AI Scientist|Data Scientist|Building Energy Modeling
Send a job offer directly to this candidate
Data Scientist and Applied Machine Learning Engineer with 7+ years of experience building scalable data-driven and physics-informed modeling systems for grid-interactive efficient buildings at the U.S.
Laboratory (NREL).
Deep expertise in data science, neural networks, statistical learning, predictive modeling, and control systems to support DOE mission areas. Strong background in large-scale simulation pipelines, and surrogate modeling, with growing focus on generative AI, LLM-based systems, and automation of AI-driven reduced order model development for commercial and residential building envelope thermodynamics.
Proven ability to lead technical projects, translate research into deployable tools, and collaborate across interdisciplinary teams to deliver impactful solutions.
National Renewable Energy Laboratory (NREL) — Golden, CO
Researcher, Residential Buildings Group (2020 – Present)
Postdoctoral Researcher (2019 – 2020)
Ph.D., Mechanical Engineering — Texas A&M University, 2018
Thesis: Automated implementation of advanced control algorithms (MPC) for large-scale building HVAC systems
M.S., Mechanical Engineering — Texas A&M University, 2011
B.E., Mechanical Engineering — Birla Institute of Technology, Ranchi, India
