A list of my publications can be found at Google Scholar.
I will upload my future publications submitted to journals and conferences to https://arxiv.org/ when they are still in review process. I hope that by doing so I can facilitate the prompt exchange of information in the research community.
I will try to open-source all my publications. The source code of my algorithms can be found in my GitHub.
The goal of my research is to use data-driven solutions to enhance the reliability, efficiency, and security of modern power systems. As the power industry undergoes transformation with the integration of renewable energy and smart grid technologies, new challenges such as intermittency in renewable generation, energy demand fluctuations, and the need for adaptive grid management arise. My work addresses these challenges by applying Generative AI (GenAI) to power systems, focusing on synthetic data generation, missing data restoration, and predictive maintenance. GenAI helps tackle data scarcity, restore missing information, and improve predictive models, providing utilities with valuable insights for decision-making. The broader impact of my research lies in improving grid resilience, promoting sustainable energy practices, and driving AI innovations in energy management, all while ensuring grid stability in data-constrained environments.
Photovoltaic Analysis and Response Support Platform for Solar Situational Awareness and Resiliency Services
U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy technologies Office.
Award Number: DE-EE0008770
Role: Graduate Research Assistant
GAN-based synthetic data generation.
BERT-based missing data restoration and DR baseline estimation.
An Artificial Intelligence Engineering System Analysis Assistant (Aiesaa) for auto-creation of integrated transmission-distribution grid models
U.S. National Science Foundation, Energy, Power, Control, and Networks (EPCN).
Award Number: 2329536
Role: Graduate Research Assistant
Fine-Tuning LLM for missing data restoration and load forecasting.
Grid Operator Analytics and Assessment Tools for Inverter-Based Resources Dominated Grid (GOAAT-IBR)
U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy technologies Office.
Award Number: DE-EE0011375
Role: Intern
Power system event detection and classification using PMU data.
Resilience Analysis, Forecasting, and Tracking System
Eaton Research Lab, Golden, CO.
Role: Intern
Switchgear condition monitoring and maintenance scheduling.
Power System Engineering Research Center (PSERC) Webinar, Nov 19, 2025
Title: Generative AI for Data Challenges in Electric Power Engineering
Announcement | Slides | Recording.