Fei Gao

Multi-agent path finding can reliably scale to 100,000 agents in dense 3D spaces by treating neural networks as counterfactually gated advisors over classical priority inheritance rather than end-to-end controllers.

A generalized Medical Imaging Disentanglement Learning framework that outperforms state-of-the-art supervised and self-supervised classification methods in accuracy across all datasets and successfully isolates target-specific latent representations.

COPA is a robust active-perception framework for global-state-free aerial-ground cooperation that derives an active-perception model that relates UAV motion, gimbal angle, and UGV motion to the target image-plane state and uses these predictions to jointly optimize UAV and gimbal control.