Deeksha Rastogi

Deeksha Rastogi is a research scientist in the Computational Urban Sciences Group within the Computational Science and Engineering Division at Oak Ridge National Laboratory. She has served in this role since 2019, after joining ORNL in 2013 as a research associate in the Computational Earth Sciences Group. With 16 years of interdisciplinary research experience, she works at the intersection of high-resolution Earth system modeling, extreme-weather analysis, high-performance computing, artificial intelligence and energy-water applications.

Rastogi’s research integrates methodological development, uncertainty evaluation and the development of high-resolution data resources to address challenges related to electricity demand, hydropower, water resources, infrastructure and regional resilience. Her work spans dynamical and statistical downscaling, AI and machine-learning methods, extreme-event characterization, and the identification of physical storm mechanisms. She has made substantive scientific and technical contributions to major national and international modeling efforts and leads AI-based downscaling research for developing high-resolution Earth system projections. Her research has examined extreme precipitation, heat waves and cold waves, and compound heat wave–drought extremes.

She currently serves as principal investigator for a DOE Hydropower and Hydrokinetic Office (H2O)- funded project that classifies storm types in high-resolution datasets to support precipitation frequency analysis for risk-informed evaluations of hydropower and infrastructure safety. She also leads an ORNL Laboratory Directed Research and Development (LDRD) that focuses on Integrated Multi-sector Modeling of Hurricane Hazard, Risk, and Resilience for Southeast Energy-Water Infrastructure. In addition, she serves as co-investigator on the SECURE Water Act Section 9505 assessment, funded by DOE H2O office, and  Integrated AI-Driven Weeks-to-Years Prediction of Water for Energy in the Tennessee Valley Authority Region, supported by DOE Genesis Mission.

Previously, she led an ORNL LDRD project that applied artificial intelligence, scientific data analysis and high-performance computing to evaluate temperature extremes and their effects on electricity consumption. She has also served as a co-investigator on several other ORNL LDRD projects and contributed to numerous DOE-supported projects, including Integrated Multi-Sector Multi-Scale Modeling (IM3) funded by the DOE Office of Biological and Environmental Research (BER); the Terrestrial Ecosystem Science Scientific Focus Area, also supported by DOE BER; Future and Extreme Weather Data, funded by the DOE, Building Technology Office and Energy System Planning for Resilience during Severe Weather (ESPRS), supported by the DOE Office of Electricity.

Rastogi’s scholarly record includes 37 peer-reviewed journal articles, eight publicly available datasets, six technical reports and an encyclopedia chapter. She also mentors students and early-career researchers and contributes to the scientific community through collaborations, editorial service, peer review and the organization of scientific sessions.