Career • 2021.12-present, Assistant Professor, ShanghaiTech University • 2019.9-2021.11, Postdoctoral Fellow, The Chinese University of Hong Kong • 2018.5-2019.8, Data Scientist/Senior Manager, Headquarters of Country Garden Group Education • July 2018, Ph.D. in Statistics, Newcastle University, United Kingdom • July 2014, M.S. in Probability and Statistics, University of Science and Technology of China •July 2011, B.S. in Mathematics, Hefei University ofTechnology
Research Interest My research area includes Statistics, Data Science and Bioinformatics. I am also interested in Machine Learning and Deep Learning. The focus of my current research work is on developing statistical methods and computational tools for analyzing cutting-edge large-scale genomic data and healthcare data.
Selected Publications [1] Zeng, P.# and Lin, Z. (2023) scICML: Information-theoretic Co-clustering-based Multi-view Learning for the Integrative Analysis of Single-cell Multi-omics data. IEEE/ACM Transactions on Computational Biology and Bioinformatics. DOI : 10.1109/TCBB.2023.3305989. (#:corresponding author) [2] Zeng, P. and Lin, Z. (2023) scAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data. Bioinformatics, 39(1), btac739. [3] Ma, Y., Sun, Z., Zeng, P., Zhang, W. and Lin, Z. (2022) JSNMF enables effective and accurate integrative analysis of single-cell multi-omics data. Briefings in Bioinformatics. 23(3):bbac105. [4] Tang, L.*, Zeng, P.*, Shi, J.Q. and Kim, W-S. (2022) Model-based joint curve registration and classification. Journal of Applied Statistics. https://doi.org/10.1080/02664763.2021.2 023118. (*:co-first authors) [5] Zeng, P. and Lin, Z. (2021) coupleCoC+: an information-theoretic co-clustering-based transfer learning framework for the integrative analysis of single-cell genomic data. PLoS Computational Biology. 17(6): e1009064. [6] Zeng, P., Wangwu, J. and Lin, Z. (2021) Coupled Co-clustering-based Unsupervised Transfer Learning for the Integrative Analysis of Single-Cell Genomic Data. Briefings in Bioinformatics. 22(4), bbaa347. [7] Zeng, P. and Lin, Z. (2020) Elastic Coupled Co-clustering for Single-Cell Genomics Data. Preprint. https://arxiv.org/abs/2003.12970. [8] Zeng, P., Shi, J.Q. and Kim, W-S. (2019) Simultaneous Registration and Clustering for Multi-dimensional Functional Data. Journal of Computational and Graphical Statistics. 4(28), 943-953. [9] Kim, W-S.*, Zeng, P.*, Shi, J.Q., Lee, Y. and Paik, N-J. (2017) Semi-automatic Tracking, Smoothing and Segmentation of Hyoid Bone Motion from Videofluoroscopic Swallowing Study. PLoS ONE. 12(11): e0188684. (*: co-first authors) |
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