Biobanks collect and store large amounts of data that researchers use to conduct a wide range of studies. Making sure participants understand what they’re getting into can help build trust in science.

A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.

A new study finds human supervisors have the potential to reduce barriers to deploying autonomous vehicles.

Through the Multidisciplinary University Research Initiative, the US Department of Defense supports research projects in areas of critical importance to national defense.

A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.

The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.

We can now store information outside of our brains, and use computers to retrieve it. That ought to make learning and remembering easy, right?

Associate Professor Tamara Broderick and colleagues build a “taxonomy of trust” to identify where in data analysis processes confidence in its results might break down.

By keeping data fresh, the system could help robots inspect buildings or search disaster zones.

Even after January’s storms, California faces a water-scarce future. An economist and an engineer propose a way to test higher water prices as a conservation strategy without hurting low-income users.