Hangzhou He

Hangzhou He

Ph.D. student at Peking University

Hi! I’m Hangzhou He (何航舟) from Peking University. I’m a first-year Ph.D. student at the Molecular Imaging and Medical Intelligence Lab (MILab), under the supervision of assistant professor Yanye Lu and professor Qiushi Ren.

My research focuses on the intersection of artificial intelligence and biomedical applications, with a particular emphasis on the trustworthiness of deep learning models, including explainability, generalization, and robustness.

Publications

(#: Equal Contribution; *: Corresponding Author)

  • V2C-CBM: Building Concept Bottlenecks with Vision-to-Concept Tokenizer
    Hangzhou He, Lei Zhu, Xinliang Zhang, Shuang Zeng, Qian Chen, Yanye Lu*
    AAAI 2025 (main track poster and oral at workshop)
    [pdf] [doi] [code]

  • 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 (poster)
    [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 (poster)
    [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 (poster)
    [pdf] [arxiv] [code]

Projects

  • PyTorch Attribution Toolbox
    Feature attribution methods for explaining image classification models, with a Chinese patent (ZL 2024 1 0941326.8)
    [Github]
    image

Honors and Awards

  • AAAI-25 Student Scholarship, AAAI, 2025
  • 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 Scholar, Grand Challenges Scholars Program & Peking University, 2024 (Top 5 undergraduates university-wide)
  • Outstanding Project Award for undergraduate research training, Peking University, 2024
  • Award for Academic Excellents, Peking University, 2023

Educations

  • 2024.09 - Present, Ph.D. student 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
  • Conference Volunteer: AAAI2025

Talsk