ChengXiang Zhai

Ph.D. Carnegie Mellon University, 2002

Research Statement

My research spans several related fields including information retrieval, natural language processing, machine learning, data mining, and bioinformatics. My primary research interest is developing techniques for managing and exploiting large amounts of text information, such as news articles, email messages, scientific literature, government documents, and all kinds of Web pages. With the dramatic growth of online information, we are overwhelmed with huge amounts of information and have an urgent need for powerful software tools to help manage and make use of it. I work on a variety of general techniques for searching, filtering, organizing, and mining text information and develop applications in multiple domains including Web, email, and literature. My research draws on methods from statistical learning, natural language processing, and data mining to tackle problems in information retrieval, and emphasizes on both fundamental research and system development. In fundamental research, I have been developing effective and efficient information retrieval models, especially models based on statistical language modeling and formalized retrieval constraints; I have also been working on latent probabilistic models for comparative and spatiotemporal text mining. In system development, I have been developing information retrieval toolkits and application systems for personalized Web search and literature navigation.

In addition to text information management, I am also very interested in bioinformatics both as an application domain of the developed general text information management techniques and as a new research area where similar problem solving strategies and methods can be applied. My research in bioinformatics includes biology literature retrieval and mining, motif sequence analysis, and in general, integrating text mining with sequence mining to help biology discovery.

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