童立，男，助理教授，2014年本科毕业于北京大学生物医学工程系，2020年博士毕业于美国佐治亚理工与埃默里大学生物医学工程系。博士毕业后回国加入上海联影医疗科技股份有限公司磁共振事业部，担任资深应用开发工程师，从事基于磁共振成像的医学影像算法创新与相关辅助诊断算法的开发，相关成果已申请国内外专利30余篇，授权专利4项。2025年12月加入深圳大学医学部生物医学工程学院担任助理教授，目前主要的研究方向为多模态医学图像处理，以及基于多模态生物医学数据融合的计算机辅助诊断和精准治疗等。相关成果已发表在IEEE Journal of Biomedical and Health Informatics, Journal of the American Medical Informatics Association, IEEE Reviews in Biomedical Engineering等领域内权威期刊上。多次参加包括IEEE EMBS, IEEE BHI, ACM BCB, ISMRM等在内的国际性学术会议并进行口头汇报，并担任IEEE Healthcare Summit (IHS) 2021的Young Professional Activities Co-Chair和即将担任ACM BCB 2026的Poster Co-Chair.

- 医学图像处理和机器学习

- 多模态生物医学数据融合与精准医学

- 医学多模态大模型及其在辅助诊断中的应用

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2. Tong, L., Wu, H., Wang, M. D., & Wang, G. (2022). Introduction of medical genomics and clinical informatics integration for p-Health care. Progress in molecular biology and translational science, 190(1), 1-37.

3. Tong, L., Wu, H., & Wang, M. D. (2021). Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer. Methods, 189, 74-85.

4. Tong, L., Mitchel, J., Chatlin, K., & Wang, M. D. (2020). Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis. BMC medical informatics and decision making, 20, 1-12.

5. Tong, L., Wu, H., & Wang, M. D. (2019). CAESNet: Convolutional AutoEncoder based Semi-supervised Network for improving multiclass classification of endomicroscopic images. Journal of the American Medical Informatics Association, 26(11), 1286-1296.