Xiaoqing Guo PhD

Dr Xiaoqing Guo is currently a postdoctoral research fellow with the Department of Engineering Science, University of Oxford, United Kingdom. She received the B.Eng. degree from the School of Biological Science and Medical Engineering, Beihang University, Beijing, in 2018, and the Ph.D. degree from the Department of Electrical Engineering, City University of Hong Kong, Hong Kong, in 2022.

Her research interest is in the interdisciplinary field of medical image analysis, computer vision, and machine learning, aiming to create innovative intelligent systems that can support high-quality medical diagnosis, intervention, and interaction.

Recently, Dr Guo has been dedicated to multi-modal learning with video, text, audio, and gaze modalities, human-machine interaction/collaboration, out-of-distribution generalization, and learning with noisy labels.

Previously, she focused on developing annotation-efficient deep learning solutions, such as data augmentation, semi-supervised learning, domain adaptation, out-of-distribution generalization, and learning with noisy labels, to achieve trustworthy and effective intelligent systems.

Turing AI WLR Fellowship

Key Papers

Xiaoqing Guo, Qianhui Men, Alison Noble. “MMSummary: Multimodal Summary Generation for Fetal Ultrasound Video”. The 27nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024), Marrakesh, Morocco.

Qianhui Men, Xiaoqing Guo, Aris Papageorghiou, Alison Noble. “Pose-GuideNet: Automatic Scanning Guidance for Fetal Head Ultrasound from Pose Estimation”. The 27nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024), Marrakesh, Morocco.

Ziyun Liang, Xiaoqing Guo, Alison Noble, Konstantinos Kamnitsas. “IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI”. The 27nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024), Marrakesh, Morocco.

Xiaoqing Guo, Jie Liu, Yixuan Yuan. “Adaptive Infinite Prototypes for Single Domain Generalization in Semantic Segmentation.” International Journal of Computer Vision. 2024. (IJCV, IF: 19.565)

Xiaoqing Guo, Jie Liu, Tongliang Liu, Yixuan Yuan. “Handling Open-set Noise and Novel Target Recognition in Domain Adaptive Semantic Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023. (TPAMI, IF: 24.314)

Yuanyuan Chen*, Xiaoqing Guo*, Yongsheng Pan, Yong Xia, Yixuan Yuan. “Dynamic Feature Splicing for Few-Shot Rare Disease Diagnosis.” Medical Image Analysis, vol. 90, p. 102959, 2023. (* indicates equal contribution) (MedIA, IF: 13.828)

Xiaoqing Guo, Zhen Chen, Jun Liu, Yixuan Yuan. “Non-Equivalent Images and Pixels: Confidence- Aware Resampling with Meta-Learning Mixup for Polyp Segmentation.” Medical Image Analysis, vol. 78, p. 102394, 2022. (MedIA, IF: 13.828)

Xiaoqing Guo, Jie Liu, Yixuan Yuan. “Semantic-oriented Labeled-to-unlabeled Distribution Translation for Image Segmentation.” IEEE Transactions on Medical Imaging, vol. 41, no. 2, pp. 434-445, 2022. (TMI, IF: 11.037)

Xiaoqing Guo, Jie Liu, Tongliang Liu, Yixuan Yuan. “SimT: Handling Open-set Noise for Domain Adaptive Semantic Segmentation.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, USA.

Xiaoqing Guo, Yixuan Yuan. “Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels.” The 25nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022), Singapore.

Xiaoqing Guo, Chen Yang, Yixuan Yuan. “Dynamic-Weighting Hierarchical Segmentation Network for Medical Images.” Medical Image Analysis, vol. 73, p. 102196, 2021. (MedIA, IF: 13.828)

Xiaoqing Guo, Chen Yang, Yajie Liu, Yixuan Yuan. “Learn to Threshold: ThresholdNet with Confidence-Guided Manifold Mixup for Polyp Segmentation.” IEEE Transactions on Medical Imaging, vol. 40, no. 4, pp. 1134-1146, 2021. (TMI, IF: 11.037)

Xiaoqing Guo*, Chen Yang*, Baopu Li, Yixuan Yuan. “MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021)

Xiaoqing Guo, Yixuan Yuan. “Semi-supervised WCE Image Classification with Adaptive Ag- gregated Attention.” Medical Image Analysis, vol. 64, p. 101733, 2020. (MedIA, IF: 13.828)

Xiaoqing Guo, Zhen Chen, Yixuan Yuan. “Complementary Network with Adaptive Receptive Fields for Melanoma Segmentation.” The 17th IEEE International Symposium on Biomedical Imaging (ISBI 2020), Iowa City, Iowa, USA.

Xiaoqing Guo, Chen Yang, Pak Lun Lam, Peter Y.M. Woo, Yixuan Yuan. “Domain Knowledge Based Brain Tumor Segmentation and Overall Survival Prediction.” Brain Lesion (BrainLes) workshop of MICCAI 2019, Shenzhen, China.

Xiaoqing Guo, Yixuan Yuan. “Triple ANet: Adaptive Abnormal-aware Attention Network for WCE Image Classification.” The 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Shenzhen, China.

• The Rising Star of Women in Engineering – Asian Deans’ Forum, 2024
• Global Top 80 Chinese Young Female Scholars in Artificial Intelligence, 2023
• CVPR Outstanding Reviewer Award (232 out of more than 7000 reviewers), 2023
• Chow Yei Ching School of Graduate Studies Outstanding Doctoral Research Award (only 5 awardees in the history of CityU before 2022), City University of Hong Kong, 2022
• Outstanding Research Thesis Award (8 awardees at CityU in 2022), City University of Hong Kong, 2022
• Microsoft Research Asia Fellowship Nomination Award (28 students in Asia-Pacific Area), Microsoft, 2021