EEG-based Recognition of Driver State Related to Situation Awareness Using Graph Convolutional Networks. - Ruilin Li 001; Zirui Lan; Jian Cui 001; Olga Sourina; Lipo Wang (CW, 2020)

A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG. - Jian Cui 001; Zirui Lan; Yisi Liu; Ruilin Li 001; Fan Li 015; Olga Sourina; Wolfgang Müller-Wittig (CoRR, 2021)

Situation Awareness Recognition Using EEG and Eye-Tracking data: a pilot study. - Ruilin Li 001; Jian Cui 001; Ruobin Gao; Ponnuthurai N. Suganthan; Olga Sourina; Lipo Wang; Chun-Hsien Chen (CW, 2022)

Advanced Ensemble Deep Random Vector Functional Link for Eye-Tracking-based Situation Awareness Recognition. - Ruilin Li 001; Ruobin Gao; Jian Cui 001; Ponnuthurai N. Suganthan; Olga Sourina (SSCI, 2022)

A Decomposition-Based Hybrid Ensemble CNN Framework for Improving Cross-Subject EEG Decoding Performance. - Ruilin Li 001; Ruobin Gao; Ponnuthurai N. Suganthan (CoRR, 2022)

Sample-Based Data Augmentation Based on Electroencephalogram Intrinsic Characteristics. - Ruilin Li 001; Lipo Wang; Ponnuthurai N. Suganthan; Olga Sourina (IEEE J. Biomed. Health Informatics, 2022)

Heart Rate Based Cross-subject Stress Recognition. - Joanne Tan; Wei Lun Lim; Ruilin Li 001; Meng-Hsueh Hsieh; Olga Sourina; Chun-Hsien Chen (CW, 2023)

Benchmarking EEG-based Cross-dataset Driver Drowsiness Recognition with Deep Transfer Learning. - Jian Cui 001; Liqiang Yuan; Ruilin Li 001; Zhaoxiang Wang; Dongping Yang; Tianzi Jiang (EMBC, 2023)

Ensemble of Randomized Neural Network and Boosted Trees for Eye-Tracking-Based Driver Situation Awareness Recognition and Interpretation. - Ruilin Li 001; Minghui Hu 001; Jian Cui 001; Lipo Wang; Olga Sourina (ICONIP (3), 2023)

Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning. - Ruobin Gao; Ruilin Li 001; Minghui Hu 001; Ponnuthurai Nagaratnam Suganthan; Kum Fai Yuen (Eng. Appl. Artif. Intell., 2023)

An enhanced ensemble deep random vector functional link network for driver fatigue recognition. - Ruilin Li 001; Ruobin Gao; Liqiang Yuan; Ponnuthurai N. Suganthan; Lipo Wang; Olga Sourina (Eng. Appl. Artif. Intell., 2023)

Towards best practice of interpreting deep learning models for EEG-based brain computer interfaces. - Jian Cui 001; Liqiang Yuan; Zhaoxiang Wang; Ruilin Li 001; Tianzi Jiang (Frontiers Comput. Neurosci., 2023)

A decomposition-based hybrid ensemble CNN framework for driver fatigue recognition. - Ruilin Li 001; Ruobin Gao; Ponnuthurai Nagaratnam Suganthan (Inf. Sci., 2023)

Online dynamic ensemble deep random vector functional link neural network for forecasting. - Ruobin Gao; Ruilin Li 001; Minghui Hu 001; Ponnuthurai N. Suganthan; Kum Fai Yuen (Neural Networks, 2023)

A spectral-ensemble deep random vector functional link network for passive brain-computer interface. - Ruilin Li 001; Ruobin Gao; Ponnuthurai N. Suganthan; Jian Cui 001; Olga Sourina; Lipo Wang (Expert Syst. Appl., 2023)

Heart Rate based Fatigue Recognition for Human Factors Evaluation. - Wei Lun Lim; Chang Shen Hoe; Ruilin Li 001; Meng-Hsueh Hsieh; Ziqing Xia; Olga Sourina; Chun-Hsien Chen (CW, 2024)

Noise Elimination in Deep Random Vector Functional Link Network for Tabular Classification. - Minghui Hu 001; Ruilin Li 001; Ruobin Gao; Ponnuthurai N. Suganthan (IJCNN, 2024)

Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking. - Zijian Dong 001; Ruilin Li 001; Yilei Wu; Thuan Tinh Nguyen; Joanna Su Xian Chong; Fang Ji; Nathanael Ren Jie Tong; Christopher Li Hsian Chen; Juan Helen Zhou (NeurIPS, 2024)

TFormer: A time-frequency Transformer with batch normalization for driver fatigue recognition. - Ruilin Li 001; Minghui Hu 001; Ruobin Gao; Lipo Wang; Ponnuthurai N. Suganthan; Olga Sourina (Adv. Eng. Informatics, 2024)

A benchmarking framework for eye-tracking-based vigilance prediction of vessel traffic controllers. - Zhimin Li; Ruilin Li 001; Liqiang Yuan; Jian Cui 001; Fan Li 015 (Eng. Appl. Artif. Intell., 2024)

Entropy-guided robust feature domain adaptation for electroencephalogram-based cross-dataset drowsiness recognition. - Liqiang Yuan; Jian Cui 001; Ruilin Li 001; Zhong Zheng; Mohammed Yakoob Siyal; Zhengkun Yi (Eng. Appl. Artif. Intell., 2024)

SPARK: A High-Efficiency Black-Box Domain Adaptation Framework for Source Privacy-Preserving Drowsiness Detection. - Liqiang Yuan; Ruilin Li 001; Jian Cui 001; Mohammed Yakoob Siyal (IEEE J. Biomed. Health Informatics, 2024)

EEG-Based Cross-Dataset Driver Drowsiness Recognition With an Entropy Optimization Network. - Liqiang Yuan; Shasha Zhang; Ruilin Li 001; Zhong Zheng; Jian Cui 001; Mohammed Yakoob Siyal (IEEE J. Biomed. Health Informatics, 2025)

Stacked Ensemble Deep Random Vector Functional Link Network With Residual Learning for Medium-Scale Time-Series Forecasting. - Ruobin Gao; Minghui Hu 001; Ruilin Li 001; Xuewen Luo; Ponnuthurai Nagaratnam Suganthan; Muhammad Tanveer 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)