Bella Vakulenko-Lagun

I received my Ph.D. degree in Statistics from the Hebrew University of Jerusalem in 2016 and joined the Department of Statistics at The University of Haifa in 2019. Prior to that I was a postdoctoral researcher at the Department of Biostatistics, Harvard School of Public Health.

Causal inference; Survival analysis and multi-state processes; Selection bias and missing data

My current research focuses on development of methods that correct for biased sampling and missingness in time-to-event data with competing risks and multi-state structure. In general, I am interested in problems that aim to answer important scientific questions motivated by real life (especially related to public health), questions that pose statistical challenges and lead to collaboration with other disciplines. 

• B. Vakulenko-Lagun, M. Mandel, R.A. Betensky (2019). Inverse probability weighting methods for Cox regression with right‐truncated data. Biometrics, DOI: 10.1111/biom.13162
• B. Vakulenko-Lagun, J. Qian, S.-H. Chiou, R.A. Betensky (2019). Nonidentifiability in the presence of factorization for truncated data. Biometrika, 106, 3, pp.724-731
• B. Vakulenko-Lagun, M. Mandel, Y. Goldberg (2017). Nonparametric estimation in the illness-death model using prevalent data. Lifetime data analysis, 23 (1), 25-56
• S.D. Oman, B. Vakulenko-Lagun (2009). Estimation of sill matrices in the linear model of coregionalization. Mathematical Geosciences, 41 (1), 15-27