Chris Rackauckas
Christopher Rackauckas is an Applied Mathematics Instructor at the Massachusetts Institute of Technology and a Senior Research Analyst at University of Maryland, Baltimore, School of Pharmacy in the Center for Translational Medicine. Chris's research is focused on numerical differential equations and scientific machine learning with applications from climate to biological modeling. He is the developer of over many core numerical packages for the Julia programming language, including DifferentialEquations.jl for which he won the inaugural Julia community prize, and the Pumas.jl for pharmaceutical modeling and simulation. He is the lead developer for the SciML Open Source Scientific Machine Learning software organization, along with its packages like DiffEqFlux.jl and NeuralPDE.jl
Sessions
Scientific machine learning combines differentiable programming, scientific simulation, and machine learning in order impose physical constraints on machine learning and automatically learn biological models. Given the composibility of Julia, it is positioned as the best language for this set of numerical techniques, but how to do actually "do" SciML? This workshop gets your hands dirty.
Join via Zoom: link in email from Eventbrite. Backup Youtube link: https://youtu.be/QwVO0Xh2Hbg
You might not know all of the latest methods in differential equations, all of the best knobs to tweak,
how to properly handle sparsity, or how to parallelize your code. Or you might just write bad code. Don't you wish someone would just fix that for you automatically? It turns out that the latest feature of DifferentialEquations.jl, autooptimize, can do just that. This talk is both a demo of this cool new feature and a description of how it was created for other package authors to copy.
Dynamical modeling is arguably one of the biggest strengths of the Julia programming language. With DifferentialEquations.jl, DynamicalSystems.jl, RigidBodyDynamics.jl, ModelingToolkit.jl, DiffEqBiological.jl, Pumas.jl, etc. (the list keeps going), there are many state-of-the-art award winning projects. However, ,what's missing? What's next? Let's discuss and figure out some next steps. Join the BoF channel on Discord.