Shovan Chowdhury

Shovan Chowdhury is a data scientist with expertise in mechanical and energy engineering. He holds a position as a Research Fellow in the Grid-Interactive Controls group at the Building Technologies Research and Integration Center (BTRIC) of Oak Ridge National Laboratory. Prior to this role, he earned a master’s degree in Mechanical Engineering from Idaho State University. At ORNL, Shovan focuses on large-scale building energy modeling and simulation using the AutoBEM software suite. His current projects involve the development of the AutoBEM software suite and the Model America dataset. He specializes in handling big data and implementing machine learning techniques for building energy modeling. Additionally, he has developed future typical meteorological year (fTMY) files for every Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (RCP) scenario for each county in the United States.

Shovan contributed to key data releases including data and energy models for 141.5 million U.S. buildings:

New J ; Bass B ; Berres A ; Clinton N ; Adams M ; Li F ; Stubbings A ; Chowdhury S (2021): Model America: Data and Models for every U.S. Building. Southwest Urban Corridor Integrated Field Laboratory (SW-IFL), ESS-DIVE repository. Dataset. doi:10.15485/2283980 accessed via https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2283980 on 2024-03-12
Stubbings, Avery, Li, Fengqi, Chowdhury, Shovan, New, Joshua. (2023). “Model America – Summer 2020 Arizona Building Energy Simulation Results from ORNL’s AutoBEM.” ORNL internal Scientific and Technical Information (STI) report. Zenodo: https://zenodo.org/records/10419620, Dec 21, 2023.

Future-weather data from 1980-2100: