Dr. Huang's research spans the fields of computer vision, computer graphics, and machine learning, and publishes extensively in venues such as SIGGRAPH, CVPR, ICCV, ECCV, NeuriPS, ICML, and etc. In particular, his recent focus is on developing machine learning algorithms (particularly deep learning) that leverage Big Data to solve core problems in computer vision, computer graphics and computational biology. He is also interested in statistical data analysis, compressive sensing, low-rank matrix recovery, and large-scale optimization, which provides theoretical foundation for his research. He also received the best paper award at the Symposium on Geometry Processing 2013, the best dataset award at the Symposium on Geometry Processing 2018, and the most cited paper award of Computer-Aided Geometric Design in 2010 and 2011.