I am interested in developing data-driven methods that can take advantage of domain knowledge to solve complex problems. For example, we built machine learning algorithms that incorporate spatial science techniques for air quality prediction and imagery recognition. I also enjoy building working systems with my students and doing consulting work related to my research.
I teach data mining and advanced spatial computing at USC. I used to teach spatial databases and geospatial data integration.
Werner, M. and Chiang, Y.-Y. (eds.) Handbook of Big Geospatial Data, Springer (ISBN 978 3-030-55461-3)
Tavakkol, S., Han, F., Mayer, B., Phillips, M., Shahabi, C., Chiang, Y.-Y., & Kiveris, R. (2020). Kartta Labs: Collaborative Time Travel. Hawaii International Conference on System Sciences
Lin, Y., Chiang, Y.-Y., Franklin, M., Eckel, P. S., and Ambite, J. L. (November 2020). Building Autocorrelation-Aware Representations for Fine-Scale Spatiotemporal Prediction, In Proceedings of IEEE International Conference on Data Mining (ICDM), Sorrento, Italy
If you have scrolled all the way to see this sentence, you might as well check out my PhD thesis and defense presentation. (My PhD supervisor is Craig Knoblock, to whom I am eternally grateful.)