Faculty
Biography
Xiaoying Tang, Ph.D. from Johns Hopkins University, is a tenured Associate Professor and Researcher in the Department of Electrical and Electronic Engineering at Southern University of Science and Technology, and a doctoral advisor. She is a recipient of the National Natural Science Foundation of China (NSFC) Excellent Young Scientists Fund, the Guangdong Distinguished Young Scholar Fund, and the Shenzhen Outstanding Youth Fund. She has been recognized as a Shenzhen High-Level Overseas Talent and a Distinguished Professor under the Shenzhen "Pengcheng Peacock Plan". Dr. Tang has held visiting professor positions at Johns Hopkins University and Carnegie Mellon University. She has served as Principal Investigator for over ten national and provincial research projects, including the Youth Project of the National Key R&D Program during the 14th Five-Year Plan and sub-projects under the 13th Five-Year Plan National Key R&D Program. She is an Associate Editor for Neural Networks, IEEE Transactions on Cognitive and Developmental Systems, and IEEE Transactions on Circuits and Systems for Video Technology.She has held multiple leadership roles in international conferences, including Area Chair, Session Chair, and Local Chair for MICCAI; Session Chair and Area Chair for IEEE ISBI; and Area Chair for ICPR. Dr. Tang is a Senior Member of IEEE and the Chinese Society of Biomedical Engineering, and serves as Vice Chair of the IEEE EMBS Shenzhen Chapter.
Education Background
09/2009-05/2014 Johns Hopkins University (USA), Electrical and Computer Engineering, Ph.D.
01/2013-05/2014 Johns Hopkins University (USA), Applied Mathematics and Statistics, M.Eng.
09/2009-05/2011 Johns Hopkins University (USA), Electrical and Computer Engineering, M.Eng.
09/2006-06/2009 Huazhong University of Science and Technology, School of Foreign Language, B.Sc.
09/2005-06/2009 Huazhong University of Science and Technology, Department of Control Science and Engineering, B.Eng.
Working Experiences
01/2024–NOW Tenured Associate Professor, Researcher, Electrical and Electronic Engineering, Southern University of Science and Technology
05/2018–12/2023 Tenure-track Assistant Professor, Associate Researcher, Electrical and Electronic Engineering, Southern University of Science and Technology
02/2016–02/2019 Adjunct Assistant Professor, Electrical and Computer Engineering, Carnegie Mellon University (USA)
05/2015–05/2018 Adjunct Assistant Professor, Electrical and Computer Engineering, Johns Hopkins University (USA)
05/2015–05/2018 Associate Professor, School of Electronics and Information Technology, Sun Yat-sen University (formerly named School of Mobile and Information Engineering)
05/2015–05/2018 Tenure-track Assistant Professor, SYSU-CMU Joint Institute of Engineering, Sun Yat-sen University
05/2015–05/2018 Assistant Professor, SYSU-CMU Shunde International Joint Research Institute
05/2015–08/2016 Visiting Professor, Electrical and Computer Engineering, Carnegie Mellon University (USA)
05/2014–05/2015 Postdoctoral Research Fellow, Center for Imaging Science, Johns Hopkins University (USA)
Research Introduction
Dr. Tang’s research focuses on intelligent medical image computation and analysis, with primary applications to the multi-modality MRI image analysis of the human brain and the multi-modality ophthalmic images, as well as the AI-based early diagnosis and prediction of brain disorders and eye diseases.
Research Interests
Medical Image Computing and Analysis, Precision Intelligent Surgical Robotics, Eye-Brain Image Analysis, Data-efficient Learning
Major Recognitions
Shenzhen Science and Technology Progress Award in Artificial Intelligence (1/8), 2024
Youth Science and Technology Award of the Chinese Society for Stereology (1/1), 2024
Distinguished Professor of the "Pengcheng Peacock Plan" (Category B), Shenzhen, 2024
China Medical AI Representative Algorithm Award (1/2), 2023
First Prize, Guangdong Provincial Science and Technology Progress Award (4/11), 2022
Excellent Postgraduate Supervisor Award, SUSTech, 2022
Outstanding Faculty for Undergraduate Student Enrollment, SUSTech, 2022
Excellent Residential College Mentor of Zhixin College, SUSTech, 2019
High-level Talent in Nanshan District, Shenzhen, 2019
Overseas High-Caliber Personnel in Shenzhen, 2018
Papers
J. Lyu, P. Bartlett, F. Nasrallah, and X. Tang*, "Masked Deformation Modeling for Volumetric Brain MRI Self-supervised Pre-Training", IEEE Transactions on Medical Imaging, 44(3): 1596-1607, 2024.
L. Lin, Y. Liu, J. Wu, P. Cheng, Z. Cai, K.K.Y. Wong, and X. Tang*, "FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-Supervised Medical Image Segmentation", IEEE Transactions on Medical Imaging, 44(3): 1127-1139, 2024.
Z. Cai, L. Lin, H. He, P. Cheng, and X. Tang*, "Uni4Eye++: A General Masked Image Modeling Multi-Modal Pre-Training Framework for Ophthalmic Image Classification and Segmentation", IEEE Transactions on Medical Imaging, 43(12): 4419-4429, 2024.
L. Lin, L. Peng, H. He, P. Cheng, J. Wu, K.K.Y. Wong, and X. Tang*, “YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation”, Medical Image Analysis, 90: 102937, 2023.
Z. Wang, J. Lyu, and X. Tang*, “autoSMIM: Automatic Superpixel-based Masked Image Modeling for Skin Lesion Segmentation”, IEEE Transactions on Medical Imaging, 42(12): 3501-3511, 2023.
P. Cheng, L. Lin, J. Lyu, Y. Huang, W. Luo, and X. Tang*, “PRIOR: Prototype Representation Joint Learning from Medical Images and Reports”, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), Paris, August 2023.
J. Lyu, Y. Zhang, Y. Huang, L. Lin, P. Cheng, and X. Tang*, “AADG: Automatic Augmentation for Domain Generalization on Retinal Image Segmentation”, IEEE Transactions on Medical Imaging, 41(12): 3699-3711, 2022.
Y. Zhang, J. Wu, Y. Liu, Y. Chen, W. Chen, E.X. Wu, C. Li, and X. Tang*, "A Deep Learning Framework for Pancreas Segmentation with Multi-atlas Registration and 3D Level-set", Medical Image Analysis, 68: 101884, 2021.
J. Wu and X. Tang*, “Brain Segmentation Based on Multi-atlas and Diffeomorphism Guided 3D Fully Convolutional Network Ensembles”, Pattern Recognition, 115: 107904, 2021.
Y. Zhang, J. Wu, Y. Liu, Y. Chen, E.X. Wu, and X. Tang*, “MI-UNet: Multi-Inputs UNet Incorporating Brain Parcellation for Stroke Lesion Segmentation from T1-weighted Magnetic Resonance Images”, IEEE Journal of Biomedical and Health Informatics, 25(2): 526-535, 2021.
Recruitment Announcement
Dr. Tang’s group recruits research assistants professors, post-doc researchers, research assistants, Ph.D. students, master students, as well as undergraduate interns. Visiting scholars and students are also welcome. Please contact Dr. Tang directly via email if interested in any of the above positions.
Contact Information
Email: [email protected]