03/05/2025] My proposal, “Multimodal AI Framework for Intelligent Energy Systems: Enhancing Decision-Making and Grid Resilience” (as Principal Investigator), has been selected for funding under the 2025 NSF DigiCARES Seed Grant Program.

• [28/04/2025] Got selected for the NM EPSCoR Early Career Workshop (June 3–4, 2025) at the University of New Mexico's Center for High Tech Materials (UNM–CHTM), with a grant award.

• [01/04/2025] Our paper entitled “Impact of Solar Integration on Grid Security: Unveiling Vulnerabilities in Load Redistribution Attacks”, got accepted in 2025 IEEE Kiel PowerTech.

• [20/03/2025] Our paper entitled “OPFkNN: Congestion aware Real-Time Optimal Power Flow With Uncertain Solar Generation”, got accepted in IEEE Transactions on Industrial Informatics​