Kim – Research Overview

My research is focused on information theory and statistical signal processing, with applications in communication, control, computation, networking, data compression, and learning. On a less serious note, I am interested in fun mathematical puzzles, which my research group discusses routinely during weekly seminars; see also a course on puzzles I taught in Fall 2011.

Current (ever-evolving) research interests are as follows:

Network information theory

Directed cutset bound: The fundamental limit on network information flow

Index coding: The canonical network communication problem

Optimal relaying: The instruction manual for network building blocks

Communication theory

Sliding-window coded modulation (SWCM): A practical interference mitigation technique from information theory

Data science (information theory + learning theory)

Directed information: The ‘‘right’’ answer to many problems on causality

Universal information processing: How to get something out of nothing