数学科学研究所
Insitute of Mathematical Science

曾鹏程 Pengcheng Zeng


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 authorsBold: 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 Liuand 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 TangPengcheng 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. 















Email:

 zengpch@shanghaitech.edu.cn

Office: S512, School of Creativity & Arts




地址:上海市浦东新区华夏中路393号
邮编:201210
上海市徐汇区岳阳路319号8号楼
200031(岳阳路校区)