The Faculty


Machine learning approaches used to quantitatively model immune function

Research interests

The Riesenfeld Group develops and uses machine learning approaches to quantitatively model immune function. We leverage large-scale, systematic genomic data to identify the key cellular components, molecular circuitry, and dynamics underlying tissue-based immune responses. By combining experimental and computational analysis, the group aims to understand the factors that drive an immune response towards tolerance versus inflammation, and to predict how manipulations may alter the response.

Selected publications

Link to publication list