Presenter

Qixing Huang is an associate professor of Computer Science at the University of Texas at Austin. He obtained his PhD in Computer Science from Stanford University. He was a research assistant professor at Toyota Technological Institute at Chicago before joining UT Austin. 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, ICLR and etc. In particular, his recent focus is on developing 3D generative models that enforce geometric, physical, and topological priors and learn from both 3D and 2D that address issues of limited 3D data and generalization. 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, IJCAI Career Spotlight, and an NSF Career award.