Profile picture of Arjun Bhattacharyya

Arjun Bhattacharyya

Graduate Research Assistant

Arjun Bhattacharyya is a Ph.D. student in Energy Science and Engineering at the Bredesen Center - University of Tennessee, Knoxville, and a Research Assistant at Oak Ridge National Laboratory (ORNL). He also holds an MS in Electrical Engineering from The University of Tennessee, Knoxville, with a focus on Power Systems, and a bachelor's degree in Electrical and Electronics Engineering from Manipal Academy of Higher Education, India.

Arjun’s research lies at the intersection of artificial intelligence and power system engineering, with a core emphasis on improving the reliability and resilience of electric grids under conditions of increasing renewable energy penetration. His work integrates advanced machine learning, natural language processing, and domain-specific simulation tools to solve critical challenges in energy systems. 

 

 

Arjun’s professional experience spans academic and national laboratory. As a Graduate Research Assistant at the Bredesen Center, he conducts research on power system resilience using AI and machine learning, contributing to DOE-funded initiatives that address real-world energy challenges. 

Earlier, Arjun also gained industry exposure through his internship at Deloitte USI, where he engaged in cloud resilience, compliance, and data analytics.

  1. Graduate Scholarship Award for Academic Excellence – Spring 2025
    Awarded by the Graduate School, The University of Tennessee, Knoxville.
  2. First First-Author Publication Award – 2025
    Awarded by the Bredesen Center for publishing the first first-author article.
  • Ph.D. in Energy Science and Engineering
    The University of Tennessee, Knoxville, USA
    2023 – Present
  • M.S. in Electrical Engineering
    The University of Tennessee, Knoxville, USA
    2023 – 2025
  • B.S. in Electrical and Electronics Engineering
    Manipal Academy of Higher Education, Manipal, India
    2019 – 2023
  1. A. Bhattacharyya, S. Mukherjee, “Using Artificial Intelligence to Improve Reliability and Operational Efficiency of Small-Scale Hydroelectric Distributed Generation”, 2025 IEEE Rural Electric Power Conference (REPC), Westminster, CO, USA, 2025, doi: 10.1109/REPC60353.2025.00017
  2. S. Mukherjee, S. Chintavalli, N. Bhusal, V. Tansakul, S. Subedi and A. Bhattacharyya, “The Challenges of Modeling Distributed Energy Resources (DERs) as Blackstart Resources and for Volt-VAR Optimality,” 2024 IEEE Rural Electric Power Conference (REPC), Tulsa, OK, USA, 2024, pp. 76-80, doi:  10.1109/REPC57617.2024.00021