Chris Rackauckas: MIT, University of Maryland, Baltimore, and University of California, Irvine Alan Turing Institute, September 30th, 2018 Julia is a language for scientific computing and data science which has the simplicity of Python but the speed of C. In this talk, Chris Rackauckas introduces the Julia language from the standpoint of a scientific modeler, showing how the speed and features of Julia can be used in differential equation applications. The start of the talk introduces the Julia programming language and describes why one might be tempted to give it a try. The latter portion of the talk then shows DifferentialEquations.jl in action, utilizing Julia's generic algorithms to solve equations faster, with error bars, outputting sensitivities, and with high precision. The end of talk shows the depth of the Julia differential equation solver library by showing the simplicity of switching to stochastic and delay equation models. Together, the audience is left with a good understanding of the merits of Julia for mathematical modelers.