I develop predictive mathematical models of cells, in the intersection of machine learning, synthetic biology and automation, as the founder of Berkeley Lab's Quantitative Metabolic Modeling group, Deputy Vicepresident for JBEI's Biofuels and Bioproducts Division and Learn colead of the Agile BioFoundry.
I am a physicist working in synthetic biology. How did I get here?
I started my Ph. D. in condensed matter physics, but very early on became fascinated by emergent properties in biology, like e.g. the species area rule. Hence, I decided to work on metagenomics for my postdoc at the Joint Genome Institute, obtaining blueprints of microbial community metabolism. Irked by the difficulty of creating predictive models for microbial communities, I focused on an easier target: pure cultures for which we have the tools to change their genome. This took me to my current position, developing predictive models for biological systems to produce renewable biofuels and other products. You can read the expanded version of this story here.