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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] cornell.edu, v-shixingyu [at] microsoft.com
GitHub |
GScholar
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Publications
Accepted for publication, Journal of NeuroComputing, 2023
[arXiv]
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Accepted for publication, Proc. ISCAS 2022 (MSA-TC Best Paper Award)
[arXiv]
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Accepted for publication, Proc. NeurIPS 2023 Datasets and Benchmarks (Oral)
[arXiv]
[code]
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Education
Cornell University, Ithaca, NY
Ph.D. in ECE • 09/2023 - now
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The University of Texas at Austin, Austin, Texas
M.S.E. in ECE • 09/2021 to 05/2023
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Peking University, China
B.Sc. in Computer Science • 09/2017 to 07/2021
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Experiences
Machine Learning Group, Microsoft Research Asia, Beijing, China
Research Intern • 07/2023 - now
Advisor: Dr. Li Zhao
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AI + Science Lab, Caltech, Pasadena, CA, USA
Research Intern • 09/2022 to 12/2022
Advisor: Prof. Anima Anandkumar
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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
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Berkeley Artificial Intelligence Research (BAIR) Lab, University of California, Berkeley, CA, USA
Research Intern • 07/2020 to 01/2021
Advisors: Prof. Kurt Keutzer
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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
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