Ye Zhu

Department of Computer Science
Hong Kong Baptist University

Email: csyzhu@comp.hkbu.edu.hk

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.

News

[03/2023] Two papers are accepted by MIDL2023 and one is rated as the oral presentation.
[04/2022] One paper is accepted by NeurIPS2022.
[02/2022] One paper is accepted by MICCAI2022.
[07/2021] One paper is accepted by TKDE2021.

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. [paper]
	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)