Ye Zhu

Department of Computer Science
Hong Kong Baptist University


Biography [ CV ]

I am currently a first-year PhD student in the Department of Computer Science, Hong Kong Baptist University, commencing my doctoral studies under the supervision of Prof. PC Yuen in 2023. Prior to this, I gained valuable research experience through two RA positions. The first, under the guidance of Prof. Ruimao Zhang in The Chinese University of Hong Kong, Shenzhen [10/2021-06/2023], and the second, working alongside Prof. Chang-Dong Wang in Sun Yat-sen University [03/2021-09/2021]. In 2021, I received the B. Eng degree from College of Mathematics and Information, South China Agriculture University.

My research interest lies in deep learning and computer vision, including scene understanding, semi-supervised learning and multimodal learning in medical.


Selected Publications

Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation
Ye Zhu, Jie Yang, Siqi Liu, Ruimao Zhang*.
Proc. of Conference on Medical Imaging with Deep Learning (MIDL), 2023.

[paper, code](Oral)

Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency
Jie Yang, Ye Zhu, Chaoqun Wang, Zhen Li, Ruimao Zhang*.
Proc. of Conference on Medical Imaging with Deep Learning (MIDL), 2023.


AMOS_A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation
Yuanfeng Ji, Haotian Bai, Jie Yang, Chongjian Ge, Ye Zhu, Xiang Wan*, Ping Luo* and Ruimao Zhang*.
Proc. of Conference on Neural Information Processing Systems (NeurIPS), 2022.

[paper, code](Oral)

Toward Clinically Assisted Colorectal Polyp Recognition via Structured Cross-modal Representation Consistency
Weijie Ma, Ye Zhu, Jie Yang, Yiwen Hu, Zhen Li, Li Xiang and Ruimao Zhang*.
Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022.

[paper, code](early accept)

Hybrid-Order Anomaly Detection on Attributed Networks
Ling Huang, Ye Zhu, Yuefang Gao, Tuo Liu, Chao Chang, Caixing Liu, Yong Tang and Chang-Dong Wang*.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

[paper](early accept)

© Ye Zhu | Last updated: May 2022