Zeshi Zheng uses the data streams coming from the wireless sensor clusters installed in the American River basin and the remotely sensed fractional snow coverage data to create a high resolution spatial product of snow water equivalent for the basin in nearly real time. The method is novel: it not only includes classical snow hydrological models, but it also involves cutting-edge machine learning techniques for real-time estimate and future prediction. The product will be a significant contribution to the foundation of the water information system UC Water is building.
Zeshi is an original graduate student with UC Water, working with Profs. Steven Glaser and Roger Bales and coordinating research with the mountain hydrology team.
Zeshi Zheng is a graduate student in the Department of Civil and Environmental Engineering at UC Berkeley. Zeshi has been working on water-related scientific and technical issues of the state of California since 2013. His current research is focusing on using cutting-edge computer science technologies and statistical methods to synchronize the remotely sensed spatial data and ground measurements and create real-time spatial snowpack information systems of headwater regions. Zeshi earned dual degrees of B.S. in mechanical engineering and civil engineering from Shanghai Jiaotong University and University of Michigan at Ann Arbor. He earned M.S. in Civil Systems at the University of California, Berkeley.