Zhizhuo is interested in computer vision and its ability to make breakthroughs in interdisciplinary fields such as ecology and climatology.

The fellowship will advance her work in inferring relational world knowledge in machines with explicit and implicit representations.

Wang hopes that, by summarizing longer documents, she can make a new class of information more accessible to a variety of audiences.

His work is in the area of coordinating systems of autonomous agents that operate in uncertain, dynamic environments.

Twelve students and faculty co-authored papers spanning several key application areas for AI.

His work on reinforcement learning is aimed at accelerating the training of RL agents.

This distinction recognizes young researchers with exceptional promise who are having an impact on the world.

The project enables neural networks to model how people are positioned based on only partial views of their bodies, like perspective shots in instructional videos or vlogs.