I am a research biostatistician at Memorial Sloan Kettering cancer center (MSKCC) in New-York city in the department of Epidemiology & Biostatistics.

My primary work focuses on the development of complex methods for survival prediction and stratification in high-dimensional genomic datasets of various cancer cohorts. Over the course of my time at MSKCC I have developed some open-source R packages to perform ensemble learning for left-truncated genomic survival datasets, including some online visual tools for exploration, validation and individual predictions.

This focus on genomics also lead me to develop tools to streamline data retrieval and processing into an analysis ready format, building pipelines enabling beginners to perform complex analytics in a very accessible way.

I also specialize in R Shiny application development both for research and educational purposes in order to render in a more user friendly way complex statistical results. More recently I developed interest in making use of causal inference methods to optimize sequential treatment rules for cancer patients using time on treatment and genomic data.

Download my resumé.