M.S., Ph.D. in Computer Science, King Abdullah University of Science and Technology, Saudi Arabia (2020-2025).

B.S. in Bioinformatics, Southern University of Science and Technology, China (2016-2020)

Professor Juexiao Zhou is an Assistant Professor at the School of Data Science. He obtained his bachelor’s degree in Bioinformatics from the Southern University of Science and Technology (SUSTech) in 2020 and his Ph.D. degree in Computer Science from King Abdullah University of Science and Technology (KAUST) in 2025. His research lies at the intersection of computer science and biomedicine, focusing on intelligent healthcare and bioinformatics. He specializes in developing cutting-edge AI algorithms for healthcare applications, including disease detection, risk assessment, and predictive modeling. He also works on developing new methods in bioinformatics, such as gene regulatory networks, functional and structural prediction, and systems biology. Additionally, his work addresses critical challenges in deep learning, privacy, security, and Artificial General Intelligence (AGI) within medical contexts. He has published over 30 academic papers in prestigious journals and conferences, including Science Advances, Nature Machine Intelligence, Nature Communications, Trends in Genetics, The Lancet, Genome Research, Bioinformatics, and MICCAI. His research has been widely covered by mainstream media outlets, such as Arab News, Radio Television Hong Kong (RTHK), and Inside Precision Medicine. He is a member of CAAI/APBioNET/GBD and serves as a reviewer for several SCI journals, including Nature, Nature Communications, Medical Image Analysis, Computers in Biology and Medicine, Computational Biology and Chemistry, Computerized Medical Imaging and Graphics, Genome Biology, Genome Research, and IEEE Transactions on Knowledge and Data Engineering. He also reviews for various international conferences, such as NeurIPS, IJCAI-ECAI, ICONIP, MICCAI, and SIGKDD.

1. Juexiao Zhou#, Xiaonan He#, Liyuan Sun#, Jiannan Xu, Xiuying Chen, Yuetan Chu, Longxi Zhou, Xingyu Liao, Bin Zhang, Shawn Afvari, Xin Gao*. Pre-trained Multimodal Large Language Model Enhances Dermatological Diagnosis using SkinGPT-4. Nature Communications (IF: 17). DOI: 10.1038/s41467-024-50043-3.
2. Juexiao Zhou#, Haoyang Li#, Xingyu Liao, Bin Zhang, Wenjia He, Zhongxiao Li, Longxi Zhou, Xin Gao*. A unified method to revoke the private data of patients in intelligent healthcare with audit to forget. Nature Communications (IF: 17). DOI: 10.1038/s41467-023-41703-x
3. Juexiao Zhou#, Siyuan Chen#, Yulian Wu#, Haoyang Li, Bin Zhang, Longxi Zhou, Yan Hu, Zihang Xiang, Zhongxiao Li, Ningning Chen, Wenkai Han, Di Wang and Xin Gao*. PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data. Science Advances (IF: 15.4). DOI: 10.1126/sciadv.adh8601
4. Juexiao Zhou#, Bin Zhang#, Guowei Li, Xiuying Chen, Haoyang Li, Xiaopeng Xu, Siyuan Chen, Liwei Liu, Xin Gao*. An AI Agent for Fully Automated Multi-omic Analyses. Advanced Science (IF: 15.1). DOI: 10.1002/advs.202407094
5. Juexiao Zhou, Chao Huang, Xin Gao*. Patient privacy in AI-driven omics methods. Trends in Genetics (IF: 11.4). DOI: 10.1016/j.tig.2024.03.004
6. Juexiao Zhou#, Bin Zhang#, Haoyang Li, Longxi Zhou, Zhongxiao Li, Yongkang Long, Wenkai Han, Mengran Wang, Huanhuan Cui, Wei Chen, Xin Gao*. Annotating TSSs in Multiple Cell Types Based on DNA Sequences and RNA-seq Data via DeeReCT-TSS. Genomics, Proteomics & Bioinformatics (IF: 10.1). DOI: 10.1016/j.gpb.2022.11.010
7. Juexiao Zhou#, Longxi Zhou#, Di Wang, Xiaopeng Xu, Haoyang Li, Yuetan Chu, Wenkai Han, Xin Gao*. Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI. Computers in Biology and Medicine (IF: 7.7). DOI: 10.1016/j.compbiomed.2023.107861
8. Haoyang Li#, Juexiao Zhou#, Zhongxiao Li, Siyuan Chen, Xingyu Liao, Bin Zhang, Ruochi Zhang, Yu Wang, Shiwei Sun, Xin Gao*. A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomic. Nature Communications (IF: 17). DOI: 10.1038/s41467-023-37168-7
9. Longxi Zhou#, Xianglin Meng#, Yuxin Huang#, Kai Kang#, Juexiao Zhou, Yuetan Chu, Haoyang Li, Dexuan Xie, Jiannan Zhang, Weizhen Yang, Na Bai, Yi Zhao, Mingyan Zhao, Guohua Wang, Lawrence Carin, Xigang Xiao, Kaijiang Yu, Zhaowen Qiu, Xin Gao*. An Interpretable Deep Learning Workflow for Discovering Sub-Visual Abnormalities in CT Scans of COVID-19 Inpatients and Survivors. Nature machine intelligence (IF: 25.9). DOI: 10.1038/s42256-022-00483-7
10. Wenkai Han#, NingNing Chen#, Xinzhou Xu, Adil Salhi, Juexiao Zhou, Zhongxiao Li, Huawen Zhong, Elva Gao, Ruochi Zhang, Yu Wang, Shiwei Sun, Peter Cheung, Xin Gao*. Predicting the antigenic evolution of SARS-COV-2 with deep learning. Nature Communications (IF: 17). DOI: 10.1038/s41467-023-39199-6.

A complete list of publications can be found at https://www.joshuachou.ink/publications/