Recent News
- 1 first-author paper submitted to Nature Methods!
- 1 paper submitted to Nature Methods.
- 1 paper submitted to Nature Medicine.
- 1 paper submitted to Medical Image Analysis!
About
I am a Ph.D. student in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology (HKUST), working under the supervision of Dr. Hao Chen in the HKUST SMART (Scalable Medical Analysis, Reasoning and Treatment) Lab. My research focuses on pathology image analysis and the application of artificial intelligence in healthcare, with particular emphasis on developing foundation models for medical image understanding.
Prior to joining HKUST, I completed my undergraduate studies at the University of Electronic Science and Technology of China (UESTC), where I worked with Prof. Liang-Jian Deng at the Innovation Center, focusing on remote sensing image processing and pansharpening techniques.
Research Interests
- Healthcare AI & Pathology
- Computer Vision & Foundation Models
- Medical Image Analysis
- Machine Learning Applications
Selected Publications
Preprints
Notation: # indicates co-first authorship, ^ indicates co-second authorship, * denotes corresponding author.
Genome-Anchored Foundation Model Embeddings Improve Molecular Prediction from Histology Images
Cheng Jin#, Fengtao Zhou#, Yunfang Yu#, Jiabo Ma, Yihui Wang, Yingxue Xu, Huajun Zhou, Hao Jiang, Luyang Luo, Luhui Mao, Zifan He, Xiuming Zhang, Jing Zhang, Ronald Chan, Herui Yao*, Hao Chen*
arXiv preprint, 2025
PathBench: A comprehensive comparison benchmark for pathology foundation models towards precision oncology
Jiabo Ma#, Yingxue Xu#, Fengtao Zhou#, Yihui Wang^, Cheng Jin^, Zhengrui Guo^, Jianfeng Wu, On Ki Tang, Huajun Zhou, Xi Wang, Luyang Luo, Zhengyu Zhang, Du Cai, Zizhao Gao, Wei Wang, Yueping Liu, Jiankun He, Jing Cui, Zhenhui Li, Jing Zhang, Feng Gao*, Xiuming Zhang*, Li Liang*, Ronald Cheong Kin Chan*, Zhe Wang*, Hao Chen*
arXiv preprint, 2025
A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model
Yingxue Xu#, Yihui Wang#, Fengtao Zhou#, Jiabo Ma, Cheng Jin, Shu Yang, Jinbang Li, Zhengyu Zhang, Chenglong Zhao, Huajun Zhou, Zhenhui Li, Huangjing Lin, Xin Wang, Jiguang Wang, Anjia Han, Ronald Cheong Kin Chan, Li Liang, Xiuming Zhang, Hao Chen*
arXiv preprint, 2024
Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation
Hao Jiang#, Cheng Jin#, Huangjing Lin#, Yanning Zhou, Xi Wang, Jiabo Ma, Li Ding, Jun Hou, Runsheng Liu, Zhizhong Chai, Luyang Luo, Huijuan Shi, Yinling Qian, Qiong Wang, Changzhong Li, Anjia Han*, Ronald Cheong Kin Chan*, Hao Chen*
arXiv preprint, 2025
Conference Papers
GameGen-X: Interactive Open-world Game Video Generation
Haoxuan Che#, Xuanhua He#, Quande Liu*, Cheng Jin, Hao Chen*
ICLR 2025 (Poster Acceptance)
SpanConv: A New Convolution via Spanning Kernel Space for Lightweight Pansharpening
Zhi-Xuan Chen, Cheng Jin, Tian-Jing Zhang, Xiao Wu, Liang-Jian Deng*
IJCAI-ECAI 2022 (Long Oral Acceptance, Top 3.75%)
Journal Papers
Towards A Generalizable Pathology Foundation Model via Unified Knowledge Distillation
Jiabo Ma#, Zhengrui Guo#, Fengtao Zhou, Yihui Wang, Yingxue Xu, Jinbang Li, Fang Yan, Yu Cai, Zhengjie Zhu, Cheng Jin, Yi Lin, Xinrui Jiang, Anjia Han, Zhenhui Li, Ronald Cheong Kin Chan, Jiguang Wang, Peng Fei, Kwang-Ting Cheng, Shaoting Zhang*, Li Liang*, Hao Chen*
Nature Biomedical Engineering (Impact Factor: 26.3), 2025
Shapley Values-enabled Progressive Pseudo Bag Augmentation for Whole Slide Image Classification
Renao Yan, Qiehe Sun, Cheng Jin, Yiqing Liu, Yonghong He, Tian Guan, Hao Chen*
IEEE Transactions on Medical Imaging (Impact Factor: 9.8), 2024
Laplacian pyramid networks: A new approach for multispectral pansharpening
Cheng Jin, Liang-Jian Deng*, Ting-Zhu Huang, Gemine Vivone
Information Fusion (Impact Factor: 15.5), 2021
Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening
Liang-Jian Deng, Gemine Vivone*, Cheng Jin and Jocelyn Chanussot
IEEE Transactions on Geoscience and Remote Sensing, 2020
ESI Highly Cited Paper, ESI Hot Paper
Talks
Dialyzer Modeling for Computer Fluid Dynamics Analysis
PM3 Workshop, 2021
This talk reports on the progress of my Mitacs GRI Internship focused on dialyzer modeling for computer fluid dynamics analysis. The project aims to construct an effective mathematical module for substance transfer between the dialyzer and blood.
Professional Services
Membership
- IEEE Graduate Student Member
Journal Reviewer
- Information Fusion
- IEEE Transactions on Neural Networks and Learning Systems
- International Journal of Computer Vision
- IEEE Transactions on Geoscience and Remote Sensing
- IEEE Journal of Biomedical and Health Informatics
- IEEE Geoscience and Remote Sensing Letters
Conference Reviewer
- Medical Imaging with Deep Learning 2024 (MIDL 2024)
- Medical Imaging with Deep Learning 2025 (MIDL 2025)
- 2024 International Workshop on Multiscale Multimodal Medical Imaging (MMMI 2024) and Workshop on Machine Learning for Multimodal/-sensor Healthcare Data (ML4MHD 2024)
- The Thirteenth International Conference on Learning Representations (ICLR 2025)
- The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2025 (CVPR2025)
Teaching
Teaching Assistant
- COMP 2711 - Discrete Mathematical Tools for Computer Science (Spring 2023, Fall 2024)
- COMP 3211 - Fundamentals of Artificial Intelligence (Fall 2023)
Supervised Students
Miscellaneous
PGP Signature
BA8D F912 5DE6 EFE8 9540 0AB0 9D5A D561 9E27 B262