Dr. Kim approaches problems of efficient and robust information flow in networks using an array of mathematical tools. Within the context of today's high-speed, high-volume information processing systems, Young-Han Kim primarily works on the challenges of describing information efficiently and transmitting it reliably in the presence of noise and interference. 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. His other research interests include statistical inference, learning theory, and quantum information processing. Selected Publications: