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