We are tackling fundamental open problems in machine learning and computer vision research to achieve deep understanding of visual world. High-level visual perception involves automated image and video analysis, computational geometry, and visual reasoning. Our curiosity on highly structured knowledge, images and videos lead us to study the underlying non-Euclidean space and generalize models, including deep neural networks, to manifolds, and graphs.