I'm Bjorn Shockey, a PhD student in Systems, Synthetic & Physical Biology at Rice University, working across the Silberg and Stadler labs. I aim to deploy engineered microbes reliably within complex microbiomes toward enabling ecological recovery, agricultural improvement, and therapeutic advancement. In my PhD, I am studying how gene transfer behavior varies across abiotic and biotic conditions and the downstream effects on microbial fitness at the community scale.
Successes like AlphaFold underscore the transformative potential of ML/AI for forecasting across complex parameter spaces, when trained on abundant and high-resolution data. Researchers often face a tradeoff between data quantity and resolution, since combining both remains cost-prohibitive. I hypothesize that this tradeoff limits the effectiveness of building ML/AI models for predicting horizontal gene transfer in a community. My current project aims to improve resolution while maintaining throughput of gene transfer measurement, using our ribozyme barcoding technology developed at Rice University.
Please reach out — I am always happy to discuss science!