Scott Gigante

Scott’s research is focused the development of methods in deep learning and graph signal processing to understand the structure of single-cell genomics data, especially single-cell RNA sequencing data. He is particularly interested in how to make the most of many high-resolution noisy measurements, and how manifold learning techniques can facilitate this understanding.