Ming Jingsi

2015 - 2018    Hong Kong Baptist University    Doctor of Philosophy in Statistics

2013 - 2015    Fudan University                        Master of Finance in Financial Engineering

2009 - 2013    Fudan University                        Bachelor of Science in Statistics

2020.9 -                  Assistant Professor        East China Normal University    

2018.12 - 2020.8    Post-doctoral Fellow      Hong Kong University of Science and Technology

2018.9 - 2018.11    Research Assistant        Hong Kong University of Science and Technology

My name is Jingsi Ming, and I am currently an assistant professor in School of Statistics and Academy of Statistics and Interdisciplinary Sciences, East China Normal University. My research interests include data science with statistical machine learning and deep learning, statistical genetics and genomics, and integrative analysis of single-cell RNA-sequencing data. Before joining ECNU, I obtained both of my B.S. and M.S. degree from Fudan University in 2013 and 2015, and received my Ph.D. degree from Hong Kong Baptist University in 2018. I worked as a postdoctoral fellow in Hong Kong University of Science and Technology from 2018 to 2020.

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Data Science with Statistical Machine Learning and Deep Learning

Statistical Genetics and Genomics

Integrative Analysis of Single-cell RNA Sequencing Data

Statistical Learning

Statistical and computational methods in Biomedicine

Linear Algebra

The Young Scientists Fund of the National Natural Science Foundation of China, 12201219, Statistical and computational methods for integration of heterogeneous multi-source scRNA-seq data, 2023.1-2025.12, 300,000 Yuan, Principle Investigator.

Shanghai Sailing Program, 21YF1410600, Deep learning methods for single-cell RNA-sequencing data, 2021.5-2024.4, 200,000 Yuan, Principle Investigator.

[13]    The Tabula Microcebus Consortium, Camille Ezran#, Shixuan Liu#, Jingsi Ming, Lisbeth A. Guethlein, Michael F.Z. Wang, Roozbeh Dehghannasiri, Julia Olivieri, Hannah K. Frank, Alexander Tarashansky, Winston Koh, Qiuyu Jing, Olga Botvinnik, Jane Antony, Stephen Chang, Angela Oliverira Pisco, Jim Karkanias, Can Yang, James E. Ferrell Jr., Scott D. Boyd, Peter Parham, Jonathan Z. Long, Bo Wang, Julia Salzman, Iwijn De Vlaminck, Angela Wu, Stephen R. Quake*, Mark A. Krasnow* (2022+). Mouse lemur transcriptomic atlas elucidates primate genes, physiology, disease, and evolution.

[12]    The Tabula Microcebus Consortium, Camille Ezran#, Shixuan Liu#, Stephen Chang#, Jingsi Ming, Olga Botvinnik, Lolita Penland, Alexander Tarashansky, Antoine de Morree, Kyle J. Travaglini, Kazuteru Hasegawa, Hosu Sin, Rene Sit, Jennifer Okamoto, Rahul Sinha, Yue Zhang, Caitlin J. Karanewsky, Jozeph L. Pendleton, Maurizio Morri, Martine Perret, Fabienne Aujard, Lubert Stryer, Steven Artandi, Margaret Fuller, Irving L. Weissman, Thomas A. Rando, James E. Ferrell Jr., Bo Wang, Iwijn De Vlaminck, Can Yang, Kerriann M. Casey, Megan A. Albertelli, Angela Oliveira Pisco, Jim Karkanias, Norma Neff, Angela Wu, Stephen R. Quake*, Mark A. Krasnow* (2022+). Tabula Microcebus: A transcriptomic cell atlas of mouse lemur, an emerging primate model organism.

[11]    Siyuan Huang#, Linkun Ouyang#, Junjie Tang, Kun Qian, Xuanwei Chen, Zijie Xu, Jingsi Ming*, Ruibin Xi*(2024). Spatial transcriptomics: a new frontier in cancer research. Clinical Cancer Bulletin. 3(13). 

[10]    Shuang Dai, Jingsi Ming*, Zhou Yu (2023+). A distributed minimum average variance estimation for sufficient dimension reduction. Statistics and Its Interface. Accepted. 

[9]    Jingsi Ming, Jia Zhao, Can Yang* (2023). scPI: A scalable framework for probabilistic inference in single-cell RNA-sequencing data analysis. Statistics in Biosciences, 15:633-656.

[8]    Jia Zhao#, Gefei Wang#, Jingsi Ming, Zhixiang Lin, Yang Wang, The Tabula Microcebus Consortium, Angela Ruohao Wu*, Can Yang* (2022). Adversarial domain translation networks for integrating large-scale atlas-level single-cell datasets. Nature Computational Science, 2(5):317-330.

[7]    Jingsi Ming#, Zhixiang Lin#, Jia Zhao, Xiang Wan, The Tabula Microcebus Consortium, Can Yang*, Angela Ruohao Wu* (2022). FIRM: Flexible Integration of single-cell RNA-sequencing for large-scale Multi-tissue cell atlas datasets. Briefings in Bioinformatics, 23(5):bbac167.

[6]    Julia Eve Olivieri, Roozbeh Dehghannasiri, Peter L Wang, SoRi Jang, Antoine de Morree, Serena Y Tan, Jingsi Ming, Angela Ruohao Wu, Tabula Sapiens Consortium, Stephen R Quake, Mark A Krasnow, Julia Salzman* (2021). RNA splicing programs define tissue compartments and cell types at single cell resolution. eLife, 10:e70692.

[5]    Jingsi Ming, Tao Wang and Can Yang* (2020). LPM: a latent probit model to characterize the relationship among complex traits using summary statistics from multiple GWASs and functional annotations. Bioinformatics, 36(8): 2506-2514.

[4]    Jia Zhao, Jingsi Ming, Xianghong Hu, Gang Chen, Jin Liu, Can Yang* (2020). Bayesian weighted Mendelian randomization for causal inference based on summary statistics, Bioinformatics, 36(5): 1501-1508.

[3]    Mingxuan Cai, Mingwei Dai, Jingsi Ming, Heng Peng, Jin Liu, Can Yang* (2020). BIVAS: a scalable Bayesian method for bi-level variable selection with applications. Journal of Computational and Graphical Statistics, 29(1), 40-52.

[2]    Jingsi Ming, Mingwei Dai, Mingxuan Cai, Xiang Wan, Jin Liu*, Can Yang* (2018). LSMM: a statistical approach to integrating functional annotations with genome-wide association studies, Bioinformatics, 34(16): 2788-2796.

[1]    Mingwei Dai, Jingsi Ming, Mingxuan Cai, Jin Liu, Can Yang*, Xiang Wan*, Zongben Xu* (2017). IGESS: a statistical approach to integrating individual-level genotype data and summary statistics in genome-wide association studies, Bioinformatics, 33(18): 2882-2889.

#为共同第一作者，*为通讯作者及共同通讯作者