About

I am currently a fourth-year Ph.D. candidate in the DB4AI group at The Hong Kong University of Science and Technology (HKUST) supervised by Professor Lei Chen (ACM & IEEE Fellow). My research interest is building efficient systems for popular deep learning models, such as Large Language Models, Graph Neural Networks, and Recommendation Models. I received my Bachelor’s degree (2016-2020) from the School of EECS at Peking University (PKU), where I was advised by Professor Bin Cui (IEEE Fellow) and Professor Sujian Li. I have done several research&engineering internships at MSRA, Tencent, and Baidu.

The pronounciation of my Chinese name is similar to Sheen (for Xin/鑫) Jung (for Zhang/张) in English :)

Publications

Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving
Shihong Gao, Xin Zhang, Yanyan Shen, Lei Chen.
SIGMOD 2025. [paper] [code] (regular research track)

Efficient Training of Graph Neural Networks on Large Graphs.
Yanyan Shen, Lei Chen, Jingzhi Fang, Xin Zhang, Shihong Gao, Hongbo Yin.
VLDB 2024. [paper] [code] (tutorial track)

SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement.
Shihong Gao, Yiming Li, Xin Zhang, Yanyan Shen, Yingxia Shao, Lei Chen.
SIGMOD 2024. [paper] [code] (regular research track)

DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU.
Xin Zhang, Yanyan Shen, Yingxia Shao, Lei Chen.
SIGMOD 2023. [paper] [code] (regular research track)

Feature-Oriented Sampling for Fast and Scalable GNN Training.
Xin Zhang, Yanyan Shen, Lei Chen.
ICDM 2022. [paper] [code] (accept rate=85/870)

HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training.
Xupeng Miao, Yining Shi, Hailin Zhang, Xin Zhang, Xiaonan Nie, Zhi Yang, Bin Cui.
SIGMOD 2022. [paper] [code]

Machine Reading Comprehension: a Literature Review.
Xin Zhang, An Yang, Sujian Li, Yizhong Wang.
Preprint on arXiv, 2019. [paper]

Last Update: April 2025