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Biography
+ A self-motivated statistician with a strong background in Bayesian statistics, some research-oriented experiences in the clinical trials and machine learning.
+ An excellent team player and multi-tasking ability as evidence by completing many projects on
- Phase III clinical trials: 1 project about interim analysis on oncology in FDA summer internship.
- Pre-clinical trials: 3 projects, 1 published paper as a co-author, and 1 presentation about PK
and PBPK modeling to predict withdrawal time on food animal medicine;
- Bayesian statistics: 3 projects in my dissertation with 1st project published in Computational Statistics, two presentations in 2019 and 2020 JSM on Bayesian high-dimensional variable selection.
- Machine learning: 2 projects in M.S. thesis with 2 published papers about the time series
forecasting using an ensemble approach based on SVM, neural network and cuckoo search.
+ A quick learner grasping many modeling skills through these projects above: Bayesian variable selection, MCMC, survival data analysis, Experimental Design, linear mixed model, Cox PH model, interim analysis, ANOVA, PK/PBPK, time series, GLM,LASSO, etc;
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Employment (3)
Education and qualifications (2)
Works (7)
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