Liu Liu

Liu Liu
Assistant Professor
Electrical, Computer, and Systems Engineering
(518) 276-6718

Liu Liu has been with the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI) as an assistant professor since July 2022. He has a Ph.D. in Computer Science at University of California, Santa Barbara. His research interests reside in the intersection between computer architecture and machine learning, towards high-performance, energy-efficient, and robust machine intelligence. He leads the research on Elastic Processing & Hardware Architectures, with publications in top-tier conferences on machine learning and computer architecture (e.g., ICML, ICLR, MICRO, and ASPLOS). He earned an M.S. in Electrical and Computer Engineering from UC Santa Barbara in 2015. He is a recipient of the Peter J Frenkel Fellowship from the Institute of Energy Efficiency at UCSB.

Education

Ph.D. in Computer Science, University of California, Santa Barbara, 2022
M.S. in Electrical & Computer Engineering, University of California, Santa Barbara, 2015
B.E. in Optoelectronics, University of Electronic Science and Technology of China, 2013

Focus Area

Computer Architecture, Machine Learning Systems

Selected Scholarly Works

Zheng Qu, Liu Liu, Fengbin Tu, Zhaodong Chen, Yufei Ding, and Yuan Xie. "DOTA: detect and omit weak attentions for scalable transformer acceleration." In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), pp. 14-26. 2022.

Liu Liu, Jilan Lin, Zheng Qu, Yufei Ding, and Yuan Xie. "ENMC: Extreme Near-Memory Classification via Approximate Screening." In 2021 54th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), pp. 1309-1322.

Liu Liu, Zheng Qu, Lei Deng, Fengbin Tu, Shuangchen Li, Xing Hu, Zhenyu Gu, Yufei Ding, and Yuan Xie. "Duet: Boosting deep neural network efficiency on dual-module architecture." In 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), pp. 738-750.

Liu Liu, Lei Deng, Zhaodong Chen, Yuke Wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, and Yuan Xie. "Boosting deep neural network efficiency with dual-module inference." In 2020 International Conference on Machine Learning (ICML), pp. 6205-6215.

Liu Liu, Lei Deng, Xing Hu, Maohua Zhu, Guoqi Li, Yufei Ding, and Yuan Xie. "Dynamic Sparse Graph for Efficient Deep Learning." In 2019 International Conference on Learning Representations (ICLR).