Matthew Hancock studies computational and theoretical biophysics. His research focuses on the development and application of computational methods for integrativing modeling protein structures and dynamics from diverse information sources. He is particularly interested in building and interpreting biological models through the lens of Bayesian statistics and statistical physics. His current research revolves around statistical modeling of macromolecules through the integration of diverse sources of biophysical information and predicting how to perturb the structure, function, and dynamics of these systems. He is working towards his Ph.D. in biophysics from UCSF and earned his B.A. in mathematics, computer science and economics from Vanderbilt University.