Use of Training, Validation, and Test Sets for Developing Automated Classifiers in Quantitative Ethnography. - Seung B. Lee; Xiaofan Gui; Megan Manquen; Eric R. Hamilton (ICQE, 2019)

Application of AutoML in the Automated Coding of Educational Discourse Data. - Seung B. Lee; Xiaofan Gui; Eric Hamilton 001 (ICLS, 2020)

UADB: Unsupervised Anomaly Detection Booster. - Hangting Ye; Zhining Liu 002; Xinyi Shen; Wei Cao 007; Shun Zheng 001; Xiaofan Gui; Huishuai Zhang; Yi Chang 001; Jiang Bian 002 (ICDE, 2023)

Learning Intra- and Inter-Cell Differences for Accurate Battery Lifespan Prediction across Diverse Conditions. - Han Zhang; Yuqi Li; Shun Zheng 001; Ziheng Lu; Xiaofan Gui; Wei Xu 005; Jiang Bian 002 (CoRR, 2023)

BatteryML: An Open-source Platform for Machine Learning on Battery Degradation. - Han Zhang; Xiaofan Gui; Shun Zheng 001; Ziheng Lu; Yuqi Li; Jiang Bian 002 (ICLR, 2024)

Battery lifetime prediction across diverse ageing conditions with inter-cell deep learning. - Han Zhang; Yuqi Li; Shun Zheng 001; Ziheng Lu; Xiaofan Gui; Wei Xu 005; Jiang Bian 002 (Nat. Mac. Intell., 2025)

Chemistry-aware battery degradation prediction under simulated real-world cyclic protocols. - Yuqi Li; Han Zhang; Xiaofan Gui; Zhao Chen; Yu Li; Xiwen Chi; Quan Zhou; Shun Zheng 001; Ziheng Lu; Wei Xu 005; Jiang Bian 002; Liquan Chen; et al. (CoRR, 2025)