Bin Fang has a multi-disciplinary background in earth science, electrical engineering, and satellite technology, and has spent more than ten years in scientific research and teaching in universities. He received his PhD degree from University of South Carolina and was a postdoctoral research scientist at Columbia University. Bin’s studies involved developing algorithms to enhance spatial resolution of satellite imagery and compute geophysical variables for earth surface process explanation. This work motivated Bin to find new approaches for his research which involve Machine Learning technology instead of traditional physical modeling. His final project applied several models to predict the number of taxi pickups of specific time, weather condition and district in New York City, which may provide useful information to taxi dispatchers (i.e. Uber) and drivers.