Shixing Yu

I am Shixing Yu (于世兴), a first year Ph.D. @ the ECE department, The University of Texas Austin, jointly advised by Prof. Atlas(Zhangyang) Wang and Prof. Diana Marculescu. I'm interested in using statistical methods to compress neural networks (Pruning, Quantization, Distillation, NAS) and analyze network sparsity. My research interest also lies in all kinds of computer vision topics, e.g. the recently popular Vision Transformer.

Currently, I'm also a research intern @ NVIDIA Corp. with the AV perception team for Deep Learning Software and Research under the guidance of Jose Alvarez

Previously, I finished my undergraduate study @ EECS deparment, Peking University, in 2021, where I was working with Prof. Jiaying Liu on image/video processing.

I also worked as a visiting student researcher @ University of California, Berkeley, in Summer 2020, where I had the priviledge of working with Prof. Kurt Keutzer and Prof. Michael Mahoney.

Email: shixingyu [at] utexas.edu, shixingy [at] nvidia.com

GitHub

profile photo

Publications
Accepted for publication, Proc. ICLR 2022 (Poster) [OpenReview] [arXiv] [code]
Accepted for publication, Proc. WACV 2022 (Poster) [arXiv] [code]
Accepted for publication, Proc. ISCAS 2022 (MSA-TC Best Paper Award)


Education
The University of Texas at Austin, U.S.
Ph.D. in ECE • Sep. 2021 to Present
Peking University, China
B.Sc. in Data Science • Sep. 2017 to July 2021

Experiences
NVIDIA Corporation, Santa Clara, CA, USA
Autonomous Vechicle Perception Research Group
Deep Learning Software and Research Intern • June 2022 to present
Advisor: Dr. José M. Álvarez
Berkeley Artificial Intelligence Research (BAIR) Lab, University of California, Berkeley, CA, USA
Research Intern • July 2020 to Jan 2021
Advisors: Professor Kurt Keutzer
Wangxuan Institute of Computer Technology, Peking University, Beijing, China
STRUCT (Spatial and Temporal Restoration, Understanding and Compression Team)
Research Intern • July 2019 to June 2021
Advisor: Professor Jiaying Liu

Website source from Jon Barron and Yaohui Cai.

Last Updated: Feb. 1st, 2022.