Fei Huang is a Ph.D. candidate in Language Technologies Institute, School of Computer Science, Carnegie Mellon University. China. He graduated with a B.S. in Electrical Engineering and B.A. in Linguistics in 1996 from Tianjin University and M.Sc. in Pattern Recognition and Intelligent System in 1999 from Chinese Academy of Sciences. In 2001 He completed his M.Sc. in language and information technologies at CMU. His research interests are in machine translation, information extraction, spoken language processing and statistical machine learning.

Rapid economic growth and globalization enable unprecedented culture
exchange, which also presents great challenge to the communication in a
multilingual world. Because of language barriers, people speaking different
languages find it difficult to communicate efficiently, especially in urgent
situations, e.g., an emergency room in a hospital. Therefore medical
dialogue translation systems are in great need.

In this project I will first conduct literature survey on how language
technologies are applied in life science and health care issues, then I aim
to develop a technique which automatically build a Chinese-English medical
term translation dictionary via web mining. The extracted dictionary will
improve the performance of medical dialogue translation systems, and the
developed approach hopefully will be applicable to other language pairs.