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mstksg

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jle / mstksg / Lê Anh Khoa: Computational physicist & Haskeller, PhD

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

GitHub Sponsors Profile

Hi! My name is Justin.
I did my PhD in Computational & Data Science, doing some pretty heavy numerical analysis and machine learning work in the process. But I also love the safety, maintainability, denotative semantics and guided development process that comes with working in Haskell. So, I'm committed to help bringing all of the benefits of Haskell -- type-safety, static verification, type-driven development, denotative frameworks, and fearless refactoring -- to the world of numerical analysis and machine learning. You might have even read my blog where I explore these topics with an educational goal. Along the way, I hope to do my own part in growing the Haskell ecoystem as well!
The Projects You're Supporting
I keep a dashboard of my open source projects in Haskell, and their statuses. But my projects tend to fall into one of a few camps:

Numerics & Data:

backprop, backprop-learn (in-progress)
mutable
hmatrix-vector-sized, hmatrix-backprop
emd, wavelets (in-progress)
hamilton
interactive-plot
bins
opto (in-progress)

Type-Safety & Design

nonempty-containers
functor-combinators
servant-cli
one-liner-instances
list-witnesses, functor-products
typelits-witnesses
decidable
lens-typelevel

As you can see, most of my projects help push applications of what is possible in Haskell in terms of numerical analysis and data science as well as type safety and maintainability.
What You're Sponsoring
Sponsor me at any tier and you help allow me to devote more of my time to writing and maintaining open source libraries, developing and finishing new ones, and also to continue publishing new material on my educational blog. The stresses of life are real, and every cent helps :) Also, do feel free to donate or sponsor if you just feel like showing appreciation -- every gesture means a lot to me, and really helps encourage me in what I do.

Featured Works

mstksg/backprop

Heterogeneous automatic differentiation ("backpropagation") in Haskell

Language: Haskell - Stars: 180
mstksg/hamilton

Simulate physics on generalized coordinate systems using Hamiltonian Mechanics and automatic differentiation. Don't throw away your shot.

Language: Haskell - Stars: 139
mstksg/inCode

Source for personal blog.

Language: Haskell - Stars: 76
mstksg/advent-of-code-2018

Advent of Code 2018 Solutions (Spoilers!)

Language: Haskell - Stars: 83
mstksg/auto

Haskell DSL and platform providing denotational, compositional api for discrete-step, locally stateful, interactive programs, games & automations. http://hackage.haskell.org/package/auto

Language: Haskell - Stars: 180
mstksg/backprop-learn

Combinators and types for easily building trainable neural networks using the backprop library

Language: Haskell - Stars: 33
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