Research

Our work spans core computer vision and interpretability. We study recognition, detection, segmentation, multi-modal perception, and human-in-the-loop evaluation. We develop methods that reveal what models learn and why they succeed or fail, including saliency, concepts, and counterfactuals.

We release code and datasets whenever possible and partner with collaborators across academia and industry to drive responsible AI forward.