Assistant Professor
School of Electrical and Computer Engineering

How much information is it theoretically possible to send over a given medium? How small can a file be compressed? How can the nodes in a sensor network best communicate? These are the sorts of questions that interest Aaron Wagner.

“Cornell has a proud history in information theory,” he says. “It’s a traditional area of strength and I hope to build on that.”

Considering such questions in a networked context adds a new wrinkle that Wagner intends to explore. “There’s a lot of focus now on distributed compression,” he says. “Suppose two people each have a file they want to compress. What level of compression could they achieve if they each worked on different pieces of it?”

There are two types of compression: lossy, which jettisons some data in favor of compactness, such as an mp3; and lossless, which retains every bit of data in the original, like a .wav file. Shortly after arriving at Cornell, Wagner was awarded a Faculty Early Career Development grant from the National Science Foundation for “A New Look at the Fundamental Limits of Lossy Network Compression.”

Engineering is a family affair for Wagner. “My father is also an electrical engineer—a power engineer. He’s a motor guy,” says Wagner. “He had a lot of equipment lying around in the basement, and I spent a lot of time as a kid playing with it.”

At the University of Michigan, Ann Arbor, where he earned his B.S., Wagner was put off by the imprecise answers that were acceptable in some of his engineering courses. He found himself drawn instead to problems about circuits, in which every microamp can be accounted for. “I'm attracted to the parts of engineering that have a mathematical beauty to them,” says Wagner. “Information theory is one of the prettiest of them all.”

Wagner found more than a field of study at Michigan; he also found his wife Jasmine, who is a circuit designer. They attended the same high school, but didn’t start dating until college where they were both in the marching band. He played clarinet and she played piccolo.

Wagner went on to the University of California at Berkeley, where he earned a Ph.D. in electrical engineering and computer sciences with a designated emphasis in communication, computation, and statistics.

The first undergraduate class Wagner taught at Cornell was stochastic processes, a subject dealing with the probability of random events that is reserved for graduate students at most other schools. “It was kind of a challenge at first because I had to find a way to pitch it to undergrads,” he says. “I think it’s a good course for undergraduates because stochastic processes are really where probability becomes useful for engineers.”

Exploring the theoretical boundaries of information technology may sound far removed from reality, but Wagner knows his work could someday inform applications that impact everyone’s lives. “The way cell phones operate now owe a lot to information theory,” he says. “It’s not just a purely theoretical exercise.”