Alexander Ratzan is a Ph.D. candidate in the Neuroinformatics Lab at NYU advised by Erdem Varol where he develops novel, efficient, and scalable methods to analyze neural and genomic data. His research is focused on uncovering the relationship between genetics and brain connectivity patterns, an avenue that can impact how we treat brain disorders and shed light on the fundamental principles of biological neural networks. He approaches this research problem by applying techniques from statistical machine learning, graph-theory, and deep learning to large genomic and neuroimaging datasets. His research is supported by the NDSEG fellowship. More broadly, he is curious about the intersection of natural and artificial intelligence and how we can improve AI systems to benefit human health.