About Me

Hi, I am Yu Feng, a fifth-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 research interest is about designing algorithms and frameworks for Mobile Vision Computing, including but not limited to in-sensor computing, point cloud-based applications, stereo vision.

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.

Contact Details

Yu Feng
3002 Wegmans Hall
Rochester, NY 14620 US

(412)706-4492
yfeng28@ur.rochester.edu

Education

University of Rochester

PhD in Computer Science. Rochester, NY. Until now.

Carnegie Mellon University

Master of Material Science. Pittsburgh, PA. 2015-2017.

Tianjin Polytechnic University

Bachelor of Material Science. Tianjin, CHINA. 2011-2015.

Research

Taming Memory Irregular in Deep Point Cloud Analytics

July 2021 - February 2022

Point cloud has become an important modality in many computer vision applications. However, the main operations in point cloud algorithms are memory-inefficient due to its irregularity and redundancy. We proposed a algorithm-hardware co-design approach to tame the memory irregularity without compromising the overall accuracy.

LiDAR-guided Video Enhancement

Match 2021 - July 2021

Pixel flow is an important cue for many video enhancement tasks. However, accurate pixel flow is hard to obtain for many monocular vision tasks. This work proposes a lightweight and fast algorithm to leverage the synchronized LiDAR to obtain a sparse pixel flow. Using the sparse pixel flow, we propose an unified framework to improve the performance of many video enhancement tasks.

Real-time Event-driven Eye Tracking for AR/VR

September 2020 - February 2021

Eye tracking is an key application to enable many AR/VR applications. This project is inspired by the novel event-camera and design a mechanism to emulate the events in software. The software-emulated event allows us to effectively predict the eye region and only process the useful pixels to speedup the eye tracking pipeline.

Efficient Deep Learning for Point Cloud

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.

Real-time Point Cloud Compression

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.

Co-Design Stereo Vision System

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.

Task Scheduling in Runtime Application

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.

Experience

Meta Reality Labs

Color VR Passthrough. May 2022 - October 2022

Facebook Reality Labs

Event-based Eye Tracking. September 2020 - December 2020

Google AI

Smart Code Instruction Prefetching. May 2019 - September 2019

Publications

Conference Articles

Crescent: Taming Memory Irregularities for Accelerating Deep Point Cloud Analytics, ISCA 2022. [code]

Yu Feng, Gunnar Hammonds, Yiming Gan, Yuhao Zhu

Real-Time Gaze Tracking with Event-Driven Eye Segmentation, IEEE VR 2022. [slide][talk][code]

Yu Feng, Nathan Goulding-Hotta, Asif Khan, Hans Reyserhove, Yuhao Zhu

Mesorasi: Enabling Efficient Point Cloud Analytics via Delayed-Aggregation, MICRO 2020. [slide][talk][code]

Yu Feng*, Boyuan Tian*, Tiancheng Xu*, Paul Whatmough, Yuhao Zhu

(*: first three authors are equal-contribution.)
Real-Time Spatio-Temporal LiDAR Point Cloud Compression, IROS 2020. [slide][talk][code]

Yu Feng, Shaoshan Liu, Yuhao Zhu

ASV: Accelerated Stereo Vision System, MICRO 2019. [slide]

Yu Feng, Paul Whatmough, Yuhao Zhu

PES: Proactive Event Scheduling for Responsive and Energy-Efficient Mobile Web Computing, ISCA 2019. [slide]

Yu Feng, Yuhao Zhu

Journal Articles

Extension of the Mechanical Threshold Stress Model to Static and Dynamic Strain Aging: Application to AA5754-O, 21 August 2017.

Yu Feng, Sudipto Mandal, Brian Gockel & Anthony D. Rollett

Skills

Programming Languages

C, C++, Python, Java, Halide, Ruby

Other Toolkits

Matlab, OpenGL(basic)

Database

MySQL, HBase(basic)