Xi'an Jiaotong-Liverpool University

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Jingxin Liu (刘净心) is an Assistant Professor in the School of AI and Advanced Computing at XJTLU Entrepreneur College (Taicang). He received his Ph.D in Computer Science at The University of Nottingham in 2018, M.Sc in Signal Processing and Communications from The University of Edinburgh in 2013.

Jingxin Liu’s research focus on medical image analysis, especially digital pathology and microscope image analysis, computational pathology, image processing and computer vision. He has published more than 20 peer-reviewed journal articles and conference papers, such as T-MI, MIA, J-BHI, ISBI, MICCAI.

In the past years, he has successfully attracted over 2 million research funds from both academia and industry, including NSFC Young Scientist Fund, NSF of the Jiangsu Higher Education Institutions of China General Programme.

He was awarded “Dual-Innovation Doctor”(双创博士) of Jiangsu in 2022, and Gusu Innovation and Entrepreneurship Leading Talents (姑苏领军人才) Programme in 2023.

Qualifications
- Ph.D, University of Nottingham, 2018
- M.Sc, University of Edinburgh, 2013
Experience
- Assistant Professor, Xi'an Jiaotong-Liverpool University - 2021 to present
- AI Technical Director, HISTO Pathology Diagnostic Center, 2020-2021
- Post Doctor Researcher, Shenzhen University, 2018-2020
Research interests
- digital pathology image analysis, biomedical image analysis, image processing, machine learning, artificial intelligence
Articles
- Liu, Jingxin, Qiang Zheng, Xiao Mu, Yanfei Zuo, Bo Xu, Yan Jin, Yue Wang et al. "Automated tumor proportion score analysis for PD-L1 (22C3) expression in lung squamous cell carcinoma." Scientific reports 11, no. 1 (2021): 1-9.
- Xie, Ruitao, Jingxin Liu, Rui Cao, Connor S. Qiu, Jiang Duan, Jon Garibaldi, and Guoping Qiu. "End-to-End Fovea Localisation in Colour Fundus Images with a Hierarchical Deep Regression Network." IEEE Transactions on Medical Imaging 40, no. 1 (2020): 116-128.
- Shu, Jie, Jingxin Liu, Yongmei Zhang, Hao Fu, Mohammad Ilyas, Giuseppe Faraci, Vincenzo Della Mea, Bozhi Liu, and Guoping Qiu. "Marker controlled superpixel nuclei segmentation and automatic counting on immunohistochemistry staining images." Bioinformatics 36, no. 10 (2020): 3225-3233.
- Wen, Zhijie, Ru Feng, Jingxin Liu, Ying Li, and Shihui Ying. "GCSBA-Net: Gabor-Based and Cascade Squeeze Bi-Attention Network for Gland Segmentation." IEEE Journal of Biomedical and Health Informatics 25, no. 4 (2020): 1185-1196.
- Chen, Zhe, Zhao Chen, Jingxin Liu, Qiang Zheng, Yuang Zhu, Yanfei Zuo, Zhaoyu Wang, Xiaosong Guan, Yue Wang, and Yuan Li. "Weakly Supervised Histopathology Image Segmentation With Sparse Point Annotations." IEEE Journal of Biomedical and Health Informatics 25, no. 5 (2020): 1673-1685.
- Xu, Bolei, Jingxin Liu, Xianxu Hou, Bozhi Liu, Jon Garibaldi, Ian O. Ellis, Andy Green, Linlin Shen, and Guoping Qiu. "Attention by selection: A deep selective attention approach to breast cancer classification." IEEE transactions on medical imaging 39, no. 6 (2019): 1930-1941.
- Hou, Xianxu, Jingxin Liu, Bolei Xu, Xiaolong Wang, Bozhi Liu, and Guoping Qiu. "Class-aware domain adaptation for improving adversarial robustness." Image and Vision Computing 99 (2020): 103926.
- Liu, Jingxin, Bolei Xu, Chi Zheng, Yuanhao Gong, Jon Garibaldi, Daniele Soria, Andew Green, Ian O. Ellis, Wenbin Zou, and Guoping Qiu. "An end-to-end deep learning histochemical scoring system for breast cancer TMA." IEEE transactions on medical imaging 38, no. 2 (2018): 617-628.
Proceedings
- Xu, Bolei, Jingxin Liu, Xianxu Hou, Bozhi Liu, and Guoping Qiu. "End-to-end illuminant estimation based on deep metric learning." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3616-3625. 2020.
- Hou, Xianxu*, Jingxin Liu*, Bolei Xu, Bozhi Liu, Xin Chen, Mohammad Ilyas, Ian Ellis, Jon Garibaldi, and Guoping Qiu. "Dual adaptive pyramid network for cross-stain histopathology image segmentation." In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 101-109. Springer, Cham, 2019.
- Liu, Jingxin, Libo Liu, Bolei Xu, Xianxu Hou, Bozhi Liu, Xin Chen, Linlin Shen, and Guoping Qiu. "Bladder cancer multi-class segmentation in mri with pyramid-in-pyramid network." In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 28-31. IEEE, 2019.
- Xu, Bolei, Jingxin Liu, Xianxu Hou, Bozhi Liu, Jon Garibaldi, Ian O. Ellis, Andy Green, Linlin Shen, and Guoping Qiu. "Look, investigate, and classify: a deep hybrid attention method for breast cancer classification." In 2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019), pp. 914-918. IEEE, 2019.
- Liu, Jingxin, Bolei Xu, Linlin Shen, Jon Garibaldi, and Guoping Qiu. "HEp-2 cell classification based on a deep autoencoding-classification convolutional neural network." In 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), pp. 1019-1023. IEEE, 2017.
- Liu, Jingxin, Guoping Qiu, and Linlin Shen. "Luminance adaptive biomarker detection in digital pathology images." Procedia Computer Science 90 (2016): 113-118.
Grants
- Jingxin Liu, 2023-2025, National Natural Science Foundation of China, Young Scientists Fund (国家自然科学基金青年项目), PI
- Jingxin Liu, 2023-2024, Natural Science Foundation of the Jiangsu Higher Education Institutions of China (江苏省高等学校自然科学研究面上项目), PI
Courses taught
- DTS101TC, Introduction to Neural Networks
Professional memberships
- Member, Medical Image Processing, Jiangsu Association of Artificial Intelligence

电话
+86 (0)51288970719
Email
Jingxin.Liu@xjtlu.edu.cn
地址
D-5024(TC Campus-Building D)
Suzhou Dushu Lake Science and Education Innovation District
Suzhou Industrial Park
Suzhou
P.R.China
215123

Jingxin LiuDr.

Profile

Qualifications

Experience

Research interests

Articles

Proceedings

Grants

Courses taught

Professional memberships