Daniel is a Graduate Student in the Neale lab. He is developing a method based on the Maximum Entropy Principle to construct multilayer SNP-phenotype networks given GWAS data. He is generally excited about how simple yet powerful variational principles, such as Maximum Entropy, can be developed, extended and applied to problems in biology and medicine. Daniel graduated from Yeshiva University in 2016 with a Bachelor’s in Mathematics and Physics, and is on leave from medical school at Stony Brook University to focus on research and to pursue a PhD. For more information, check out his website.