Beijing Key Laboratory of Multimedia and Intelligent Software Technology

We are interested in developing efficient and effective deep learning methods for computer vision and machine learning. The impact areas include image perception (recognition, detection, retrieval, etc.), image generation (image-to-image translation, image enhancement, controllable image synthesis, etc.), multimedia analysis (visual question answering, referring expression comprehension), and advanced machine learning techniques (zero-shot learning, few-shot learning, continual learning, etc.).

To Prospective Students

I am looking for about 2~3 outstanding M.S. students to join the group each year. Students will either work on computer vision or machine learning, or both. If you are doing relevant research and have a strong track record and interest in joining our group, please feel free to contact me.

M.S Application

Before applying, please carefully and seriously read the letters from Profs. Mu-ming Poo and Zhihua Zhou. When applying for M.S. chance at BJUT, you can list me as your interested faculty in the system, and EMAIL me ahead of time for mutual understanding of What you Think and What you Want.

To Undergraduates

If you are an undergraduate student and want to join us, please read the undergraduate requirement from Prof. Song-Chun Zhu.

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Current members

  • Research Associates:
    • None
  • PhD Students:
      None
  • Ms Students:
    • Zhengxian Li (2023-)
    • Chenxu Li (2023-)
    • Ji Zhao (2023-)
    • Jie Liu (2023-)
    • Xichao Yu (2024-)
    • Jiapu Li (2024-)
    • Hongbin Xue (2025-)
  • Undergraduate Students:
    • Yizhi Li (2025-)
    • Jijun Chen (2025-)

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Alumni

  • Graduated PhD Students:
    • Jing Liu (2021-2025)
    • Yandong Bi (2020-2024): Shandong Agricultural University
    • Kai Sun (2019-2024)
  • Graduated Ms Students:
    • Jiasen Zhang (2022-2025)
    • Lincong Feng (2021-2024)
    • Mengting Liu (2021-2024)
    • Hanfu Zhang (2020-2023)
    • Yunru Zhang (2020-2023)
  • Previous Undergraduates and RAs:
    • None

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