I am a Computer Science PhD student at New York University advised by Professor Jinyang Li, and I am also a proud member of NYU System Group. I am broadly interested in doing research in distributed computing frameworks. Currently, my primary research work focuses on applying system techniques to improving the performance of machine learning frameworks.
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
- Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs
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
Lingfan Yu, Pin Gao (equal contribution), Yongwei Wu, Jinyang Li.
Porto, Portugal, April 2018.
- The Efficient Server Audit Problem, Deduplicated Re-execution, and the Web
Cheng Tan, Lingfan Yu, Joshua B. Leners, Michael Walfish.
SOSP’17 (Best paper award)
Shanghai, China, October 2017
- Applied Scientist Internship at Amazon Web Services, Inc. (2019.6 - 2019.8)