Research output per year
Research output per year
Personal profile
Personal profile
Dr. Mengfei Ran is a mathematical statistician whose research spans a wide range of areas in statistics, with a particular focus on theoretical innovation. He has profound expertise in longitudinal data analysis, nonparametric/semiparametric statistics, robust estimation etc.
He received his Ph.D. in mathematical statistics at Osaka University and his Master’s degree in mathematical statistics at the University of California, Riverside. This cross-cultural academic training has shaped his unique approach to research and allowed him to build connections across global academic and professional communities. Prior to join XJTLU, he worked at Jiangsu Hengrui Pharmaceuticals and WuXi Biologics as a biostatistician respectively.
Mengfei‘s work not only explores the cutting edge of statistical theory but also aims to apply these advancements to practical problems, driving progress across various scientific fields.
Research interests
Longitudinal Data Analysis, Functional Data Analysis
Time Series Theory, Robust Estimation
Nonparametric/Semiparametric Statistics
Experience
Assistant Professor, XJTLU 2025.01- present
Clinical Statistician, Jiangsu Hengrui Pharmaceuticals Co., Ltd 2024.04 - 2024.10
Biostatistician, WuXi Biologics 2022.03 - 2022.06
Visiting Scholar, University of Göttingen 2019.07 - 2019.08
Visiting Scholar, University of Copenhagen 2019.02 - 2019.05
Education/Academic qualification
PhD, Osaka University
Oct 2018 → Mar 2024
Master, University of California, Riverside
Sept 2016 → Jun 2018
Person Types
- Staff
Fingerprint
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Collaborations and top research areas from the last five years
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Research output
- 7 Article
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Analysis of Rank Regression Modeling in Functional Data
Ran, M., 2025, (Accepted/In press) In: Statistics and its Interface.Research output: Contribution to journal › Article › peer-review
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Multiple Robust Estimation and Prediction of Quantile Regression in Longitudinal Data
Ran, M., 2025, (Submitted) In: Journal of Statistical Computation and Simulation.Research output: Contribution to journal › Article › peer-review
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Robust variable selection via nonconcave penalties with an upgraded parsimonious dynamic covariance modeling
Ran, M. & Xu, L., 2024, In: Communications in Statistics: Simulation and Computation. 53, 10, p. 4685–4702Research output: Contribution to journal › Article › peer-review
Open Access -
Robust semiparametric modeling of mean and covariance in longitudinal data
Ran, M., Yang, Y. & Kano, Y., 2023, In: Japanese Journal of Statistics and Data Science . 6, p. 625–648Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus) -
Optimal Estimation of Large Functional and Longitudinal Data by Using Functional Linear Mixed Model
Ran, M. & Yang, Y., 2022, In: Mathematics. 10, p. 4322Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus)