Projects per year
Personal profile
Personal profile
Jingxin Liu (刘净心) is an Associate 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.
Research interests
digital pathology image analysis, biomedical image analysis, image processing, machine learning, artificial intelligence
Experience
Associate Professor, Xian Jiaotong Liverpool University, 2024-Present
Assistant Professor, Xian Jiaotong Liverpool University, 2021-2023
AI Technical Director, HISTO Pathology Diagnostic Center, 2020-2021
Post Doctor Researcher, Shenzhen University, 2018-2020
Teaching
DTS101TC, Introduction to Neural Networks
Awards and honours
2023, Gusu Innovation and Entrepreneurship Leading Talents Programme - Youth Innovation Leading Talent ( 苏州市‘姑苏领军-青年创新领军人才’ )
2022, Innovation and Entrepreneurship Talent of Jiangsu Province (江苏省‘双创博士’)
2020, May -First labour Medal Baoshan, Shanghai ( 上海市宝山区‘五一劳动奖章’ )
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Ph.D, University of Nottingham, 2018
M.Sc, University of Edinburgh, 2013
Person Types
- Staff
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Collaborations and top research areas from the last five years
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Research on Domain Generalization of Pathological Image Based on Self-supervised Learning
1/01/23 → 31/12/25
Project: Governmental Research Project
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Research on Domain Generalization of Pathological Image Based on Self-supervised Learning
1/09/22 → 31/08/25
Project: Internal Research Project
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A Dataset and Model for Realistic License Plate Deblurring
Gong, H., Feng, Y., Zhang, Z., Hou, X., Liu, J., Huang, S. & Liu, H., Aug 2024, Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24). Larson, K. (ed.). International Joint Conferences on Artificial Intelligence, p. 776-784 9 p. (IJCAI International Joint Conference on Artificial Intelligence).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Advancing H&E-to-IHC Virtual Staining with Task-Specific Domain Knowledge for HER2 Scoring
Peng, Q., Lin, W., Hu, Y., Bao, A., Lian, C., Wei, W., Yue, M., Liu, J., Yu, L. & Wang, L., 2024, Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 - 27th International Conference, Proceedings. Linguraru, M. G., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K. & Schnabel, J. A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 3-13 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15004 LNCS).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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BiF³-Net: A Full BiFormer Full-scale Fusion Network for Accurate Gastrointestinal Images Segmentation
Wang, Y., Chen, S., Tian, Y., Wang, T. & Liu, J., 2024, (E-pub ahead of print).Research output: Contribution to conference › Paper › peer-review
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Boosting FFPE-to-HE Virtual Staining with Cell Semantics from Pretrained Segmentation Model
Hu, Y., Peng, Q., Du, Z., Wu, H., Liu, J., Chen, H. & Wang, L., 3 Oct 2024, Springer, Cham.Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation
Tang, F., Xu, Z., Huang, Q., Wang, J., Hou, X., Su, J. & Liu, J., 2024, Pattern Recognition and Computer Vision - 6th Chinese Conference, PRCV 2023, Proceedings. Liu, Q., Wang, H., Ji, R., Ma, Z., Zheng, W., Zha, H., Chen, X. & Wang, L. (eds.). Springer Science and Business Media Deutschland GmbH, p. 343-356 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14429 LNCS).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
Open Access22 Citations (Scopus)
Activities
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Cross-Organ and Cross-Scanner Adenocarcinoma Segmentation (COSAS 2024) challenge
Jingxin Liu (Chair)
8 May 2024 → 5 Oct 2024Activity: Participating in or organising an event › Organising an event e.g. a conference, workshop, …
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Quantitative Assessment of Digital Histopathology Images: Experiences of Industry and Academia
Jingxin Liu (Speaker)
20 Sept 2023Activity: Talk or presentation › Keynote Speech
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IEEE Transactions on Medical Imaging (Journal)
Jingxin Liu (Reviewer)
2020 → 2022Activity: Peer-review and editorial work of publications › Publication Peer-review
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IEEE International Symposium on Biomedical Imaging (Publisher)
Jingxin Liu (Reviewer)
2018 → …Activity: Peer-review and editorial work of publications › Publication Peer-review