Scholar

jie sun

Google Scholar ID: h8MlCpIAAAAJ

Zhejiang University

Machine Learning SystemsGraphHeterogeneous Hardware

Citations & Impact

All-time

Citations

108

H-index

i10-index

Publications

Co-authors

Contact

Resume

Academic Achievements

Legion: Automatically Pushing the Envelope of Multi-GPU System for Billion-Scale GNN Training (USENIX ATC, 2023)
Hyperion: Optimizing SSD Access is All You Need to Enable Cost-efficient Out-of-core GNN Training (IEEE ICDE, 2025)
Helios: Efficient Distributed Dynamic Graph Sampling for Online GNN Inference (PPoPP, 2025)
Moment: Co-optimizing Physical Communication Topology and Data Placement for Multi-GPU Out-of-core GNN Training (SC, Best Student Paper Finalist, 2025)
TorchGT: A Holistic System for Large-scale Graph Transformer Training (SC, 2024)

Research Experience

Involved in multiple research projects, including the development of a large-scale recommendation system in collaboration with Alibaba.

Education

Ph.D. - Department of Computer Science, Zhejiang University, Supervisors: Zeke Wang and Fei Wu

Background

Jie Sun is a fourth-year Ph.D. student in the Department of Computer Science at Zhejiang University, supervised by Zeke Wang and Fei Wu. His areas of interest include machine learning systems, graph computing, and recommendation systems. He focuses on building efficient and scalable machine learning systems (for GNN, DLRM, and LLM) that leverage heterogeneous hardware, such as NVMe SSDs and GPUs, to address large-scale challenges from the industry. Currently, he is collaborating with Alibaba on developing a large-scale recommendation system.

Miscellany