Automatic Optical Coherence Tomography Imaging of Stationary and Moving Eyes with a Robotically-Aligned Scanner. - Mark Draelos; Pablo Ortiz; Ruobing Qian; Brenton Keller; Kris Hauser; Anthony N. Kuo; Joseph A. Izatt (ICRA, 2019)

Remove Diverse Artifacts Simultaneously From a Single-Channel EEG Based on SSA and ICA: A Semi-Simulated Study. - Juan Cheng; Luchang Li; Chang Li 001; Yu Liu 023; Aiping Liu; Ruobing Qian; Xun Chen 001 (IEEE Access, 2019)

Toward Autonomous Robotic Micro-Suturing using Optical Coherence Tomography Calibration and Path Planning. - Yuan Tian; Mark Draelos; Gao Tang; Ruobing Qian; Anthony N. Kuo; Joseph A. Izatt; Kris Hauser (ICRA, 2020)

Optical Coherence Tomography-Guided Robotic Ophthalmic Microsurgery via Reinforcement Learning from Demonstration. - Brenton Keller; Mark Draelos; Kevin Zhou; Ruobing Qian; Anthony N. Kuo; George Konidaris 001; Kris Hauser; Joseph A. Izatt (IEEE Trans. Robotics, 2020)

Mesoscopic Photogrammetry With an Unstabilized Phone Camera. - Kevin C. Zhou; Colin L. V. Cooke; Jaehee Park; Ruobing Qian; Roarke Horstmeyer; Joseph A. Izatt; Sina Farsiu (CVPR, 2021)

Imaging dynamics beneath turbid media via parallelized single-photon detection. - Shiqi Xu; Xi Yang; Wenhui Liu; Joakim Jönsson; Ruobing Qian; Pavan Chandra Konda; Kevin C. Zhou; Qionghai Dai; Haoqian Wang; Edouard Berrocal; Roarke Horstmeyer (CoRR, 2021)

A Binocular Model to Evaluate User Experience in Ophthalmic and AR Prescription Lens Designs. - Collins Opoku-Baah; Ian M. Erkelens; Ruobing Qian; Robin Sharma (ISMAR Adjunct, 2022)

A general sample-weighted framework for epileptic seizure prediction. - Yikai Gao; Aiping Liu; Xinrui Cui; Ruobing Qian; Xun Chen 001 (Comput. Biol. Medicine, 2022)

Transient motion classification through turbid volumes via parallelized single-photon detection and deep contrastive embedding. - Shiqi Xu; Wenhui Liu; Xi Yang; Joakim Jönsson; Ruobing Qian; Paul McKee; Kanghyun Kim; Pavan Chandra Konda; Kevin C. Zhou; Lucas Kreiß; Haoqian Wang; Edouard Berrocal; et al. (CoRR, 2022)

Toward Open-World Electroencephalogram Decoding Via Deep Learning: A comprehensive survey. - Xun Chen 001; Chang Li 001; Aiping Liu; Martin J. McKeown; Ruobing Qian; Z. Jane Wang 001 (IEEE Signal Process. Mag., 2022)

A Novel SSA-CCA Framework forMuscle Artifact Removal from Ambulatory EEG. - Yuheng Feng; Qingze Liu; Aiping Liu; Ruobing Qian; Xun Chen 001 (Virtual Real. Intell. Hardw., 2022)

EEG-based seizure prediction via hybrid vision transformer and data uncertainty learning. - Zhiwei Deng; Chang Li 001; Rencheng Song; Xiang Liu; Ruobing Qian; Xun Chen 001 (Eng. Appl. Artif. Intell., 2023)

Semi-Supervised Domain-Adaptive Seizure Prediction via Feature Alignment and Consistency Regularization. - Deng Liang; Aiping Liu; Yikai Gao; Chang Li 001; Ruobing Qian; Xun Chen 001 (IEEE Trans. Instrum. Meas., 2023)

MSAIF-Net: A Multistage Spatial Attention-Based Invertible Fusion Network for MR Images. - Xiaowen Zhang; Aiping Liu; Pan Jiang; Ruobing Qian; Wei Wei; Xun Chen 001 (IEEE Trans. Instrum. Meas., 2023)

Patient-Specific Seizure Prediction From Electroencephalogram Signal via Multichannel Feedback Capsule Network. - Chang Li 001; Yuchang Zhao; Rencheng Song; Xiang Liu; Ruobing Qian; Xun Chen 001 (IEEE Trans. Cogn. Dev. Syst., 2023)

An interpretable and generalizable deep learning model for iEEG-based seizure prediction using prototype learning and contrastive learning. - Yikai Gao; Aiping Liu; Heng Cui 001; Ruobing Qian; Xun Chen 001 (Comput. Biol. Medicine, 2024)

A Dual-Branch Interactive Fusion Network to Remove Artifacts From Single-Channel EEG. - Heng Cui 001; Chang Li 001; Aiping Liu; Ruobing Qian; Xun Chen 001 (IEEE Trans. Instrum. Meas., 2024)

Centroid-Guided Domain Incremental Learning for EEG-Based Seizure Prediction. - Zhiwei Deng; Chang Li 001; Rencheng Song; Xiang Liu; Ruobing Qian; Xun Chen 001 (IEEE Trans. Instrum. Meas., 2024)

Distilling Invariant Representations With Domain Adversarial Learning for Cross-Subject Children Seizure Prediction. - Ziye Zhang; Aiping Liu; Yikai Gao; Xinrui Cui; Ruobing Qian; Xun Chen 001 (IEEE Trans. Cogn. Dev. Syst., 2024)

Rethinking Deep Supervision for Brain Tumor Segmentation. - Jiale Li; Aiping Liu; Yu Li; Wei Wei; Ruobing Qian; Qingguo Xie; Bensheng Qiu; Xun Chen 001 (IEEE Trans. Artif. Intell., 2024)

Machine Unlearning for Seizure Prediction. - Chenghao Shao; Chang Li 001; Rencheng Song; Xiang Liu; Ruobing Qian; Xun Chen 001 (IEEE Trans. Cogn. Dev. Syst., 2024)

Active source-free domain adaptation for intracranial EEG classification via neighborhood uncertainty and diversity. - Kun Wang; Ming Yang; Aiping Liu; Chang Li 001; Ruobing Qian; Xun Chen 001 (Biomed. Signal Process. Control., 2025)

Uncertainty-guided Fourier-based domain generalization for seizure prediction. - Zhiwei Deng; Chang Li 001; Rencheng Song; Xiang Liu; Ruobing Qian; Xun Chen 001 (Expert Syst. Appl., 2025)

CH-Net: A Cross Hybrid Network for Medical Image Segmentation. - Jiale Li; Aiping Liu; Wei Wei; Ruobing Qian; Xun Chen 001 (IEEE Trans. Artif. Intell., 2025)

EEGDfus: A Conditional Diffusion Model for Fine-Grained EEG Denoising. - Xiaoyang Huang; Chang Li 001; Aiping Liu; Ruobing Qian; Xun Chen 001 (IEEE J. Biomed. Health Informatics, 2025)

Data Augmentation for Seizure Prediction With Generative Diffusion Model. - Kai Shu; Le Wu; Yuchang Zhao; Aiping Liu; Ruobing Qian; Xun Chen 001 (IEEE Trans. Cogn. Dev. Syst., 2025)

A GAN Guided Parallel CNN and Transformer Network for EEG Denoising. - Jin Yin; Aiping Liu; Chang Li 001; Ruobing Qian; Xun Chen 001 (IEEE J. Biomed. Health Informatics, 2025)