Thomaz, who joined the Georgia Tech faculty in 2007, focuses her research on social interactions between robots and humans.

"It's quite hard to enumerate, much less engineer ahead of time, all the tasks and skills people will need robots to do," said Thomaz. "We're working on developing robots that can learn new skills from everyday people so that the robots can adapt their behavior to the task at hand."

It's called Socially Guided Machine Learning, and Thomaz is working on bridging the gap between state-of-the-art learning systems and the kind of teaching an everyday person is able to give the robot.

For example, her robots - Junior and Simon - give visual cues, such as gestures and facial expression, to indicate whether they understand what a human is telling them. Thomaz also develops machine learning methods to help robots learn physical tasks more quickly, particularly from teachers who are not necessarily programmers.

Thomaz was selected from more than 300 nominees by a panel of expert judges and the editorial staff of Technology Review, MIT's magazine on science and technology. She will be featured along with the other 34 finalists in the magazine's September/October issue, and will be recognized at MIT's Emerging Technologies Conference in September.