Hangzhou He

Hangzhou He

first-year Ph.D. student at Peking University

Hi! I’m Hangzhou He (何航舟), a Ph.D. student at College of Future Technology, Peking University. I work at Molecular Imaging / Medical Intelligence Lab (MILAB) at Peking University, under the supervision of assistant professor Yanye Lu and professor Qiushi Ren.

My research interests focus on the trustworthiness of deep learning models, including explainability, generalization and their applications in medical image analysis. I am also passionate about leveraging AI for artistic creation ;-). You can find me on Google Scholar, Github, or contact me via Email.

Currently, I am working on the intersection of concept bottleneck models and large (vision-) language models, if you’re interested in these topics, I would appreciate it if you could reach out to me for a chat or collaboration.

Publications

(#: Equal Contribution; *: Corresponding Author)

  • Generative learning-based lightweight MRI brain tumor segmentation with missing modalities
    Xinliang Zhang, Qian Chen, Hangzhou He, Lei Zhu, Zhaoheng Xie, Yanye Lu*, Fangxiao Cheng*
    Expert Systems with Applications
    [pdf] [doi] [code]

  • Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation
    Lei Zhu, Xinliang Zhang, Hangzhou He, Qian Chen, Sha Li, Shuang Zeng, Yibao Zhang, Qiushi Ren, Yanye Lu*
    IEEE Transactions on Neural Networks and Learning Systems
    [pdf] [arxiv] [code]

  • Low-Rank Mixture-of-Experts for Continual Medical Image Segmentation
    Qian Chen, Lei Zhu, Hangzhou He, Xinliang Zhang, Shuang Zeng, Qiushi Ren, Yanye Lu*
    MICCAI 2024
    [pdf] [arxiv] [code]

  • On the Duality Between Sharpness-Aware Minimization and Adversarial Training
    Yihao Zhang#, Hangzhou He#, Jingyu Zhu#, Huanran Chen, Yifei Wang, Zeming Wei*
    ICML 2024
    [pdf] [arxiv] [code]

  • Scribble Hides Class: Promoting Scribble-based Weakly-supervised Semantic Segmentation with Its Class Label
    Xinliang Zhang#, Lei Zhu#, Hangzhou He, Lujia Jin, Yanye Lu*
    AAAI 2024
    [pdf] [arxiv] [code]

Projects

  • PyTorch Attribution Toolbox
    Attribution methods for explaining image classification models.
    [Github]
    image

Honors and Awards

  • Dean’s scholarship, College of Future Technology, Peking University, 2024
  • Excellent Graduate, Peking University, 2024
  • Honours Degrees, College of Engineering, Peking University, 2024
  • Grand Challenges Scholar, the Grand Challenges Scholars Program (GCSP), 2024
  • Third Prize of the 32nd Challenge Cup, Peking University, 2024
  • Outstanding Project Award for undergraduate research training, Peking University, 2024
  • Award for Academic Excellents, Peking University, 2023
  • Outstanding Project Award for undergraduate research training, College of Engineering, Peking University, 2023

Educations

  • 2024.09 - Present, Ph.D. candidate in Biomedical Engineering, College of Future Technology, Peking University
  • 2020.09 - 2024.07, B.S. major in Theoretical and Applied Mechanics, College of Engineering, Peking University
  • 2020.09 - 2024.07, B.S. minor in Biomedical Engineering, College of Engineering, Peking University

Internships

  • 2023.07 - 2023.09, Research Intern, United Imaging Intelligence, RIID, Beijing, China
    • Large language models for medical image analysis and structured reports
    • Supervisor: Dr. Pei Dong

Services

Conference Reviewer: ICLR2025

🔗 Links