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Indian American’s essay published on NASA’s EarthData
Dr Ramachandran quoted that AI foundation models (FM) are reshaping the landscape of data management and scientific research.
Indian American scientist publishes essay on NASA’s EarthData / LinkedIn
An essay by Indian American NASA scientist Rahul Ramachandran has been published on NASA’s EarthData. It addresses the challenge of scaling in Earth science due to increasing data volumes.
The work, titled "From Petabytes to Insights: Tackling Earth Science's Scaling Problem," describes Earth science's scaling problem as a multifaceted challenge. It suggests the inclusion of artificial intelligence into informatics as a potential solution.
"Tackling it requires a comprehensive approach that addresses not only the technical aspects of data management but also the broader implications on scientific processes and ethical considerations," the essay states.
Ramachandran underlined the need to recognize that the evolution of data and the research life cycle is not a one-time effort but a continuous process. He reiterates that artificial intelligence (AI) foundation models (FM) are reshaping the landscape of data management and scientific research.
"Our prototype effort in collaboration with IBM Research, the Harmonized Landsat and Sentinel-2 (HLS) Geospatial FM, Prithvi, exemplifies how FMs can address the complexities and limitations associated with traditional AI models in scientific research," Ramachandran wrote.
Currently a research scientist at NASA, where he has worked for over 10 years, Ramachandran previously served asthe principal research scientist at the University of Alabama in Huntsville.
The Indian American has also served as a team lead of Earth Science Informatics at Oak Ridge National Laboratory. He has received several honors, including the NASA Exceptional Achievement Medal in August 2018 and the Presidential Early Career Award for Scientists and Engineers (PECASE) in September 2009.
He has designed software tools for visualizing and mining satellite imagery, an XML-based solution to address the data format heterogeneity problem, and an ontology-driven meta-search engine with data, information, and service aggregation capability.
The scientist completed his bachelor's degree in mechanical engineering from Jamia Millia Islamia in India, master's in meteorology from South Dakota Mines, master’s in atmospheric science, and computer science, and a doctorate in atmospheric science from the University of Alabama in Huntsville.
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