Julie Shah

Associate Professor





Efficient Communication for Human-Machine Teams

Our goal is to develop collaborative agents (software or robots) that can efficiently communicate with their human teammates. Key threads involve designing algorithms for inferring human behavior and for decision-making under uncertainty.

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Adding a splash of human intuition to planning algorithms


Robot helps nurses schedule tasks on labor floor

Today’s robots are awkward co-workers because they are often unable to predict what humans need. In hospitals, robots are employed to perform simple tasks such as delivering supplies and medications, but they have to be explicitly told what to do. A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) thinks that this will soon change, and that robots might be most effective by helping humans perform one of the most complex tasks of all: scheduling. In a pair of new papers, CSAIL researchers demonstrate a robot that, by learning from human workers, can help assign and schedule tasks in fields ranging from medicine to the military.

Human-robot teams to the rescue!


Computers that teach by example

Computers are good at identifying patterns in huge data sets. Humans, by contrast, are good at inferring patterns from just a few examples.In a paper appearing at the Neural Information Processing Society’s conference next week, CSAIL researchers present a new system that bridges these two ways of processing information, so that humans and computers can collaborate to make better decisions.

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