Si Granted CAREER Award
Si plans to significantly advance the state-of-the-art in federated text search. This type of information retrieval provides access to hidden information centralized retrieval models used by conventional search engines do not pick up, providing better results. To better serve users, Si's proposed framework incorporates multiple type resource representation, utility-centric resource selection, and effective and efficient results merging. His work will serve as an important bridge for moving federated text search research into practical applications.
Si joined Purdue in 2006 after completing his PhD in Language and Information Technologies from Carnegie Mellon University. He earned an MS from the Language Technology Institute at Carnegie Mellon and an MS from the Tsinghua University from the Department of Computer Science and Technology where he also earned his BS. His research interests include information retrieval and management, applied machine learning and data mining, text/data mining for life science, speech processing and multimedia processing, artificial intelligence and pattern recognition, and natural language processing.
Congratulations, Professor Luo Si!
June 2008
