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Chris is the VP of Modeling and Simulation at Julia Computing, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP. For his work in mechanistic machine learning, his work is credited for the 15,000x acceleration of NASA Launch Services simulations and recently demonstrated a 60x-570x acceleration over Modelica tools in HVAC simulation, earning Chris the US Air Force Artificial Intelligence Accelerator Scientific Excellence Award.

Christopher Rackauckas's Projects

advancedhmc.jl icon advancedhmc.jl

Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms

approxbayes.jl icon approxbayes.jl

Approximate Bayesian Computation (ABC) algorithms for likelihood free inference in julia

aqua.jl icon aqua.jl

Auto QUality Assurance for Julia packages

autumnschool2023 icon autumnschool2023

Course material for the autumn school in scienfic machine learning 2023

awesome-neural-ode icon awesome-neural-ode

A collection of resources regarding the interplay between ODEs, dynamical systems and neural networks

bluestyle icon bluestyle

A Julia style guide that lives in a blue world

catlab.jl icon catlab.jl

A framework for applied category theory in the Julia language

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