GraphScSh: Efficient I/O Scheduling and Graph Sharing for Concurrent Graph Processing. - Shang Liu 001; Zhan Shi 001; Dan Feng 001; Shuo Chen; Fang Wang 001; Yamei Peng (NPC, 2019)

CSMqGraph: Coarse-Grained and Multi-external-storage Multi-queue I/O Management for Graph Computing. - Shuo Chen; Zhan Shi 001; Dan Feng 001; Shang Liu 001; Fang Wang 001; Lei Yang 018; Ruili Yu (Int. J. Parallel Program., 2020)

LSM-Subgraph: Log-Structured Merge-Subgraph for Temporal Graph Processing. - Jingyuan Ma; Zhan Shi 001; Shang Liu 001; Wang Zhang 002; Yutong Wu 013; Fang Wang 001; Dan Feng 001 (APWeb/WAIM (1), 2022)

A Crypto-Assisted Approach for Publishing Graph Statistics with Node Local Differential Privacy. - Shang Liu 001; Yang Cao 011; Takao Murakami; Masatoshi Yoshikawa (IEEE Big Data, 2022)

CARGO: Crypto-Assisted Differentially Private Triangle Counting Without Trusted Servers. - Shang Liu 001; Yang Cao 011; Takao Murakami; Jinfei Liu; Masatoshi Yoshikawa (ICDE, 2024)

Federated Graph Analytics with Differential Privacy. - Shang Liu 001; Yang Cao 011; Takao Murakami; Weiran Liu; Seng Pei Liew; Tsubasa Takahashi 001; Jinfei Liu; Masatoshi Yoshikawa (CoRR, 2024)

Federated Graph Condensation with Information Bottleneck Principles. - Bo Yan 005; Sihao He; Cheng Yang 002; Shang Liu 001; Yang Cao 011; Chuan Shi 001 (AAAI, 2025)

PGB: Benchmarking Differentially Private Synthetic Graph Generation Algorithms. - Shang Liu 001; Hao Du; Yang Cao 011; Bo Yan 005; Jinfei Liu; Masatoshi Yoshikawa (ICDE, 2025)

Privacy in Fine-Tuning Large Language Models: Attacks, Defenses, and Future Directions. - Hao Du; Shang Liu 001; Lele Zheng; Yang Cao 011; Atsuyoshi Nakamura; Lei Chen (PAKDD (4), 2025)

An interpretable and efficient multi-scale spatio-temporal neural network for traffic flow forecasting. - Wenzhu Zhao; Guan Yuan; Yanmei Zhang; Xiao Liu; Shang Liu 001; Lei Zhang 110 (Expert Syst. Appl., 2026)