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Pier Palamara is an expert in Statistical Genomics who received his PhD in Computer Science from Columbia University in 2014. He has worked as a postdoctoral fellow in statistical population genetics at the Harvard Chan School of Public Health and the Broad Institute of MIT and Harvard. Prior to that, he obtained his bachelor's and master's degrees from Sapienza University in Rome and completed a master's degree at Columbia University with a focus on artificial intelligence, machine learning, and cognitive robotics. His research interests lie at the intersection of statistics, computer science, and genetics, where he develops methods for new types of analyses in statistical population genetics. He is particularly interested in problems involving modeling and inference from large datasets. Specific areas of his research include studying evolutionary parameters of the human genome such as natural selection and mutation rates, reconstructing past demographic events using genetic data, and investigating the heritability and genetic architecture of complex traits, including the nature versus nurture debate.
Harvard Chan School of Public Health, Broad Institute of MIT and Harvard • Cambridge, MA
Worked on statistical population genetics.
Department of Politics and International Relations - Higher Level English requirement.