The theory to the application aspects of machine learning (ML). Most recently, he studies deep neural networks (DNNs) model compression with sparsity and low-bit quantization, efficient deep learning algorithms for training/inference acceleration, mobile/edge device computation, optimization, as well as their applications in various computer vision tasks.