Current Research Interest 

Axel Martin is currently pursuing a PhD degree at New-York Univeristy Langone, in Biostatistics focusing on causal inference. His primary research interests focus on the prediction and stratification of survival of late-stage cancer patients as a function of their genomic profiles. He develops flexible ensemble statistical learning methods to create clinically meaningful risk groups that can reveal groups at particularly high risk (OncoCast: https://github.com/AxelitoMartin/OncoCast). Axel’s focus on genomic data also led him to develop, in collaboration of other biostatisticians, robust frameworks for MSKCC genomic data (IMPACT) processing, visualizations and analysis. More recently he has been working with the GENIE statistical team of the Biostatistics department at MSKCC. They develop methods for data processing of clinico-genomic datasets of multiple cancer centers in North America. Axel has been focusing on multi-state modeling and causal inference methods to associate the various treatments given to late-stage lung adenocarcinoma patients and their clinical outcomes.