About

Jiawei Guan is a Ph.D. Student at Key Laboratory of Data Engineering and Knowledge Engineering and School of Information, Renmin University of China. She’s currently working with Prof. Feng Zhang. Her research focuces on Database System and Theory, High Performance Computing (HPC), and Compression. Her publications are included in top DB (SIGMOD), Sys (ASPLOS), DM (WWW), and ML (NeurIPS) conferences.

Her contact information is listed below:

📮 Email: guanjw@ruc.edu.cn

💬 Wechat: w02141209

🏢 Office: 500, Information Building, No.59 Zhongguancun Street, Haidian District Beijing, 100872, P.R. China.

Research Interests

• HPC: [ASPLOS 2023] [TKDE 2023] [NeurIPS 2022] [WWW 2022]
• Compression: [SIGMOD 2023] [SIGMOD 2024]

Invited Talks

1. TREC: Transient Redundancy Elimination-based Convolution.
   NeurIPS, Virtual, 2022.11 [Video & Slides]
   
2. Data Reuse in ML.
   NCSU, Virtual, 2022.11
   

Publications

2024

1. [SIGMOD’2024] “Homomorphic Compression: Making Text Processing on Compression”, JiaWei Guan, Feng Zhang, Siqi Ma, Kuangyu Chen, Yihua Hu, Yuxing Chen, Anqun Pan, Xiaoyong Du, ACM Symposium on Principles of Database Systems (SIGMOD), 2024. (CCF A) [PDF]
2. [VLDB’2024] “Improving Graph Compression for Efficient Resource-Constrained Graph Analytics”, Qian Xu, Juan Yang, Feng Zhang, Zheng Chen, Jiawei Guan, Kang Chen, Ju Fan, Youren Shen, Ke Yang, Yu Zhang, Xiaoyong Du, VLDB, 2024. (CCF A) [PDF]
3. [VLDB’2024 (demo)] “HocoPG: A Database System with Homomorphic Compression for Text Processing”, Jiawei Guan, Feng Zhang, Yuxin Tang, Weitang Ye, Xiaoyong Du. VLDB (demo) 2024. (CCF A) [PDF]

2023

1. [ASPLOS’2023] “Space-Efficient TREC for Enabling Deep Learning on Microcontrollers”, Jiesong Liu, Feng Zhang, Jiawei Guan, Hsin-Hsuan Sung, Xiaoguang Guo, Xiaoyong Du, Xipeng Shen, ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), March 25, 2023. (CCF A) [PDF]
2. [SIGMOD’2023] “CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression”, Zheng Chen, Feng Zhang, Jiawei Guan, Jidong Zhai, Xipeng Shen, et al., ACM Symposium on Principles of Database Systems (SIGMOD), 2023. (CCF A) [PDF]
3. [TKDE’2022] “Expanding the Edge: Enabling Efficient Winograd CNN Inference With Deep Reuse on Edge Device”, Feng Zhang, Ruofan Wu, Jiawei Guan, Zhen Zheng, Xiaoguang Guo, Xiao Zhang, Xiaoyong Du, Xipeng Shen, IEEE Transactions on Knowledge and Data Engineering (TKDE), April 21, 2023. (CCF A) [PDF]

2022

1. [NeurIPS’2022] “TREC: Transient Redundancy Elimination-based Convolution”, Jiawei Guan, Feng Zhang, Jiesong Liu, Hsin-Hsuan Sung, Ruofan Wu, Xiaoyong Du, Xipeng Shen, NeurIPS, 2022. (CCF A) [Acceptance Rate: 25.6% (2,672/10,411)] [PDF]
2. [WWW’2022] “DREW: Efficient Winograd CNN Inference with Deep Reuse,” Ruofan Wu, Feng Zhang, Jiawei Guan, Zhen Zheng, Xiaoyong Du and Xipeng Shen, The Web Conference (WWW), 2022. (CCF A) [Acceptance rate: 17.7% (323/1,822)] [PDF]