Jianwen Xie

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Jianwen Xie is a research scientist at Hikvision Research America. Prior to his position at Hikvision, he worked as a postdoctoral researcher and a staff research associate at UCLA for about one year after receiving his Ph.D. in Statistics there.

Jianwen received his B.Eng. in Software Engineering from Jinan University in 2008. During his studies, he worked as a research assistant in the Department of Computer Science and on various projects related to mathematical modeling, among other research areas. In 2012, he received his M.S. in Computer Science from UCLA and went on to get another M.S. in Statistics there as well in 2014. He received his Ph.D in Statistics in 2016.

During his first year of Ph.D. studies, Jianwen worked as graduate student researcher first at the Center for Image and Vision Science. His project that year was titled “Discriminatively Trained Mixture of Active Basis Models for Object Recognition.” He spent his final three years at the Center for Vision, Cognition, Learning, and Art for three years. His projects there were titled, “Unsupervised Learning Compositional Sparse Codes for Natural Images Representation and “Comparison of Different Dictionary Learning Techniques for fMRI Classification.” He also spent a summer at Nokia in Berkeley as a computer vision research intern. His project there proposed an improvement to one aspect of autonomous driving technology. For more information on these projects, visit https://www.linkedin.com/in/jianwen-xie-6904963a/.

Jianwen Xie knows machine learning, C++, and Matlab and has experience in computer vision, data mining, algorithms, mathematical modeling, programming, and more. He speaks English, Chinese, and Cantonese. His research interests include statistical modeling and computing, machine learning, computer vision, and artificial intelligence.