Dr. Eunsang Cho

Meet the PI

Dr. Eunsang Cho

(Assistant Professor)

Dr. Eunsang Cho joined Texas State University (TXST) in the Fall 2023 as an Assistant Professor. Dr. Cho’s research background is primarily in hydrology and remote sensing, emphasizing quantifying climate and anthropogenic impacts on water resources, extreme events (e.g., floods, drought, & wildfire), and water-related infrastructure in natural and human systems. As a research tool, he uses field observations, remote sensing techniques (from UAV, aircraft, and satellite platforms), land surface and climate modeling, big-data analytics, and machine learning techniques. He obtained his B.S. (2010) and M.S. degrees (2014) from Hanyang University, Seoul, South Korea, and Ph.D. (2020) from the University of New Hampshire, USA. Prior to joining TXST, he worked as a Postdoctoral and Assistant Research Scientist in the Hydrological Sciences Laboratory at NASA Goddard Space Flight Center (GSFC), also affiliated with the Earth System Science Interdisciplinary Center (ESSIC), University of Maryland College Park from 2020 to 2023. He has published more than 25 peer-reviewed articles in renowned journals in hydrology, water resources, and geosciences including Water Resources Research, Remote Sensing of Environment, and Geophysical Research Letters. Several of his recent articles have been highlighted in AGU’s EOS Science Magazine, ScienceDaily, and other outlets. As PI and Co-PI, Dr. Cho has secured $5.7M in U.S. federal grants from NASA, USDA, the Department of Energy (DOE), the Department of the Interior (DOI), and the Department of Transportation (DOT) to address pressing challenges related to water, climate, and society. He also serves as an Executive Member of the American Geophysical Union (AGU) Remote Sensing Technical Committee, the American Meteorological Society (AMS) Hydrology Committee, and the Eastern Snow Conference (ESC), as well as an Editorial Board Member of Scientific Reports (Nature Portfolio) and Frontiers in Big Data.

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Cho

Lab

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We are building a dynamic team of undergraduate and graduate students and postdocs who share our passion to better understand hydrology and water resources in a changing climate for a sustainable environment. To achieve this, we use field observations from station data and field campaign, multiple remote sensing techniques, land surface hydrologic models, and climate models along with big-data and machine learning (ML) techniques.

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