Deeksha Rastogi

Research Scientist

Deeksha Rastogi is a Research Scientist in the Computational Science and Engineering Division at Oak Ridge National Laboratory since 2019. She also worked as a Research Associate in the Computational Earth Sciences Group at ORNL during 2013-2016. She has over 12 years of experience working in the fields of atmospheric and climate sciences. Her research focuses on understanding climate change, weather/climate extremes and associated hydroclimate responses and impacts on natural and human systems at varying spatiotemporal scales. She employs high performance computing and earth system modeling tools and scientific data analysis to achieve these objectives.

Deeksha has worked on various projects supported by United States, Department of Energy. She has contributed to the development of multiple high-resolution, physics-based climate datasets. She has authored/coauthored a total of 20 peer reviewed publications, 3 datasets, 6 technical reports and 1 encyclopedia book chapter.  She has been a reviewer for over 20 scientific journals. She serves as a member of American Geophysical Union (AGU) and has convened and chaired sessions at AGU Fall Meetings since 2018.

Deeksha earned her PhD in Energy Science and Engineering with a focus in Environmental and Climate Sciences from the Bredesen Center at the University of Tennessee, Knoxville in 2019. She obtained her MS in Atmospheric Sciences from the University of Illinois Urbana Champaign in 2012 and BS (B. Tech.) in Environmental Engineering from Indian School of Mines, Dhanbad, India in 2010.

Deeksha received the Bredesen Center Fellowship from The University of Tennessee, Knoxville, TN from 2016-2019 and the Graduate Student Fellowship in the Advanced Study Program at the National Center for Atmospheric Research, Boulder, CO in 2019. She also received the Graduate Student Researcher Award in the Science and Technology Category of the UT-Battellle Awards in 2019.



CMIP6-based Multi-model Hydroclimate Projection over the Conterminous US


Thermodynamic Global Warming (TGW) Simulation Datasets