ABOUT

I am a highly collaborative computational biologist passionate about tackling difficult biological analyses with a focus on genomics, multi-omics, statistics, machine learning, and software development. I emphasize revealing biological insight by conceptually understanding and modeling systems with multi-omics data, though I am also excited to tackle recalcitrant problems with machine learning. My methodological background is centered on big NGS data analysis (genomics/transcriptomics), mass spectrometry, phylogenomics, and discovering/optimizing genetic pathways underlying phenotypes-of-interest. My expertise has extensively been applied to microbial natural product/biological drug discovery, and I have directly worked with eukaryotes and prokaryotes. I am passionate about presenting and training, which includes invited teaching and workshop presentations for technical expertise and general botany/mycology education.

My career includes both industry and academic experience, with 5 years in natural product drug discovery analytical chemistry, followed by 6 years in computational genomics (doctoral, post-doctoral, industry consultation). My PhD in Jason Slot's lab culminated in 1) an evolution-informed natural product biosynthesis targeting platform that can recover biosynthetic pathways with increased accuracy and recovery compared to published standards in the field; and 2) a platform for automating large-scale comparative phylogenomics that serves as the genomics database for Ohio Supercomputer Center and University of Wisconsin-Madison high performance computing cluster. I am driven to address applied questions in industry, where I have unveiled cryptic biosynthetic pathways and identified elusive flavor genes in shiitake mushrooms by integrating transcriptomic and phylogenomic data. I employed another tailored genome-guided strategy to pinpoint clusters of colocalized genes that produce analogs of the psychoactive drug, LSD.