Career Apr. 2024 - Present, Postdoctoral Fellow, ShanghaiTech University Dec. 2022 – Mar. 2023, Research Associate, Newcastle University Dec. 2018 - Jun. 2019, Algorithm Engineer, National Supercomputing Center in Wuxi
Education Jun. 2019 - Dec. 2023, Ph.D. in Statistics, Newcastle University Sep. 2015 - Jun.2018, M.S. in Applied Mathematics, Jiangnan University
Research Interests My research focuses on non-Euclidean statistics and deep learning, with applications in Bioinformatics, including spatial omics, neuroscience, and biomedical data analysis. Geometrical ideas frequently influence the way I think and solve problems.
Selected publications (First author) Ding, T., & Zeng, P. (2026). GALA: A unified landmark-free framework for coarse-to-fine spatial alignment across resolutions and modalities in spatial transcriptomics. Briefings in Bioinformatics. (Accepted). Ding, T., Nye, T. M., & Wang, Y. (2025). Manifold-valued models for analysis of EEG time series data. Computational Statistics & Data Analysis, 209, 108168. Ding, 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. Ding, 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. |
Email: Homepage: Office: S316, School of Creativity & Arts |
