I am a computational biologist with a deep background in molecular biology and statistical genetics, currently advancing cancer biomarker discovery at Exosome Diagnostics (Bio-Techne). My work bridges state-of-the-art experimental data, bioinformatics, and machine learning to support research and development programs for novel diagnostic signatures, with a focus on exosomal biomarkers, RNA-seq, and multi-omic integration.

Previously, at Boston Children’s Hospital, I led computational efforts in the Sampson Lab to uncover the genetic basis of kidney disease, integrating GWAS, eQTL mapping, single-cell transcriptomics, and causal inference. My PhD research at Tufts focused on miRNA:mRNA targeting and nephrotoxicity, laying a strong foundation in high-throughput functional genomics.

At Exosome Diagnostics (Bio-Techne), I focus on making sense of complex RNA-seq and multi-omic datasets to support biomarker discovery. I’ve built and maintained scalable Nextflow pipelines, developed cross-validated ML models for omics classification, and created internal tools for QC, feature selection, and result reporting. I’m passionate about making robust, reproducible bioinformatics workflows that deliver real-world biological and clinical impact.