学士，联合培养项目，动物医学院，中国农业大学
学士，联合培养项目，农业与生命科学院， 康奈尔大学
硕士，免疫、流行病与分子遗传学系，匹兹堡大学医学院
硕士，生物统计学系，哥伦比亚大学公共卫生学院
博士，生物统计学系，匹兹堡大学公共卫生学院
2020-至今 讲师，统计学院，中国人民大学
2022-至今 中国老年学和老年医学学会老龄经济学分会 理事
国家自然科学基金委员会青年科学基金项目，主持，2022-2024
国家统计局重点项目，主持，2021-2023
中国人民大学新教师启动金项目，主持，2021-2023
ENAR Distinguished Student Paper Award (2019), ICSA Student Paper Award (2019)
生存分析，抽样技术，回归分析，复杂数据分析，生命表编制原理与分析技术，临床试验设计
• 统计理论：复杂生存数据模型，半参数统计模型，copula模型及其检验，高维变量选择
• 统计应用：老年失能与慢性病的预防与管理，深度学习疾病风险预测
• 医学统计：流行病学调查，生物信息学
统计方法论文
• Li, Y., Ren, X., Yu, H., Sun, T.*, Ma, S. (2023). PIN: A penalized integrative deep neural network for variable selection among multiple omics datasets. The 21st Asia Pacific Bioinformatics Conference. Accepted.
• Sun, T., Li, Y., Xiao, Z., Ding, Y., Wang, X. (2023). Semiparametric copula method for semi-competing risks data subject to interval censoring and left truncation: Application to disability in elderly. Statistical Methods in Medical Research. Accepted.
• Sun, T., Cheng, Y., Ding, Y. (2022). An Information Ratio-based Goodness-of-Fit Test for Copula Models on Censored Data. Biometrics. Accepted.
• Sun, T., Ding, Y. (2022). Neural network on interval-censored data with application to the prediction of Alzheimer’s disease. Biometrics. Accepted.
• Zhang, J., Siegle, G., Sun, T., D`Andrea, W., Krafty, R. (2021) Interpretable Principal Component Analysis for Multilevel Multivariate Functional Data. Biostatistics. Accepted.
• Sun, T., Ding. Y. (2021) Copula-based semiparametric regression model for bivariate data under general interval censoring. Biostatistics. 22(2), 315-330. DOI: 10.1093/biostatistics/kxz032. (codes available on GitHub)
• Sun, T., Wei, Y., Chen, W., Ding, Y. (2020) Genome-wide association study-based deep learning for survival prediction. Statistics in Medicine. Statistics in Medicine. 39(30), 4605-4620. (codes available on GitHub)
• Sun, T., Ding, Y. (2020) CopulaCenR: copula based regression models for bivariate censored data in R. The R Journal. 12(1), 266-282. (R package available on CRAN)
• Sun, T., Liu Y., Cook, R., Chen, W., Ding, Y. (2019) Copula-based score test for bivariate time-to-event data, with application to a genetic study of AMD progression. Lifetime Data Analysis. 25(3), 546-568.
• Wei, Y., Liu, Y., Sun, T., Chen, W., Ding, Y. (2019) Gene-based association analysis for bivariate time-to-event data through functional regression with copula models. Biometrics. 76(2), 619-629.
医学统计论文
• Grubisha, MJ, Sun, T, Erickson, SL, Helmer, CD, Ding, Y, Homanics, GE, Penzes, P, Wills, ZP, Sweet, RA. (2021). A Missense Mutation in Kalirin Enhances Neuronal RhoA Signaling and Leads to Regression of Cortical Dendritic Arbors Across Development. Proceedings of the National Academy of Sciences of the United States of America.
• Dai, H., Lan, P., Zhao, D., Abou-Daya, K., Liu, W., Chen, W., Friday, A., Williams, A., Sun, T., Chen, J., Chen, W., Mortin-Toth, S., Danska, J., Wiebe, C., Nickerson, P., Nicotra, M., Gingras, S., Kubagawa, H., Shlomchik, M., Oberbarnscheidt, M., Li, X., Lakkis, F. (2020) Paired immunoglobulin-like receptors mediate innate memory to non-self MHC molecules. Science. 368(6495), 1122-1127. (responsible for all bioinformatics analyses of high-dimensional single-cell RNA sequencing data)
• Sun, T., Sun, Z., Jiang Y., Ferguson. A., Pilewski, J., Kolls, J., Chen, W., Chen, K. (2019) Transcriptomic responses to Ivacaftor and prediction of Ivacaftor clinical responsiveness. American Journal of Respiratory Cell and Molecular Biology. 61(5), 643-652. (Editorial’s Highlight, clinically meaningful results based on bioinformatics data and machine learning)
• Yang, G.,* Sun, T.,* (co-first), Han, Y., Rosser, F., Forno, E., Chen, W., Celedón, J. (2019) Serum cadmium and lead, wheezing and lung function in a nationwide study of adults in the United States. Journal of Allergy and Clinical Immunology: In Practice. 7(8), 2653-2660. (responsible for processing and analyzing a large scale national health survey)
• Yano, H., Sawant, D., Chikina, M., Zhang, Q., Sun, Z., Sun, T., Chen, W., Workman, C., Vignali, D. (2019) Adaptive plasticity of IL10+ and IL35+ regulatory T cells and their cooperative regulation of anti-tumor immunity. Nature Immunology. 20(6), 724-735. (responsible for single-cell RNA data analyses)