Yuan Zhou

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.