Portrait
Ying Chen
Incoming Ph.D. Student
Columbia University
About Me

I am an incoming Ph.D. student at Columbia University, where I will join the Laboratory of AI & Biomedical Science (LABS) under the supervision of Prof. Junhao Wen. I completed my master's studies at Xiamen University under the supervision of Prof. Rongshan Yu.

My research interests lie at AI for science, with a particular focus on foundation models, generative AI, and multimodal learning for biomedical applications. My long-term goal is to build intelligent computational models that advance our understanding of human health and disease.

Education
  • Columbia University
    Columbia University
    Ph.D. Student
    2026.09 -
  • Xiamen University
    Xiamen University
    M.S. Student
    2023.09 - 2026.06
  • South China Normal University
    South China Normal University
    B.S. Student
    2019.09 - 2023.06
Experience
  • Shanghai AI LAB
    Shanghai AI LAB
    Research Intern
    2024.05 - 2026.02
Honors & Awards
  • Outstanding Master's Thesis Award, Xiamen University
    2026
  • South China Normal University Merit Student Scholarship (four times)
    2019-2023
News
2026
Our paper has been accepted by Nature Cancer!
2026.07.12
Selected Publications (view all )
BioMTAN: A Biological Knowledge-Guided Multi-Task Attention Network for Co-Enhanced Cancer Diagnosis and Prognosis
BioMTAN: A Biological Knowledge-Guided Multi-Task Attention Network for Co-Enhanced Cancer Diagnosis and Prognosis

Ying Chen*, Jiajing Xie*, Yuxiang Lin, Yuhang Song, Wenxian Yang, Rongshan Yu# (* equal contribution, # corresponding author)

IEEE Journal of Biomedical and Health Informatics (JBHI) 2026

BioMTAN integrates biological pathway knowledge with multi-task attention to jointly predict cancer molecular subtypes and survival risk from gene expression data.

BioMTAN: A Biological Knowledge-Guided Multi-Task Attention Network for Co-Enhanced Cancer Diagnosis and Prognosis

Ying Chen*, Jiajing Xie*, Yuxiang Lin, Yuhang Song, Wenxian Yang, Rongshan Yu# (* equal contribution, # corresponding author)

IEEE Journal of Biomedical and Health Informatics (JBHI) 2026

BioMTAN integrates biological pathway knowledge with multi-task attention to jointly predict cancer molecular subtypes and survival risk from gene expression data.

SurvMamba: State Space Model with Multi-Grained Multi-Modal Interaction for Survival Prediction
SurvMamba: State Space Model with Multi-Grained Multi-Modal Interaction for Survival Prediction

Ying Chen, Jiajing Xie, Yuxiang Lin, Yuhang Song, Chen Zhang, Wenxian Yang, Rongshan Yu# (# corresponding author)

IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2025

SurvMamba introduces Mamba-based hierarchical intra-modal and inter-modal interaction modules to integrate whole-slide images and transcriptomic data for efficient cancer survival prediction.

SurvMamba: State Space Model with Multi-Grained Multi-Modal Interaction for Survival Prediction

Ying Chen, Jiajing Xie, Yuxiang Lin, Yuhang Song, Chen Zhang, Wenxian Yang, Rongshan Yu# (# corresponding author)

IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2025

SurvMamba introduces Mamba-based hierarchical intra-modal and inter-modal interaction modules to integrate whole-slide images and transcriptomic data for efficient cancer survival prediction.

SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding
SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding

Ying Chen*, Guoan Wang*, Yuanfeng Ji*#, Yanjun Li, Jin Ye, Tianbin Li, Ming Hu, Rongshan Yu, Yu Qiao, Junjun He# (* equal contribution, # corresponding author)

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025

SlideChat is an open-source vision-language assistant for gigapixel whole-slide pathology images, built with SlideInstruction and evaluated on SlideBench across captioning and VQA tasks.

SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding

Ying Chen*, Guoan Wang*, Yuanfeng Ji*#, Yanjun Li, Jin Ye, Tianbin Li, Ming Hu, Rongshan Yu, Yu Qiao, Junjun He# (* equal contribution, # corresponding author)

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025

SlideChat is an open-source vision-language assistant for gigapixel whole-slide pathology images, built with SlideInstruction and evaluated on SlideBench across captioning and VQA tasks.

RAFNet: Restricted Attention Fusion Network for Sleep Apnea Detection
RAFNet: Restricted Attention Fusion Network for Sleep Apnea Detection

Ying Chen*, Huijun Yue*, Ruifeng Zou, Wenbin Lei, Wenjun Ma, Xiaomao Fan# (* equal contribution, # corresponding author)

Neural Networks 2023

RAFNet detects sleep apnea from single-lead ECG by using restricted attention to fuse target and adjacent ECG segments while suppressing redundant neighboring information.

RAFNet: Restricted Attention Fusion Network for Sleep Apnea Detection

Ying Chen*, Huijun Yue*, Ruifeng Zou, Wenbin Lei, Wenjun Ma, Xiaomao Fan# (* equal contribution, # corresponding author)

Neural Networks 2023

RAFNet detects sleep apnea from single-lead ECG by using restricted attention to fuse target and adjacent ECG segments while suppressing redundant neighboring information.

All publications