Personal Biography

I received my PhD in computer science from Columbia University in 2014. I then spent three and a half years working on statistical and population genetics as a postdoctoral fellow at the Harvard Chan School of Public Health, and at the Broad Institute of MIT and Harvard. Prior to that, I obtained a bachelor’s and a master’s degree from Rome's Sapienza University, and a master’s degree from Columbia University, all in computer science with a focus on artificial intelligence, machine learning, and cognitive robotics.

Research and Teaching

My research is at the intersection of statistics, computer science, and genetics. I develop new statistical and machine learning methods to enable novel analyses in population and disease genetics, with a particular interest in problems that involve modeling and inference in large datasets. Specific areas of research include studying evolutionary parameters in the human genome (natural selection, mutation/recombination rates), reconstructing past demographic events using genetic data (migration, expansion/contraction of populations), studying the heritability and genetic architecture of complex traits (nature vs nurture), and detecting disease-causing variation in the human genome.

I teach students in maths, covering first and second year probability, statistics, and algebra, and a course in statistical machine learning at the Department of Statistics and other doctoral training centers.

Representative Publications

P. Palamara, J. Terhorst, Y. Song, A. Price. High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability. Nature Genetics, 2018.

P. Palamara. ARGON: fast, whole-genome simulation of the discrete time Wright-Fisher process. Bioinformatics, 2016.

P. Palamara, et al.. Leveraging distant relatedness to quantify human mutation and gene conversion rates. The American Journal of Human Genetics, 2015.

Genome of the Netherlands Consortium. Whole-genome sequence variation, population structure and demographic history of the Dutch population. Nature Genetics, 2014.

P. Palamara, T. Lencz, A. Darvasi, I. Pe'er. Length distributions of identity by descent reveal fine-scale demographic history. The American Journal of Human Genetics. 2012.