Professor Kong’s research interests focus on data mining and big data analysis, with emphasis on addressing the data variety issues in biomedical research and social computing. Data today involves an increasing number of data types that need to be handled differently from conventional data records, and an increasing number of data sources that need to be fused together. Dr. Kong is particularly interested in designing algorithms to tame data variety issues in various research fields, such as biomedical research, social computing, neuroscience, and business intelligence. He has been working on mining graph data in the domains of neuroscience, biomedical informatics and social networks, and has published papers in top conferences and journals of data mining, including KDD, ICDM, SDM, WWW, WSDM, CIKM, TKDE.