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

### Monte Carlo decoding: A novel randomized decoding for high performance and low complexity

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

### Information theory for cellular wireless

## 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