About me
I am a PhD candidate at the Computer Science Department of New York University, advised by Professor Jinyang Li. I am interested in applying system techniques to improving the performance of machine learning systems. Currently, my research primarily focuses on deep learning serving systems.
Before joining NYU, I received my B.S. in Computer Science at Nanjing University, China, where I was advised by Professor Wenzhong Li and I worked on improving performance of wireless network.
Here is my one-page Resume. You can also download a full version of my CV.
Education
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Computer Science PhD Program (2016.9 - Present)
New York University, New York, NY, United States -
B.S. in Computer Science (2012.9 - 2016.6)
Nanjing University, Nanjing, Jiangsu, China -
University Exchange Program (2015.9 - 2016.4)
University of Waterloo, Waterloo, Ontario, Canada
Publications
- Stateful Large Language Model Serving with Pensieve
Lingfan Yu, Jinyang Li
Under Review - Scalable Graph Neural Networks for Heterogeneous Graphs
[paper]
Lingfan Yu, Jiajun Shen, Jinyang Li, Adam Lerer
ArXiv preprint arXiv:2011.09679 - Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs
[paper]
Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander Smola and Zheng Zhang
ICLR’19 Workshop on Representation Learning on Graphs and Manifolds
New Orleans, United States, May 2019 - Low Latency RNN Inference with Cellular Batching
[paper]
Pin Gao, Lingfan Yu (equal contribution), Yongwei Wu, Jinyang Li.
Eurosys’18
Porto, Portugal, April 2018. - The Efficient Server Audit Problem, Deduplicated Re-execution, and the Web
[paper]
Cheng Tan, Lingfan Yu, Joshua B. Leners, Michael Walfish.
SOSP’17 (Best paper award)
Shanghai, China, October 2017
Work Experience
- Research Intern at Facebook AI Research, Facebook, Inc. (2020.5 - 2020.9)
- Applied Scientist Intern at Amazon Web Services, Inc. (2019.6 - 2019.8)