David Widmann

I'm a PhD student at the IT department and the Center for Interdisciplinary Mathematics (CIM) at Uppsala University, Sweden. For my master thesis at TU Munich, Germany, I studied a delay differential equation model from biology and, since Julia is my preferred scientific programming language, I started to contribute to the development of DelayDiffEq.jl. My research interests are uncertainty quantification in machine learning and differential equations.

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Solving Delay Differential Equations with Julia

Delay differential equations (DDEs) are used to model dynamics with inherent time delays in different scientific areas; however, solving them numerically in an efficient way is hard. This talk demonstrates how the DifferentialEquations ecosystem allows to solve even complicated DDEs with a variety of different numerical algorithms.