Check out our latest research in Publications.

Understanding Cellular Function Through Molecular Interactions
We develop machine learning approaches to map the molecular interactions that shape microbial cellular function. By studying molecular interactions between proteins, nucleic acids and ligands, we aim to uncover how molecular recognition gives rise to gene regulation, metabolism, and cellular phenotype.
Machine learning for microbial biochemistry
We develop machine learning approaches that learn from the immense diversity of microbial genomes to discover new biochemical functions and design new ones. Our work spans enzyme and pathway discovery, generative design of biosynthetic systems, and models that reason over the genomic context in which molecular functions evolved.
Microbial technologies for human and environmental health
We translate discoveries in microbial biology into new capabilities for human and environmental health. From natural products and sustainable biomanufacturing to microbial therapeutics, we aim to engineer biological systems that address important challenges in medicine, industry, and the environment.
Contextualizing biological function with microbial ecology and evolution
We use large-scale genomic data and machine learning to study how microbial functions emerge, diversify, and spread across environments. By linking sequence variation to ecological context, we aim to uncover the evolutionary forces that shape microbial adaptation, community interactions, and biochemical diversity.