SONG, Fangda

Assistant Professor (Fixed Term)

Education Background

Ph.D. in Statistics, The Chinese University of Hong Kong, 2020
B.Sc. in Statistics, Zhejiang University, 2016

Research Field
Bayesian Statistics, Statistical Genomics, Statistical Computing and Big Data Analysis
Personal Website
Email
songfangda@cuhk.edu.cn
Office
Room 519, Daoyuan Building
Biography

Dr. Fangda SONG is an Assistant Professor in School of Data Science, The Chinese University of Hong Kong, Shenzhen, since August 2021. He obtained his B.Sc. in Statistics from Zhejiang University in 2016. Then, he received his Ph.D. degree in Statistics at the Chinese University of Hong Kong in 2020 under the supervision of Prof. Yingying WEI. During his PhD study, he visited Biostatistics department at Yale university supervised by Prof. Shuangge MA in 2018. His main research interest lies in developing novel statistical models, providing theoretical justifications, and developing computationally efficient algorithms to analyze data arising from various cutting-edge fields, including genomics, social networks and e-learnings.

Academic Publications

SELECTED PUBLICATIONS

1. Fangda Song, Jing Chu, Shuangge Ma and Yingying Wei (2023+) Survival Mixed Membership Blockmodel. Journal of the American Statistical Association, accepted.

2. Ran Wang, Xubin Zheng, Jun Wang, Shibiao Wan, Fangda Song, Man Hon Wong, Kwong Sak Leung, and Lixin Cheng (2022) Improving bulk RNA-seq classification by transferring gene signature from single cells in acute myeloid leukemia. Briefings in Bioinformatics, 23(2). 

3. Fangda Song, Ga Ming Chan and Yingying Wei (2020) Flexible Experimental Designs for Valid Single-cell RNA-sequencing Experiments Allowing Batch Effects Correction. Nature Communications, 11(1), 1-15.