< back California Institute for Telecommunications and Information Technology yhk@ucsd.edu Phone (858) 534-4254 Website < back |
Young-Han Kim Statistical signal processing, information theory, communication, networking, data compression, information processing Young-Han Kim primarily works on two important challenges for today's high-speed, high-volume information processing systems -- how to describe information efficiently and how to transmit it reliably in the presence of noise and interference. With the ultimate goal of providing guidelines that can be put into practice, he explores fundamental principles behind a variety of applications in communication, networking, compression, prediction, and data storage. For example, he studies the role of feedback in communication networks, searching for new ways of utilizing feedback to improve system performance. In his recent work on Gaussian channels, which are the most popular models for real communication channels that can be mathematically analyzed, Young-Han Kim not only solved the long-standing open problem of finding the optimal feedback communication method, but also showed an interesting connection between control, estimation, and communication. In a broader context, Kim approaches problems of efficient and robust information flow in networks using an array of mathematical tools from statistical signal processing, control theory, convex optimization, and information theory. His other research interests include statistical inference, learning theory, and quantum information processing. Biography Professor Young-Han Kim received his B.S. degree with honors in Electrical Engineering from Seoul National University, Korea, where he was a recipient of the General Electric Foundation Scholarship. After a three-year stint as a software architect for building Korea's newly opening Incheon International Airport, he resumed his graduate studies at Stanford University and received his Ph.D. degree in Electrical Engineering (M.S. degrees in Statistics and Electrical Engineering) in June 2006. His Ph.D. thesis elucidates the role of feedback in communication and in particular, resolves the long standing open problem of finding the feedback capacity of Gaussian channels. More broadly, Professor Kim is interested in statistical signal processing and information theory, with applications in communication, networking, data compression, and learning. |
