Data Scientist
Data Scientist

Biography

Sarthak Chaturvedi is a Data Scientist in the Optimization and Controls group at the Pacific Northwest National Laboratory (PNNL), where he applies his expertise in machine learning, natural language processing (NLP), and mathematical optimization to develop innovative solutions for complex problems in the energy, environment, and policy domains. Since joining PNNL, he has worked on projects sponsored by the DOE Office of Energy Efficiency and Renewable Energy (EERE), the Advanced Research Projects Agency-Energy (ARPA-E), and the Office of Policy, focusing on advancing high-potential, high-impact energy technologies and supporting policymakers in making informed decisions.

Sarthak holds a Master of Science in Computational Science and Engineering from Georgia Tech, where his research focused on developing state-of-the-art language models to evaluate electric vehicle (EV) charging infrastructure in the US and identify key equity issues in access and pricing. His graduate research was supported by grants from the National Science Foundation and Microsoft. As part of a multi-institution project between Georgia Tech and Stanford University, Sarthak utilized advanced language models to extract insights from a large corpus of energy reports, developing human-in-the-loop approaches to identify prominent carbon removal strategies and analyze industry sentiment.

Prior to this, he collaborated with researchers from TU Delft, University of Cambridge, and the Robert Bosch Centre for Data Science and AI on various energy and sustainability projects. His work has been selected for presentation at renowned conferences and journals such as AAAI, TADA, Transportation Research Group, and APPAM in the fields of AI, transportation, and public policy. Sarthak's current research interests include EV infrastructure, grid optimization, decarbonization, energy storage technologies, and the application of advanced NLP techniques like retrieval-augmented generation (RAG), few-shot learning, and transfer learning to address critical challenges in energy and environmental sustainability.

Research Interest

  • Retrieval Augmented Generation 
  • Multi-Agent Systems
  • Foundation Models
  • Responsible AI
  • Grid Resilience
  • Sustainable Transportation
  • Energy Policy

Education

  • MS in computational sciences and engineering, Georgia Tech
  • BS in civil engineering, National Institute of Technology

Publications

2025