I received my Ph.D. degree in Computer Science from the University of Minnesota, Twin Cities, in 2007. I also got the M.S. in Computer Science at the University of Minnesota (Department of Computer Science and Engineering).†† For undergraduate majors, I studied Computer Science & Engineering (B.S.) and Statistics (B.S.) at Korea University in (South) Korea.
My research area is data science (including data mining, machine learning and statistics), data-driven discovery and database. My research focuses on large scale data mining and† data management, with a particular emphasis on nontraditional data such as spatial (with geospatial references), temporal and spatio-temporal data, and graph/network data and scientific data cross boundaries of computer and information science and other sciences. Location based computing, information and services are closely related to my research area.
Current research projects concern Big Data analytic methods (e.g., parallel and distributed data mining on the MapReduce framework, e.g., Hadoop, and on Spark) and Big Data management techniques (e.g., NoSQL, distributed database systems and data warehousing) in the cloud computing environment.
My research has been supported by the U.S. Air Force Office of Scientific Research, the Air Force Research Laboratory, Purdue Research Foundation, Griffiss Institute, SUNY Research Foundation, Indiana University, and so on. I have worked as Air Force Summer Faculty Fellow and Air Force Summer Visiting Faculty at Air Force Research Laboratory/Rome Research Site.
I am an active member of review panels of NSF (National Science Foundation)/CISE (Computer & Information Science & Engineering), NSF/IIS (Information and Intelligent Systems), and NSF/CCLI (Course Curriculum and Laboratory Improvement). †Recently I have served as the Big Data panelist of NSF/CISE.† I also serve as the organizer or program committee in numerous top-tier international conferences and often as the manuscript reviewer of international journals. I am currently organizing the International Symposium on Spatial and Temporal Databases (SSTD2015) as the publicity co-chair.
Iím directing the Knowledge discovery, Data mining and Database Lab at school. Students and other domain experts are welcome to work with me in all areas of data mining, database, machine learning and related applications.
†††† Recent News / Coming Events
The 2015 SSTD is the fourteenth event of a series of biannual symposia that discuss new and exciting research in spatial, temporal and spatio-temporal data management and related technologies and start setting future research directions. The SSTD publications have high impact on spatial and temporal data research area in computer science and other relative area.
†††† Research advising courses