I completed PhD in Computer Science in 2009 at the University of Tasmania (UTAS). I investigated knowledge acquisition methods for smart information systems on the Web. I have worked at the University of New South Wales as a research fellow since 2009 (Level B) Research. I have studied social networks with a large Australian social network web site, which has about 2 million adult members (ages over 18). And among the members over 30,000 members are active users per month and they have interactions over 1 millions of interactions between users. Our research team received very detailed data over four years and to analyze them I have applied statistical methods and data mining methods.I have researched for the social network web site to develop people-to-people recommender systems, which recommends a set of users to a specific users. Our research team have developed multiple recommendation methods and evaluated them in the real world. At last the recommender system has been deployed the social network website and provides recommendation nowadays.Ripple-down rules. I have investigated Ripple-Down Rules (RDR), a heuristic knowledge acquisition method, and have focused on its extension, application and integration with other machine learning techniques. I have applied RDR to various applications, such as document classification, natural language processing (named entity extraction, entity relation analysis, etc), e-education, and e-health. Web intelligence I also have researched web intelligence, which covers web crawling and monitoring, information management, and recently social network analysis and recommendation systems. I have authored or co-authored a total of 38 papers since 2002, and total number of citations is 128 (Google Scholar, May 2012). Industry Experience. I had six and a half years experience in the ICT industry in Korea.