Head Pose Estimation with Improved Random Regression Forests. - Ronghang Zhu; Gaoli Sang; Ying Cai; Jian You; Qijun Zhao (CCBR, 2013)

A Novel Iterative Approach to Pupil Localization. - Ronghang Zhu; Gaoli Sang; Wei Gao; Qijun Zhao (CCBR, 2014)

A transfer learning approach to cross-database facial expression recognition. - Ronghang Zhu; Tingting Zhang; Qijun Zhao; Zhihong Wu (ICB, 2015)

Glasses Detection Using Convolutional Neural Networks. - Li Shao; Ronghang Zhu; Qijun Zhao (CCBR, 2016)

Discriminative Feature Adaptation for cross-domain facial expression recognition. - Ronghang Zhu; Gaoli Sang; Qijun Zhao (ICB, 2016)

Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition. - Feng Liu 013; Ronghang Zhu; Dan Zeng 002; Qijun Zhao; Xiaoming Liu 002 (CVPR, 2018)

Self-supervised Universal Domain Adaptation with Adaptive Memory Separation. - Ronghang Zhu; Sheng Li 001 (ICDM, 2021)

Transferable Feature Learning on Graphs Across Visual Domains. - Ronghang Zhu; Xiaodong Jiang; Jiasen Lu; Sheng Li 001 (ICME, 2021)

Automated Graph Learning via Population Based Self-Tuning GCN. - Ronghang Zhu; Zhiqiang Tao; Yaliang Li; Sheng Li 001 (SIGIR, 2021)

CrossMatch: Cross-Classifier Consistency Regularization for Open-Set Single Domain Generalization. - Ronghang Zhu; Sheng Li 001 (ICLR, 2022)

Pairwise Adversarial Training for Unsupervised Class-imbalanced Domain Adaptation. - Weili Shi; Ronghang Zhu; Sheng Li 001 (KDD, 2022)

Self-supervision based Semantic Alignment for Unsupervised Domain Adaptation. - Ronghang Zhu; Sheng Li 001 (SDM, 2022)

Progressive Mix-Up for Few-Shot Supervised Multi-Source Domain Transfer. - Ronghang Zhu; Xiang Yu 002; Sheng Li 001 (ICLR, 2023)

XDC: Adaptive Cross Domain Short Text Clustering. - Saed Rezayi; Handong Zhao; Ronghang Zhu; Sheng Li 001 (SDM, 2023)

Trustworthy Representation Learning Across Domains. - Ronghang Zhu; Dongliang Guo 002; Daiqing Qi; Zhixuan Chu; Xiang Yu 002; Sheng Li 001 (CoRR, 2023)

Semi-Supervised Single Domain Generalization with Label-Free Adversarial Data Augmentation. - Ronghang Zhu; Xiang Yu 002; Sheng Li 001 (Trans. Mach. Learn. Res., 2023)

Co-Embedding of Nodes and Edges With Graph Neural Networks. - Xiaodong Jiang; Ronghang Zhu; Pengsheng Ji; Sheng Li 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Cross-Domain Graph Convolutions for Adversarial Unsupervised Domain Adaptation. - Ronghang Zhu; Xiaodong Jiang; Jiasen Lu; Sheng Li 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Open-Set Graph Domain Adaptation via Separate Domain Alignment. - Yu Wang; Ronghang Zhu; Pengsheng Ji; Sheng Li 001 (AAAI, 2024)

Graph Neural Networks for lightweight plant organ tracking. - Daniel Petti; Ronghang Zhu; Sheng Li 001; Changying Li (Comput. Electron. Agric., 2024)

No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users. - Mengxuan Hu; Hongyi Wu; Zihan Guan 001; Ronghang Zhu; Dongliang Guo 002; Daiqing Qi; Sheng Li 001 (CoRR, 2024)

A Survey of Trustworthy Representation Learning Across Domains. - Ronghang Zhu; Dongliang Guo 002; Daiqing Qi; Zhixuan Chu; Xiang Yu 002; Sheng Li 001 (ACM Trans. Knowl. Discov. Data, 2024)

Unsupervised Class-Imbalanced Domain Adaptation With Pairwise Adversarial Training and Semantic Alignment. - Weili Shi; Ronghang Zhu; Sheng Li 001 (IEEE Trans. Circuits Syst. Video Technol., 2024)

Revisiting Source-Free Domain Adaptation: Insights into Representativeness, Generalization, and Variety. - Ronghang Zhu; Mengxuan Hu; Weiming Zhuang; Lingjuan Lyu; Xiang Yu 002; Sheng Li 001 (CVPR, 2025)

Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety. - Zihan Guan 001; Mengxuan Hu; Ronghang Zhu; Sheng Li 001; Anil Vullikanti (CoRR, 2025)