Brief Introduction:

Yuqian Chen is a Distinguished Professor and Ph.D. Supervisor at Tianjin University. She was selected for a national-level young talent program in 2025 and joined Tianjin University in 2026. Dr. Chen received her Ph.D. in Computer Science from the University of Sydney and completed her postdoctoral training at Harvard Medical School. Her research focuses on the intersection of neuroimaging and artificial intelligence, with a long-standing commitment to advancing cutting-edge methods in medical image analysis and brain science. Dr. Chen has published extensively in leading international journals and conferences in medical imaging and neuroscience, including Medical Image Analysis, MICCAI, and NeuroImage. Her work has received multiple prestigious international awards and honors. She has also organized numerous international conferences and workshops and serves as a reviewer for several top-tier journals and conferences in the fields of medical imaging, artificial intelligence, and neuroimaging.

Academic Achievements:

Chen, Y., Zekelman, L.R., Lo, Y., et al (2025). TractCloud-FOV: Deep Learning-based Robust Tractography

Parcellation in Diffusion MRI with Incomplete Field of View. Human Brain Mapping, 46(5), e70201.

Chen, Y., Zhang, F., Wang, M., Zekelman, L.R., et al (2025). TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Interpretable Sex and Age Prediction from Diffusion MRI Tractography. Medical Image Analysis (2025): 103476.

Chen, Y., Zekelman, L.R., Zhang, C., et al (2023). TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance. Medical Image Analysis, 94, 103120.

Chen, Y., Zhang, C., Xue, T., Song, Y., et al (2023). Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation. NeuroImage, 273, p.120086.

Chen, Y., Zhang, F., R. Zekelman, L.R., et al (2023). TractGraphCNN: Anatomically Informed Graph CNN for

Classification using Diffusion MRI Tractography. 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), pp. 1-5. IEEE, 2023.

Chen, Y., Zhang, F., Zhang, C., et al (2022). White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning. 25th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022), pp. 174-184.

Chen, Y., Zhang, C., Song, Y., et al (2021). Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation. 24th International Conference on Medical Image

Computing and Computer-Assisted Intervention (MICCAI 2021), pp. 497-507.

Chen, Y., Song, Y., Zhang, C., et al (2021).  CellTrack R-CNN: A novel end-to-end deep neural network for cell segmentation and tracking in microscopy images. 18th IEEE International Symposium on Biomedical Imaging (ISBI 2021), Nice: Institute of Electrical and Electronics Engineers (IEEE).

Xue, T., Chen, Y., Zhang, C., et al (2023). TractCloud: Registration-free tractography parcellation with a novel

local-global streamline point cloud representation. 26th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2023), pp. 409-419.

Vroemen, M. J., Chen, Y., Lo, Y., et al. (2026). DeepMultiConnectome: Deep Multi-Task Prediction of Structural Connectomes Directly from Diffusion MRI Tractography. NeuroImage, 121765.

Honors & Awards:

2025 OCSMRM Young Investigator Award

2024 Organization for Human Brain Mapping (OHBM) Merit Award

2019-2023 USYD International Scholarship