My current research interests are: spatiotemporal data mining, privacy issues in data mining, machine learning on network/graph data, learning analytics. My research on spatiotemporal data mining focuses on (i) overcoming data management issues using distributed array-based database, (ii) analytic algorithms and tasks, (iii) data representation using networks and tree structures, (iv) privacy issues, and (v) application developments. My projects and investigations are both research-driven and application-driven. The application-driven investigations utilize real-world data such as mobile data from smartphones, crowdsourced sensor data collected from smartphone, factory sensor data, text data (from internet), image data, and satellite data.

I am also interested in (i) developing new methods for discovering interesting or useful events (and patterns) in heterogeneous data from multiple data sources, (ii) effective machine learning using very few labeled examples, and (iii) applying data analytics and machine learning techniques to support technological-enabled learning.