We use machine learning, high-dimensional statistics, physics driven modeling and data visualization to develop algorithms to analyze large and complex datasets in neuroscience and ophthalmology. In the retina, we aim to understand the link between the computations performed by individual cell types, the circuits they are part of and the underlying genetics and anatomy. Also, we are interested in developing interpretable, uncertainty-aware algorithms for improving clinical decision making. We collaborate closely with our experimental and clinical partners to answer fundamental questions about how visual information is processed and how degenerative diseases of the eye can be detected early.