Hi, I am Yu Feng, a third-year PhD student in Computer Science department, U of R. I am interested in computer system in general and programming for fun. Currently, I am working with Prof. Zhu. My current research is about creating a better system for Vision Computing and optimizing Web application platfrom, such as Chromium.
Before I came to U of R, I attended Carnegie Mellon University as Master’s student in Material Science. I worked with Prof. Rollett as a researcher on scientific computing.
3002 Wegmans Hall
Rochester, NY 14620 US
January 2020 - April 2020
Point cloud becomes a common modality in deep learning. We found some common computation patterns that are unique to point cloud, and designed a framework for point cloud deep learning system.
October 2019 - February 2020
Point cloud is a key modality in many visual applications, such as autonomous driving. To enable real-time communications and data transfer, efficient real-time point cloud compression is important. We leverage the temporal and spatial redundancies in and across point cloud and develop an efficient compression technique.
October 2018 - April 2019
The key for Stereo Vision applications is the ability to obtain theambient information and estimate the depth of their surround-ings. We designed a framework, Stereo Engine, that leverages the unique characteristics in stereo vision and supports a wide range of algorithms in this domain.
March 2018 - November 2018
Web applications are mainly user-driven/user-oriented. When and what tasks will be triggered and executed largely depends on user behaviors. It is a open issue for mobile developers to design a scheduler that can fulfill user experience (to speedup) meanwhile decrease the amount of energy consumption. We proposed a proactive event scheduler. Instead of optimizing based on current system state, we expand our optimization scope to speculate future system state. By increasing our optimization scope, we expect to enhance the user experience and lower the energy consumption.