Shixing Yu

I am Shixing Yu, a Ph.D. student @ the ECE department, Cornell University. My previous research focuses on using statistical methods to compress neural networks by designing efficient architecture and algorithms. I'm generally interested in energy-efficient solutions for machine learning, sparse neural network analysis, explainable AI and Large Language Models.

Previously, I finished my undergraduate study @ EECS deparment, Peking University, in 2021.

Email: sy774 [at], v-shixingyu [at]

GitHub | GScholar

profile photo

Yucong Liu, Shixing Yu, Tong Lin
Accepted for publication, Journal of NeuroComputing, 2023 [arXiv]
Accepted for publication, Proc. ICLR 2022 (Poster) [OpenReview] [arXiv] [code]
Accepted for publication, Proc. WACV 2022 (Oral) [arXiv] [code]
Accepted for publication, Proc. ISCAS 2022 (MSA-TC Best Paper Award) [arXiv]
Accepted for publication, Proc. NeurIPS 2023 Datasets and Benchmarks (Oral) [arXiv] [code]

Cornell University, Ithaca, NY
Ph.D. in ECE • 09/2023 - now
The University of Texas at Austin, Austin, Texas
M.S.E. in ECE • 09/2021 to 05/2023
Peking University, China
B.Sc. in Computer Science • 09/2017 to 07/2021

Machine Learning Group, Microsoft Research Asia, Beijing, China
Research Intern • 07/2023 - now
Advisor: Dr. Li Zhao
AI + Science Lab, Caltech, Pasadena, CA, USA
Research Intern • 09/2022 to 12/2022
Advisor: Prof. Anima Anandkumar
Autonomous Vechicle Perception Research, NVIDIA Corporation, Santa Clara, CA, USA
Deep Learning Software and Research Intern • 06/2022 to 09/2022
Advisor: Dr. José M. Álvarez
Berkeley Artificial Intelligence Research (BAIR) Lab, University of California, Berkeley, CA, USA
Research Intern • 07/2020 to 01/2021
Advisors: Prof. Kurt Keutzer
Wangxuan Institute of Computer Technology, Peking University, Beijing, China
STRUCT (Spatial and Temporal Restoration, Understanding and Compression Team)
Research Intern • 07/2019 to 06/2021
Advisor: Prof. Jiaying Liu

Website source from Jon Barron and Yaohui Cai.

Last Updated: Aug. 1st, 2022.