Expected to total $540K over the next five years, the award supports his research in improving how autonomous AI agents learn and collaborate in complex, real-world environments.

His research focuses on efficient high-quality rendering, signal processing techniques for computer graphics, data-driven modeling and animation, and point-based methods.

The funding supports a crossdisciplinary team investigating new interfaces, techniques and tools that encourage children ages 5–10 to build and program their own interactive wearables.

Penghui Yao is studying quantum communication, revealing that quantum messages need more qubits than anticipated, even in ideal conditions, and that interactive communication can require far more qubits than the information itself.

Elissa Redmiles was recognized for her research on helping users make security decisions online, which aims to improve security education for at-risk users.

The essay discusses how machine learning is transforming the prediction of human behavior, highlighting challenges like data "noise" and rare-event prediction, while emphasizing its potential in fields such as national security and health.

The researchers created a 3-minute "edutainment" video that improves software updating practices, showing that entertaining educational videos are more effective than traditional text-based security advice.

He was specifically recognized for his major contributions to algorithms, the uses of randomization in algorithms, randomness in networks, and the real-world applications of these topics.