His research interests include metadata, information retrieval, natural language processing, text mining, knowledge management, and human computing. His dissertation at Syracuse University explored an innovative ranking method that weighted the retrieved results by leveraging dynamic community interests. In contrast to most existing studies in scientific resource recommendation, his research developed an enhanced understanding of the scholarly network from a topical content perspective and investigated the use of full-text citation data to improve the overall recommendation ranking performance. He proposed SWALE and Collaborative PDF reader projects, which will generate innovative metadata along with next generation knowledge retrieval and question answering systems.