Currently, I am an associate professor at the Shanghai Jiaotong University. Before that, In 2014, I became a postdoctoral associate at the University of California, Los Angeles, under the supervision of Song-Chun Zhu.
    My research interests range across computer vision, machine learning, robotics, and data mining. I have published top-tier journal and conference papers in these four fields, which include topics of deep learning, graph theory, unsupervised learning, object detection, 3D reconstruction, 3D point cloud processing, knowledge mining, and etc.
    Now, I am leading a group for explainable AI. The related topics include explainable CNNs, explainable generative networks, unsupervised semanticization of pre-trained neural networks, and unsupervised/weakly-supervised learning of neural networks. I aim to end-to-end learn interpretable models and/or unsupervisedly transform the black-box knowledge representation of pre-trained neural networks into a hierarchical and semantically interpretable model. Meanwhile, I also expect strong interpretability can ensure high transferability of features and help unsupervised/weakly-supervised learning from small data.