Scholar
Hongzhi Chen
Google Scholar ID: QaU7idMAAAAJ
ByteDance
Citations & Impact
Citations
779
H-index
15
i10-index
19
Publications
20
Co-authors
14
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers, including 'G-Tran: A High Performance Distributed Graph Database with a Decentralized Architecture' (VLDB'22), 'ByteGraph: A High-Performance Distributed Graph Database in ByteDance' (VLDB'22), 'Colorful h-star Core Decomposition' (ICDE'22), 'Fast Maximal Clique Enumeration on Uncertain Graphs: A Pivot-based Approach' (SIGMOD'22), 'Lightning Fast and Space Efficient k-clique Counting' (WWW'22), 'ByteGNN: Efficient Graph Neural Network Training at Large Scale' (VLDB'22), 'BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing' (NSDI'23).
Research Experience
- 08/2022 - present: Staff Software Engineer at ByteDance, Infra Department; 07/2020 - 08/2022: Senior Software Engineer at ByteDance, Infra Department; 02/2019 - 08/2019: Research Intern at HUAWEI, 2012 Lab, Parallel and Distributed Computing Laboratory, MindSpore Team; 05/2017 - 08/2017: Visiting Scholar at NetDB Lab, University of Pennsylvania, Supervisor: Prof. Boon Thau Loo; 09/2015 - 07/2019: Research Assistant at HDL Lab, The Chinese University of Hong Kong, Supervisor: Prof. James Cheng; 06/2014 - 05/2015: Research Intern at Software Analytics Group, Microsoft Research Asia, Supervisor: Qingwei Lin (Leader Researcher) and Dr. Jianguang Lou (Principle Researcher).
Education
- Obtained Ph.D. degree from the Department of Computer Science and Engineering at CUHK, supervised by Prof. James Cheng; received B.E. degree from an Honor Class with 1st-rank, Qingming College, Department of Computer Science and Technology at HUST.
Background
- Research interests cover the broad area of distributed systems and databases, with special emphasis on Graph Database, Graph Neural Network system, and Relational Deep Learning.
Miscellany
- Currently working on a stealth startup.
