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Yixiong Chen

I am currently a first-year CS Ph.D. student at Johns Hopkins University, advised by Bloomberg Distinguished Professor Alan Yuille.

I received my B.S. in Data Science from Fudan University in 2021. After that, I worked as a research assistant at Shenzhen Research Institute of Big Data, where I was honored to work with Dr. Li Liu and Prof. Chris Ding. I will never forget the time spent in Shenzhen which taught me to be grateful and concentrate.

My research focuses on medical image analysis, representation learning, self-supervised learning, and generative models.

I'm currently looking for an opportunity of summer intern in 2024, welcome to contact me via email!

Email  /  Google Scholar  /  Github  /  Linkedin  /  CV


  • 12/2023, 1 paper has been accepted by ICASSP 2024.
  • 08/2023, I join CCVL@JHU as a new Ph.D. student.
  • 06/2023, 1 paper has been accepted by MICCAI 2023.
  • 02/2023, 1 paper has been accepted by CVPR 2023.
  • 12/2022, 1 paper has been accepted by ICLR 2023.
  • 12/2022, 1 journal paper has been accepted by IEEE TMI.
  • Research

    I'm interested in exploring the mechanism behind deep learning, designing efficient training algorithms for transfer learning and generative modeling, as well as the applications for medical image analysis.

    Conference Papers:

    1. Leveraging Noisy Labels of Nearest Neighbors for Label Correction and Sample Selection
      Hua Jiang, Yixiong Chen, Li Liu, Xiaoguang Han, Xiaoping Zhang
      ICASSP 2024 (coming soon)

    2. MetaLR: Layer-wise Learning Rate based on Meta-learning for Adaptively Fine-tuning Medical Pre-trained Models
      Yixiong Chen, Jingxian Li, Hua Jiang, Li Liu, Chris Ding
      MICCAI 2023 | paper

    3. Label-Free Liver Tumor Segmentation
      Qixin Hu, Yixiong Chen, Junfei Xiao, Shuwen Sun, Jieneng Chen, Alan Yuille, Zongwei Zhou
      CVPR 2023 | paper

    4. Which Layer is Learning Faster? A Systematic Exploration of Layer-wise Convergence Rate for Deep Neural Networks
      Yixiong Chen, Alan Yuille, Zongwei Zhou
      ICLR 2023 | paper

    5. HiCo: Hierarchical Contrastive Learning for Ultrasound Video Model Pretraining
      Chunhui Zhang, Yixiong Chen, Li Liu, Qiong Liu, Xi Zhou
      ACCV 2022 | paper

    6. USCL: pretraining deep ultrasound image diagnosis model through video contrastive representation learning
      Yixiong Chen, Chunhui Zhang, Li Liu, Cheng Feng, Changfeng Dong, Yongfang Luo, Xiang Wan
      MICCAI 2021 | paper | Oral Presentation

    Journal Papers:

    1. Generating and weighting semantically consistent sample pairs for ultrasound contrastive learning
      Yixiong Chen, Chunhui Zhang, Chris HQ Ding, Li Liu
      IEEE TMI 2023 | paper

    Workshop Papers:

    1. Synthetic Tumors Make AI Segment Tumors Better
      Qixin Hu, Junfei Xiao, Yixiong Chen, Shuwen Sun, Jie-Neng Chen, Alan Yuille, Zongwei Zhou
      NeurIPS Workshop 2022 | paper

    2. When person re-identification meets changing clothes
      Fangbin Wan, Yang Wu, Xuelin Qian, Yixiong Chen, Yanwei Fu
      CVPR Workshop 2020 | paper

    Preprint Papers:

    1. Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis
      Xiaoshi Wu, Yiming Hao, Keqiang Sun, Yixiong Chen, Feng Zhu, Rui Zhao, Hongsheng Li
      Arxiv 2023 | paper

    2. X-IQE: eXplainable Image Quality Evaluation for Text-to-Image Generation with Visual Large Language Models
      Yixiong Chen, Li Liu, Chris Ding
      Arxiv 2023 | paper

    3. Rethinking Two Consensuses of the Transferability in Deep Learning
      Yixiong Chen, Jingxian Li, Chris Ding, Li Liu
      Arxiv 2022 | paper


  • 06/2023, Meta-learning for adaptive fine-tuning. Thanks Dr. Zongwei Zhou for the invitation.
  • 02/2023, The property of DNN's layer-wise convergence. Thanks Dr. Zongwei Zhou for the invitation.
  • Services

  • Reviewer of MICCAI 2023, ICML 2023, T-ASE.

  • Teaching assistant at CUHK (Shenzhen).

  • Awards

  • 2023, Excellent Paper on Science and Technology of Shenzhen.

  • 2022, Excellent Paper on Artificial Intelligence of Shenzhen.

  • 2021, Second Class Scholarship for Outstanding Graduates of Fudan University.

  • 2018, Huawei Cloud Scholarship.

  • 2015, 1st prize of National Physics Competition of China.

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