Yuhan (Douglas) Rao
Yuhan (Douglas) Rao received his PhD degree in Geographical Sciences from University of Maryland, College Park, in 2019. His dissertation focused on using machine learning and satellite observations to reduce the uncertainty of regional near surface air temperature datasets. Douglas received both his bachelor’s degree in Statistics and master’s degree in cartography and remote sensing from Beijing Normal University. He has also been working for the GOES-R algorithm working group (AWG) as a research assistant at the Cooperative Institute for Climate and Satellites–Maryland at UMD, where he supported the validation of the GOES-R ABI land surface temperature (LST) product using both station measurements and other satellite products. During his PhD program, Douglas taught GIS and spatial statistics courses at UMD.
Dr. Rao joined NCICS as a Postdoctoral Research Scholar in 2019. His current research at NCICS focuses on generating a blended temperature dataset by integrating station measurements and satellite observations via innovative statistical models. His broad research interests focus on advanced statistical models, satellite data development/validation, and applied research for climate and environment monitoring.
Dr. Rao is actively engaged in local and national community. He is a fellow for the Earth Science Information Partners (ESIP) machine learning cluster, where he is developing training tutorials to promote Earth-science-oriented machine learning applications. He has also been an active member of the American Geophysical Union (AGU), where he is a member of AGU Global Environmental Change section Executive Committee. He is also the co-chair of the AGU Student and Early Career Scientist Conference.