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vaibhavdixit02

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Funding Links: https://github.com/sponsors/Vaibhavdixit02

GitHub Sponsors Profile

I am a Software Engineer at Julia Computing based out of Bengaluru, India. I am involved in maintaining and developing packages for Scientific Machine Learning in the SciML organisation. So far my primary contributions have been to the parameter estimation tooling, DiffEqParamEstim.jl, DiffEqBayes.jl, DiffEqFlux.jl and GalacticOptim.jl and I also maintain the GlobalSensitivity.jl package for global sensitivity analysis. Additionally I am also involved in expanding Julia's EHR integration capabilities and contribute to packages in the JuliaHealth organisation like SMARTAppLaunch.jl and EHRAuthentication.jl. I would appreciate sponsorship to continue devoting time to my current projects and also expand my contributions to more projects. See you around!

Featured Works

JuliaHealth/EHRAuthentication.jl

Helper code for authenticating to various electronic health record (EHR) systems

Language: Julia - Stars:
SciML/Optimization.jl

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable i…

Language: Julia - Stars: 776
SciML/DiffEqBayes.jl

Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning

Language: Julia - Stars: 124
SciML/GlobalSensitivity.jl

Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia

Language: Julia - Stars: 57
JuliaHealth/SMARTAppLaunch.jl

Implementation of the SMART App Launch Framework for building SMART on FHIR applications

Language: Julia - Stars: 2