Research Areas: Microbial ecology; nutrition; machine learning; ecological and evolutionary dynamics; omics data analysis; virus-host interactions; quantitative biology
Motivated by models in statistical physics, math, ecology, epidemiology, and machine learning, I am broadly interested in modeling microbial communities with cross-feeding interactions and predator-prey interactions. I study the ecological and evolutionary dynamics influenced by those interactions. On the practical side, I focus on predicting metabolomic profiles based on microbiome compositions and dietary compositions via both mechanistic models and machine learning methods and then leveraging those methods to infer interactions between microbes, metabolites, and dietary compounds.