I serve as leading postdoc for a collaborative $1.3 million dollar grant from National Science Foundation (NSF) Division of Ocean Sciences supports Citizen Science GIS at the University of Central Florida (UCF). This project is one of the earliest attempts to employ UAV mapping in seagrass management and conservation across 23 degrees of latitude over an extended time series.
For my doctoral dissertation, I developed and implemented a novel geo-statistical method that used to assimilate multi-scale data sets with different temporal sampling frequencies and different spatial densities. The algorithm has been made available in Python and ArcGIS packages with a user-friendly interface. High-performance computing on supercomputer and parallel computing are utilized to enhance the efficiency of the algorithm.
Citizen Science GIS, a 2017 Esri Special Achievement in GIS Award winner (one of four higher education awardees worldwide), is housed at University of Central Florida lead by Dr. Timothy Hawthorne. We are a diverse group of faculty, students, and community partners around the world committed to strengthening the connections between science and society.
I am co-leading the NSF RET project to build mutually rewarding partnerships with K-12 science teachers to transfer teachers’ experience in cutting edge research to the broader impact content in the classroom. Iwork with teachers participating fieldworks and developing science lessons using fieldwork data and drone mapping principles to support inquiry-based learning with students.
I am in the developer team of GRASS7 for satellite image segmentation module (i.segment). GRASS GIS, commonly referred to as GRASS (Geographic Resources Analysis Support System), is a free and open source Geographic Information System (GIS) software suite used for geospatial data management and analysis, image processing, graphics and maps production, spatial modeling, and visualization.