Call me by 😉#
Hi, I’m Jingyun Yang.
Close friends call me Xiaoyang, which means “little lamb.” 🐑
I am a fifth-year Ph.D. student in Data and Information Science at Tsinghua University, supervised by Prof. Yang Li. I received my B.S. in Computer Science from the University of Electronic Science and Technology of China in 2020.
My research focus is medical data understanding processing, including images, point clouds, and radiology reports, by integrating reinforcement learning, active learning, and transfer learning to improve model generalization. If you are interested, please visit my research page.
I’m currently looking for postdoctoral opportunities, so if you have any tips or openings, please reach out. Download my CV to see what I do — don’t miss the chance to offer me a job. 🤲
News about me! 🥳
- 2025/09 Started an internship at Huawei, working on multimodal learning for biomedical data.
- 2025/06 One paper accepted at MICCAI 2025; one paper accepted at HAIC 2025 (spotlight talk).
- 2025/01 One paper accepted at ISBI 2025.
- 2024/12 Received the IEEE Student Travel Award at BIBM 2024.
Selected publications 🥸
Hierarchical Feature Learning for Medical Point Clouds via State Space Model
Guoqing Zhang * , Jingyun Yang * and Yang Li
In International Conference on Medical Image Computing and Computer-Assisted Intervention 2025.
Code is available at the GitHub repository: Flemme.
Adapting Foundation Models for Few-shot Medical Image Segmentation:
Actively and Sequentially
Jingyun Yang, Guoqing Zhang, Jingge Wang and Yang Li
In IEEE International Symposium on Biomedical Imaging 2025.
Code is available at the GitHub repository: ASAP.
Joint PVL Detection and Manual Ability Classification using Semi-Supervised Multi-task Learning
Jingyun Yang, Jie Hu, Yicong Li, Heng Liu and Yang Li
In International Conference on Medical Image Computing and Computer-Assisted Intervention 2021.
Visit Cheyenne 🥰
Visit qg, songzi, and juzi 🐱