Professor Su is interested in fundamental problems in broad disciplines related to artificial intelligence, including machine learning, computer vision, computer graphics, robotics, and smart manufacturing. His work of ShapeNet, PointNet series, and graph CNNs have significantly impacted the emergence and growth of a new field, 3D deep learning. He used to work on ImageNet, a large-scale 2D image database, which is important for the recent breakthrough of computer vision. Applications of Su's research include robotics, autonomous driving, virtual/augmented reality, smart manufacturing, etc.