His work focuses on spatial artificial intelligence (AI). Tell us about your journey to the University of Minnesota. I was a research associate professor at the University of Southern California (USC). I worked at the Spatial Science Institute. My research area is spatial artificial intelligence (AI), so we build applied machine learning methods and systems to spatial data in order to understand human-environment interactions from all kinds of data, such as old maps, satellite imagery, onsite sensors, street photos, census data, and map datasets. One of the main reasons I came to the University of Minnesota is because of the Department’s strong spatial computing faculty members - like Shashi Shekhar and Mohamed Mokbel. How did you become interested in computer science and your specific field? I felt this was a natural environment for me to continue my work with some great collaborators. I started to work on geographical datasets a long time ago when I was an undergraduate student. My first project was to take vector lines, so geometries of things in space, and write a C++ library in order to perform intersections and unions of all of these geometrics. I started to work on larger datasets to see if we could do this more efficiently and then started to work on new problems. For example, how can we take two datasets and integrate them together. for my master’s degree in computer science where I started to look at a variety of problems in spatial data - like computer vision for historical map scans and integration systems for map datasets. I love maps and they provided us with a lot of interesting maps to use for our research. I worked on computer algorithms to help us understand what is going on with different maps. Then, you use the information in combination with other datasets to create knowledge and useful connections.įirst, we tracked information with scanned images. I have been working in this field for a long time.
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