Ryan Poplin

From GSA

Ryan Poplin joined the Broad Institute in October of 2009 and has developed several methods such as Base quality score recalibration and Variant quality score recalibration. Previously, Ryan was a graduate student in the laboratory of Tai Sing Lee studying how brains perform Bayesian inference during visual perception. And before that, Ryan worked at MIT Lincoln Laboratory where he attached lasers to airplanes and made beautiful 3D maps of cities and forests.

Ryan holds a Master of Science in Neural Computation from Carnegie Mellon University (2009) and a Bachelor of Science in Computer Science and Mathematics from Rose-Hulman Institute of Technology (2004).