Dr Yue is a Lecturer in the Engineering Systems and Design Pillar (ESD) at Singapore University of Technology and Design (SUTD).
Prior to joining SUTD, she worked as a postdoctoral research fellow at the Biostatistics & Modelling domain, Saw Swee Hock School of Public Health, National University of Singapore (NUS). At the same time, she taught probability and statistics course at the Department of Economics, NUS.
Her research interest includes the development of statistical and machine learning methodologies, especially in the area of biomedical sciences, economics and business. Her research has been published in various renowned international journals.
Dr Yue received her Ph.D. in Statistics from NUS and Bachelor in Mathematics and Economics (with Honors) from Nanyang Technological University (NTU).
- Ph.D., Statistics, National University of Singapore (2014 – 2017)
- B.Sc., Mathematics and Economics, Nanyang Technological University (2008 – 2012)
- Statistical Modelling
- Machine Learning
- High-dimensional Data Analysis
- Yue, M., Clapham H. & Cook, A. R. (2020). Estimating the size of a COVID-19 epidemic from surveillance systems. Epidemiology, 31(4), 567-569.
- Yue, M. & Huang, L. (2020). A new approach of subgroup identification for high-dimensional longitudinal data. Journal of Statistical Computation and Simulation, 90(11).
- Xu J., Yue, M., & Zhang W. (2019). A new approach of multilevel modelling for clustered survival data. Econometric Theory, 36(4), 707-750.
- Yue, M., Dickens, B. L, Yoong, J. S. Y., Mark, I., Teerawattananon Y., & Cook, A. R. (2019). Cost- effectiveness analysis for influenza vaccination coverage and timing in tropical and subtropical climate settings: a modelling study. Value in Health, 22(12), 1345-1354.
- Yue, M., Wang, Y., Low C. K., Yoong, J. S. Y., & Cook, A. R. (2019). Optimal design of population- level financial incentives of influenza vaccination for elderly. Value in Health, 23(2), 200-208.
- Li, J., Yue, M., & Zhang, W. (2019). Subgroup identification via homogeneity pursuit for dense longitudinal/spatial data. Statistics in Medicine, 38(17), 3256-3271.
- Yue, M., Li, J., & Cheng, M. Y. (2019). Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients. Computational Statistics & Data Analysis, 131, 222-234.
- Yue, M., Li, J., & Ma, S. (2018). Sparse boosting for high-dimensional survival data with varying coefficients. Statistics in Medicine, 37(5), 789-800.
- Teh, D. B. L., Chua, S. M., Prasad, A., Kakkos, I., Jiang, W., Yue, M., … & All, A. H. (2018). Neuroprotective assessment of prolonged local hypothermia post contusive spinal cord injury in rodent model. The Spine Journal, 18(3), 507-514.
- Yue, M., & Li, J. (2017). Improvement screening for ultra-high dimensional data with censored survival outcomes and varying coefficients. The International Journal of Biostatistics, 13(1).