Applies bioinformatics and machine learning algorithm methodologies to explore high-dimensional genomic datasets with an emphasis on single-cell and survival analyses.
Over the past ten years, I specialized myself in big data analysis (i.e., Machine-Learning) applied to Genomics, Semantics and Next Generation Sequencing (NGS) data linked to single-cell and cancer research. I obtained my PhD in Computational biology and Evolutionary Genomics at Ecole Centrale de Lyon (Lyon University), France. My previous research at the Cancer Center of the University of Hawaii and the Center for Epigenomics (UCSD) elaborated advanced analytical methods and workflows for single-cell, multi-omics, and survival datasets. My current work involves working with single-cell ATAC-Seq and RNA-Seq datasets and developing new statistical methods for inferring epigenomics regulation.