About Me

I am currently a Postdoctoral Fellow in the Department of Statistics and Data Science, The Chinese University of Hong Kong (CUHK), supervised by Prof. Zhixiang Lin . My postdoctoral research focuses on integrating multi-omics with computational pathology to study cancer diagnosis, tumor heterogeneity, and interpretable multimodal modeling.

I received my M.Sc. degree in Statistics from the School of Mathematics and Statistics, Lanzhou University. I then obtained my Ph.D. in Computer Science and Technology from the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, under the supervision of Prof. Yongbing Zhang .

During my Ph.D., I was awarded the China Scholarship Council (CSC) scholarship and conducted research at the Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Germany, working with Dr. Jianxu Chen . My doctoral research focused on computational pathology, including nuclei instance segmentation, multimodal large language model, and visual reasoning for cancer diagnosis.

I also maintain a collection of online Reading Notes and Figure Library , where I curate reading notes, key figures, and thematic summaries spanning computer vision, machine learning, multi-omics, and biomedical foundations for long-term study.

News

  • 🔥
    Spring 2026
    Will join The Chinese University of Hong Kong as a Postdoctoral Fellow in the Department of Statistics and Data Science.
  • 🎉
    May 2025
    Paper “The Four Color Theorem for Cell Instance Segmentation” accepted at International Conference on Machine Learning (ICML 2025).
  • 🇩🇪
    Sep. 2024
    Began joint Ph.D. training at Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V..

Research Experience

Postdoctoral Fellow, Computational Biology
The Chinese University of Hong Kong
Integrating statistical modeling, computational pathology, and multi-omics for cancer research.
2026 – Present
Joint Ph.D. Trainee, Computational Pathology
Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund
Working on multimodal large language models and visual reasoning.
2024 – 2025
Visiting Ph.D. Student, Computer Vision
Tsinghua Shenzhen International Graduate School
Research training in computer vision and computational pathology during the doctoral period.
2021 – 2022

Educations

Ph.D. in Computer Science and Technology
Harbin Institute of Technology, Shenzhen
Dissertation focused on computational pathology, nuclei instance segmentation, and cancer-related image analysis.
2021 – 2025
M.Sc. in Applied Statistics
Lanzhou University
Training in machine learning and deep learning, with a particular focus on graph neural networks and time-series prediction.
2018 – 2021
B.M. in Agricultural and Forestry Economics
Beijing Forestry University
Early training in economics and statistics, with exposure to data, systems thinking, and applied quantitative analysis.
2013 – 2017

Selected Publications

A selected list of my recent publications in computational pathology, medical image analysis, and machine learning. For a complete publication record, please visit my Google Scholar .

📘 Journal Articles
  1. Ye Zhang, Cai L, Wang Z, et al.
    SEINE: Structure Encoding and Interaction Network for Nuclei Instance Segmentation
    IEEE Journal of Biomedical and Health Informatics JBHI 2025
    Paper Code
  2. Ye Zhang, Wang Y, Fang Z, et al.
    DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation
    IEEE Transactions on Circuits and Systems for Video Technology TCSVT 2024
    Paper Code
  3. Cai L, Huang S, Ye Zhang, et al.
    AttriMIL: Revisiting Attention-Based Multiple Instance Learning for Whole-Slide Pathological Image Classification from the Perspective of Instance Attributes
    Medical Image Analysis MIA 2025
    Paper Code
📗 Conference Proceedings
  1. Ye Zhang, Zhou Y, Wang Y, et al.
    The Four Color Theorem for Cell Instance Segmentation
    International Conference on Machine Learning ICML 2025
    Paper Code
  2. Ye Zhang, Fang Z, Wang Y, et al.
    Category Prompt Mamba Network for Nuclei Segmentation and Classification
    AAAI Conference on Artificial Intelligence AAAI 2025
    Paper Code
  3. Guan X, Zhang Z, Ye Zhang, et al.
    OT-StainNet: Optimal Transport-Driven Semantic Matching for Weakly Paired H&E-to-IHC Stain Transfer
    AAAI Conference on Artificial Intelligence AAAI 2025
    Paper Code
  4. Zhang L, Sun B, Ye Zhang, et al.
    Counting by Points: Density-Guided Weakly Supervised Nuclei Segmentation
    ACM Multimedia ACM MM 2025 Oral
    Paper Code
  5. Ye Zhang, Guan X, Li H, et al.
    Multi-Scale Context Intertwining for Panoramic Renal Pathology Segmentation
    IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP 2025
    Paper Code
  6. Guan X, Zhang Z, Ye Zhang, et al.
    Correlated Multiple IHC Virtual Staining for Breast Histopathological Images
    IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP 2025
    Paper Code
  7. Zhang L, Ye Zhang, Cai L, et al.
    Relation-Aware Graph Attention Network for Nuclei Classification
    IEEE International Conference on Multimedia and Expo ICME 2025 Oral
    Paper Code
  8. Ye Zhang, Wang Z, Wang Y, et al.
    Boundary-Aware Contrastive Learning for Semi-Supervised Nuclei Instance Segmentation
    Medical Imaging with Deep Learning MIDL 2024 Oral
    Paper Code
  9. Wang Z, Ye Zhang, Cai L, et al.
    Dynamic Pseudo Label Optimization in Point-Supervised Nuclei Segmentation
    International Conference on Medical Image Computing and Computer-Assisted Intervention MICCAI 2024
    Paper Code
  10. Fang Z, Wang Y, Ye Zhang, et al.
    MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models
    IEEE International Conference on Bioinformatics and Biomedicine BIBM 2024
    Paper Code

Awards

🏆
Excellent Graduate Award
Gansu Province, for academic excellence
2021
🎓
Huawei Scholarship
Awarded for outstanding performance and research potential
2020
🎖️
AnShuo Scholarship
Recognized for excellent academic achievements
2019
📐
Third Prize – Huawei Cup Graduate Mathematical Modeling Competition
National-level competition in modeling and optimization
2018

Projects

📁
Computational Pathology Imaging and Key Technologies
Principal Investigator
2024–2028
📁
AI Diagnosis System for Liver Diseases
Research Team Member
2021–2023
📁
Image Acquisition and Processing
Research Team Member
2020–2022
📁
Study on Changes in Northern Chinese Lakes
Research Team Member
2019–2024

Skills

🧠
Deep Learning
PyTorch, MMDetection, MONAI
💻
Programming
Python, TensorFlow
🧬
Medical Imaging Tools
QuPath, ImageJ

Contact

📬 I’m always happy to connect. Feel free to email me or reach out at conferences and academic events.