I am currently a PhD candidate in the School of Life Sciences at Tsinghua University, under the supervision of Prof. Fuchu He, focusing on computational biology, single-cell analysis, and deep learning research. For any inquiries regarding potential academic collaborations, please don’t hesitate to reach out to me via email at zhuj21@mails.tsinghua.edu.cn.

Previously, I earned my bachelor’s degree from the School of Life Sciences and Technology at Tongji University. During my undergraduate studies, I was advised by Dr. Qi Liu(刘琦) in the Department of Bioinformatics.

News

  • 2024.12:  🚀 Our Paper “DUSTED: Dual-attention Enhanced Spatial Transcriptomics Denoiser” has been accepted by AAAI-2025 and selected as Oral pre.
  • 2024.02:  🎉🎉 We release Cell Decoder !

Publications

DUSTED: Dual-attention Enhanced Spatial Transcriptomics Denoiser

Jun Zhu#,*, Yifu Li#, Zhenchao Tang#, et al.

Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2025)


Cell Decoder: Decoding cell identity with multi-scale explainable deep learning

Jun Zhu#, Zeyang Zhang#, Yujia Xiang, et al.

Under Review

Honors and Awards

  • 2023.02 MICOS (THE MAMMOTH INTERNATIONAL CONTEST ON OMICS SCIENCES), First Award
  • 2021.12 iGEM 2021, Best Software & Gold Medal, Team advisor.
  • 2021.06 Outstanding Graduates of Shanghai (Top 1%)
  • 2020.11 iGEM 2020, Gold Medal, Team leader.
  • 2020.10 National Scholarship (Top 1%)
  • 2019.10 National Scholarship (Top 1%)

Educations

  • 2021.09-now, PhD, Tsinghua University, Beijing.
  • 2017.09-2021.06, Undergraduate, Tongji Univeristy, Shanghai.

Invited Talks

  • 2025.02, Oral Presentation, AAAI Conference on Artificial Intelligence (AAAI-2025). (Philadelphia, USA)
  • 2024.09, Oral Pre, BENZON SYMPOSIUM No. 68 INTEGRATION OF MASS SPECTROMETRY-BASED PROTEOMICS AND AI TO REVOLUTIONIZE PERSONALIZED MEDICINE. (Copenhagen, Denmark)
  • 2023.11, The Fifth Chemical Biology Graduate Forum, Peking University.(Beijing, China)

Internships

  • 2024.05-Now, AI4Science Research Intern; Tencent, AI Lab, Shenzhen.
  • 2021.04-2021.08, AI4Science Machine Learning Research Intern; Baidu, NLP group, Shanghai.
    ·Tumor typing using Omics data based on graph neural network
    ·Development of nearly one million sample clustering algorithms