Short Bio

Dr. Xin Zhang obtained his PhD degree in Individualized Interdisciplinary Program (Data Science and Analytics) from The Hong Kong University of Science and Technology (HKUST) in 2026, under the supervision of Professor Lei Chen (ACM & IEEE Fellow). He received his Bachelor’s degree in Intelligence Science and Technology from Peking University (PKU) in 2020, where he was advised by Professor Bin Cui (IEEE Fellow).

Research Interest

Dr. Xin Zhang’s research focuses on building Machine Learning Systems for modern deep learning workloads, including Large Language Models, Graph Neural Networks, and Recommendation Models. His work spans the full model lifecycle, addressing challenges in both scalable training and efficient serving.

Publications

Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling.
Xin Zhang, Yanyan Shen, Yingxia Shao, Haoyang Li, Lei Chen.
PVLDB 2026. [paper] [code]

Graph Neural Network Training: From Data Management Perspective
Springer Nature 2026. [book]

RelServe: Fast LLM Inference Serving on Relational Data.
Xin Zhang, Shihong Gao, Yanyan Shen, Haoyang Li, Lei Chen.
Preprint 2025. [paper]

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]

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

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]

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]

Feature-Oriented Sampling for Fast and Scalable GNN Training.
Xin Zhang, Yanyan Shen, Lei Chen.
ICDM 2022. [paper] [code]

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 2019. [paper]

Services

Invited journal reviewer:

• TPAMI (IEEE Transactions on Pattern Analysis and Machine Intelligence) 2026
• TPDS (IEEE Transactions on Parallel and Distributed Systems) 2026
• TC (IEEE Transactions on Computers) 2026
• TSC (IEEE Transactions on Services Computing) 2026
• TMC (IEEE Transactions on Mobile Computing) 2026
• TMM (IEEE Transactions on Multimedia) 2026
• TAC (IEEE Transactions on Affective Computing) 2026
• FCS (Frontiers of Computer Science) 2026

Last Update: August 2026