Professional headshot of Narendra Das

Narendra Das

Associate Professor

Department of Biosystems and Agricultural Engineering, College of Engineering

Associate Professor - Department of Civil and Environmental Engineering in the College of Engineering

Farrall Hall, 524 S Shaw Ln Rm 223

Biography

Dr. Narendra N. Das is an Associate Professor with joint appointments in the Departments of Biosystems and Agricultural Engineering and Civil and Environmental Engineering. His research focuses on hydrology, microwave remote sensing, and crop modeling. Dr. Das leads the Remote Sensing for Agriculture and Hydrology Lab (RSHAL), where he collaborates with NASA satellite missions, a continuation of projects initiated during his tenure at NASA's Jet Propulsion Laboratory. Dr. Das is a Science Team M

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Education

Ph.D., Biological and Agricultural Engineering, Texas A&M University

M.S., Biological and Agricultural Engineering, Texas A&M University

B.E., Chemical Engineering, National Institute of Technology, Raipur

Awards

MSU 2022, MTRAC AgBio Innovation Challenge award to create a Low-Cost Gas Sensor for Agricultural Applications and Climate Change Studies.

JPL Voyager Award 2020 for high impact work on hydrological extreme forecasting.

NASA Achievement Award for 2019 for exceptional service toward the NASA SMAP mission.

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Publications

Nanda, A.1, Das N. N.3, Singh G., Bindlish R., Andreadis K., and Jayasinghe S., (2024). Harnessing SMAP Satellite Soil Moisture Product to Optimize Soil Properties to Improve Water Resource Management for Agriculture. Agriculture Water Management. vol. 300, 108918. (DOI: https://doi.org/10.1016/j.agwat.2024.108918)

Lal, P.1, Singh G., Colliander A., Entekhabi D., and Das N. N.3, (2024). Uncertainty Estimates in the NISAR High-Resolution Soil Moisture Retrievals from Multi-Scale Algorithm. Remote Sensing of Environment (in Press).

Hashemi M G.Z1, Tan P. Tan, Jalilvand E., Wilke B., Alemohammad H., and Das N. N.3, (2023). Synthetic Aperture Radar (SAR); Deep Learning; Crop Yield Prediction; XGBoost; 3D-CNNs. Submitted to Computers and Electronics in Agriculture (under review).

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