Open Source

Some of my open-source contributions include:

• SciML - Scientific Machine Learning ecosystem in Julia
  • I have contributed to various packages in the ecosystem including LinearSolve.jl, SciMLBase.jl, Integrals.jl and ModelingToolkit.jl.
• JuliaGaussianProcesses - Gaussian Processes ecosystem in Julia
  • AbstractGPs.jl - Abstract types and methods for Gaussian Processes.
  • KernelFunctions.jl - Julia package for kernel functions for machine learning
• Bijectors.jl - Implementation of normalising flows and constrained random variable transformations
• PyMC4 - High-level interface to TensorFlow Probability

I have successfully completed the following open source programs under wonderful supervision for which I am eternally grateful.

• Google Summer of Code (GSoC) 2018
  • with PyMC
  • worked on TensorFlow prototype of PyMC4
  • mentored by Colin Carroll - PyMC Team
• Julia Season of Contributions (JSoC) 2019 with TuringLang
  • with TuringLang
  • worked on Bijectors.jl - Flexible transformations for probability distributions
  • mentored by Kai Xu - University of Edinburgh
• Google Summer of Code (GSoC) 2020
  • with TuringLang
  • worked on JuliaGaussianProcesses
  • mentored by
    • Will Tebbutt - MLG, University of Cambridge
    • David Widmann - Uppsala University
    • Théo Galy-Fajou - TU Berlin