My research has historically focused on technology development and quantitative investigations of evolutionary dynamics, interaction network dynamics, and epistasis. As a postdoc working with Mark Siegal at NYU, I developed a high-throughput microscopy assay that monitors variable protein expression, morphology, growth rate, and survival outcomes of tens of thousands of cell microcolonies simultaneously. Since then, I have been developing technologies that use highly efficient DNA recombination to develop new capabilities and ask new questions. Working as a postdoc with Gavin Sherlock, I developed a genomic barcoding system in yeast and used it to track millions of lineages simultaneously as they evolve. This effort pioneered an emerging field devoted to barcode-based cell lineage tracking in lab strains, pathogenic infections, normal human tissues, and cancer. As an academic lab head, my group extended this technology into a genomic double barcode system capable of tracking lineages through mating events in yeast. We used this system as an interaction sequencing platform that is capable of generating and simultaneously measuring large numbers of interactions between proteins, gene knockouts, mutations, or genotypes. My lab used these technologies to explore how interaction networks change across environments, drug perturbations and genotypes, and the genotype to phenotype map. At Stanford, my academic group also developed recombination-based technologies for multiplexed DNA assembly and plasmid sequencing in E. coli. We have recently spun these technologies out to form a company, BacStitch, and I have left academia to serve as the CSO. At BacStitch, we aim to develop a composable DNA engineering platform that streamlines and scales the ability to write, cut, copy, paste, save, and share DNA “code”. I have expertise in the development of genetic tools, yeast genetics, bacterial genetics, barcode and amplicon sequencing, experimental evolution, analysis of large data sets, metrology, development of computational tools, and network and evolutionary theory.