Research Interests

Statistical genetics
Machine Learning
Artificial Intelligence

Pier Francesco Palamara

Short Bio

I obtained my "laurea di Primo Livello" and "Laurea Specialistica" (B.S. and M.S. degrees) from Rome's Sapienza University, and a M.S. degree from Columbia University (Dec. 2009). Until then, the focus of my studies/research was on artificial intelligence, cognitive robotics and machine learning.

I defended my Ph.D. thesis "Population genetics of identity-by-descent" at Columbia University in October 2013. My Ph.D. advisor was Itsik Pe'er, and I mainly worked on computational models for population genetics.

I am currently at the Harvard School of Public Health and the Broad Institute of MIT and Harvard, working on statistical genetics problems as a post-doctoral researcher in Alkes Price's group.


See my list of publications, or Google Scholar profile.


Some of the code I wrote for my projects is available at my Github page
  • ARGON - a fast genome simulator sampling from the discrete time Wright-Fisher model (see this paper). The simulator can efficiently output IBD segments.

  • IBDMUT - inferring mutation and gene conversion rates using IBD (see this paper).

  • DoRIS - a tool for demographic inference based on shared IBD haplotypes (see this paper).



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