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 of Technology
Research Interest My group operates at the intersection of Statistics, Computational Biology and Data Science, with a primary focus on: (i) functional data analysis, (ii) biomedical big data analysis, (iii) statistical machine learning, and (iv) AI-driven methodology. We aim to develop rigorous statistical and AI methods that address fundamental challenges in complex data analysis, integrating practical solutions with theoretical guarantees.
Publications (†: Co-first authors; *: Corresponding authors；Bold: Group members): 1. Pengcheng Zeng†* and Siyuan Jiang†. (2025) Semi-parametric Functional Classification via Path Signatures Logistic Regression. https://arxiv.org/abs/2507.06637. 2. Hongyao Li†, Yunrui Liu†and Pengcheng Zeng*. (2025) Guided Co-clustering Transfer Across Unpaired and Paired Single-cell Multi-omics Data. https://www.biorxiv.org/content/10.1101/2025.05.16.654635v1. 3. Siyuan Jiang†, Yihan Hu†, Wenjie Li and Pengcheng Zeng*. (2025) DeepFRC: An End-to-End Deep Learning Model for Functional Registration and Classification. https://arxiv.org/abs/2501.18116. 4. Chen Jason Zhang†, Yunrui Liu†, Pengcheng Zeng*, Ting Wu, Lei Chen, Pan Hui and Fei Hao. (2024) Similarity-driven and Task-driven Models for Diversity of Opinion in Crowdsourcing Markets. The VLDB Journal 33, 1377–1398 (2024). https://doi.org/10.1007/s00778-024-00853-0. (CCF-A) 5. Pengcheng Zeng* and Zhixiang Lin. (2024) 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. (CCF-A) 6. Pengcheng Zeng and Zhixiang Lin*. (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. 7. Yuanyuan Ma, Zexuan Sun, Pengcheng Zeng, Wenyu Zhang and Zhixiang Lin*. (2022) JSNMF enables effective and accurate integrative analysis of single-cell multi-omics data. Briefings in Bioinformatics. 23(3):bbac105. 8. Lin Tang†, Pengcheng Zeng†, Jian Qing Shi* and Won-Seok Kim. (2022) Model-based joint curve registration and classification. Journal of Applied Statistics. https://doi.org/10.1080/02664763.2021.2 023118. 9. Pengcheng Zeng and Zhixiang Lin*. (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. 10. Pengcheng Zeng, Jiaxuan Wangwu and Zhixiang Lin*. (2020) Coupled co-clustering-based unsupervised transfer learning for the integrative analysis of single-cell genomic data. Briefings in Bioinformatics. 22(4):bbaa34. 11. Pengcheng Zeng, Jian Qing Shi* and Won-Seok Kim. (2019) Simultaneous registration and clustering for multi-dimensional functional data. Journal of Computational and Graphical Statistics. 4(28), 943-953. 12. Won-Seok Kim†, Pengcheng Zeng†, Jian Qing Shi*, Youngjo Lee and Nam-Jong Paik. (2017) Semi-automatic Tracking, Smoothing and Segmentation of Hyoid Bone Motion from Videoflfluoroscopic Swallowing Study. PLoS ONE 12(11): e0188684. https://doi.org/10.1371/journal. |
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