Graduate student (Ph.D.)
M.S. Cart/GIS, Beijing Normal University, 2013
Empowered by the rapid advancement and popularization of information technology, general public nowadays can actively involve in scientific data collection endeavors (e.g., tweets, citizen science project like eBird, volunteered geographic information, etc.). This crowd-sourcing data contributing paradigm imposes opportunities as well as challenges for GIScience research, especially for the inquiry of predictive mapping of spatial variation of geographic phenomena (e.g., wildlife habitat).
Citizen contributed data can serve as voluminous and inexpensive samples for predictive mapping. But it also raises challenges for traditional mapping methods which often impose rigorous restrictions on how the samples were collected, to which citizen contributed data usually does not conform.
My research interests focus on developing a methodology for addressing some of the challenges imposed by citizen contributed data in predictive mapping of geographic phenomena of interest. Wildlife habitat mapping would most probably be one of my case studies.
Teaching Assistant, Geog 578 (GIS Applications), Fall 2013
Teaching Assistant, Geog 676 (Web Spatial Database Development), Spring 2014
Teaching Assistant, Geog 377 (Intro to GIS), Fall 2014
Awards and Honors
Excellent Volunteer in the 29th Olympic Games, 200
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