Xiaofeng Ren is a research scientist at the Intel Science and Technology Center (ISTC) on Pervasive Computing, Intel Labs, and an affiliate assistant professor at the University of Washington. His research interests are broadly in the areas of computer vision and its applications, including image features, grouping and segmentation, object recognition, scene understanding, activity recognition and motion analysis. His goal is to understand and solve fundamental computer vision problems in everyday life settings, thus providing rich information for future intelligent systems such as personal assistants, smart homes and robots. His current research themes include the use of RGB-D cameras (Kinect-style color+depth) and that of wearable cameras. He has published over 30 research papers at top conferences and journals. He received his Ph.D. from University of California, Berkeley, his M.S. from Stanford University, and his B.S. from Zhejiang University. Prior to joining Intel in 2008, he was on the research faculty of Toyota Technological Institute at Chicago.