Yuhan Hu

Robots can learn to adapt their manipulation styles dynamically, achieving compositional generalization across diverse tasks with a single framework.

Personalized federated learning can now handle the messy reality of heterogeneous industrial data, enabling more accurate failure time predictions across diverse clients.