Career lApr. 2024 - Present, Postdoc, ShanghaiTech University lDec. 2018 - Jun. 2019, Algorithm Engineer, National Supercomputing Center in Wuxi Education lJun. 2019 - Dec. 2023, Ph.D. in Statistics, Newcastle University lSep. 2015 - Jun.2018, M.S. in Applied Mathematics, Jiangnan University lSep.2011 - Jun.2015, B.S. in Mathematics and Applied Mathematics, Huangshan University Research Interests I have a wide range of interests in data science, including functional data analysis, machine learning, and non-Euclidean statistics, with applications to diverse data backgrounds. My Ph.D. project centered on statistical modelling and manifold-valued data in computational neuroscience. Geometrical ideas frequently influence the way I think and solve problems. Selected publications lDing, T., Nye, T. M., & Wang, Y. (2024). Manifold-valued models for analysis of EEG time series data. arXiv preprint arXiv:2402.06410. lWang, Y., Xuan, C., Wu, H., Zhang, B., Ding, T., & Gao, J. (2023). P-CSN: single-cell RNA sequencing data analysis by partial cell-specific network. Briefings in Bioinformatics, 24(3), bbad180. lXuan, C., Wang, Y., Zhang, B., Wu, H., Ding, T., & Gao, J. (2022). scBPGRN: Integrating single-cell multi-omics data to construct gene regulatory networks based on BP neural network. Computers in Biology and Medicine, 151, 106249. lWang, Y., Zhou, G., Guan, T., Wang, Y., Xuan, C., Ding, T., & Gao, J. (2022). A network-based matrix factorization framework for ceRNA co-modules recognition of cancer genomic data. Briefings in Bioinformatics, 23(5), bbac154. lDing, T., Gao, J., Zhu, S., Xu, J., & Wu, M. (2019). Predicting microRNA-disease association based on microRNA structural and functional similarity network. Quantitative Biology, 7, 138-146. lSun, M., Ding, T., Tang, X. Q., & Yu, K. (2018). An efficient mixed-model for screening differentially expressed genes of breast cancer based on LR-RF. IEEE/ACM transactions on computational biology and bioinformatics, 16(1), 124-130. lDing, T., Xu, J., Sun, M., Zhu, S., & Gao, J. (2017). Predicting microRNA biological functions based on genes discriminant analysis. Computational biology and chemistry, 71, 230-235. Software lR package “geomTS”: Analyzing manifold-valued time series with applications to EEG data, 2023. (install_github(TaoDing2/geomTS). |
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