I have a strong background in the physical and computational sciences, large-scale computational techniques, and software design, allowing me to model biological systems in multidisciplinary projects. In my post-doctoral research at Michigan State University, I have developed novel statistical and mathematical approaches in open-source packages PyIOmica, DigitalCellSorter, and DECNEO for time-series data analysis and discovery of the combinations of receptors from an extensive collection of single-cell RNA sequencing datasets. Currently, I am developing advanced computational approaches for quality control and downstream analysis of spatially resolved transcriptomics data. I am interested in algorithms exploring tumor growth, development dynamics, and gene expression regulation. I enjoy researching complex processes in the tumor microenvironment to help understand cancer biology questions through the analysis of Next Generation Sequencing data. I help automate and standardize data analysis workflows by creating Nextflow-based computational pipelines using state-of-the-art computational biology methods. My objective is to continue biostatistics analysis, develop bioinformatics algorithms and encapsulate these novel methods in reliable software for personal and HPC systems.
