Andy Davis

Co-authored the sparsely-gated MoE layer paper: a foundational conditional-computation design.

One of the most important architecture-level thinkers in modern AI, with influence spanning Transformers, efficient scaling, and mixture-of-experts systems.

A foundational figure in modern sequence modeling whose work on the Transformer changed the technical direction of language and multimodal systems.

A foundational transformer researcher whose work still matters because it connects the original architecture shift to later efforts on efficiency, scaling, and sequence modeling infrastructure.

One of the most important optimization researchers of the deep-learning era, especially for work that became default infrastructure across nearly every modern training stack.

A foundational computer-vision researcher whose work on representations and architectures still shapes modern pretraining and perception systems.