Hey there, internet voyager!
I’m Sander ( he / him ) — a programmer and trained data scientist,
poking at the language design and user interface dragons
with the sticks of category theory and topology.
🔭 Right now
I’m working on a long-term research project, designing a different type of programming language. It’s not your-favourite-language-but-with-a-twist, and it’s not a connect-boxes-with-wires thing. Behind the scenes, it’s based on shapes, patterns, types, categories, and proofs.
I’d like to make computer programming more accessible and friendly, so that you too can code. In the meantime, maybe we can make programming safer and a bit more pleasant for the professional developers.
I’m open to opportunities to work with kind and compassionate folk on fun problems, preferably in Haskell, or Elm, or something similar.
Remote ( I’m on GMT +3 ) or relocation to Deutschland.
A few ground rules, though:
Do no evil. Is your business exploiting, manipulating, or hurting people? No, thanks. Same thing goes for the environment.
Riddle me this. I’m not interested in solving brainteasers on the spot — especially on a whiteboard. I realise that hiring people is hard, but this is not the way.
👐 Open source
I try to post my projects on GitHub with liberal licenses.
Some of my recent projects:
A colourful animated clock in polar coordinates built in Elm. Complex animated SVG paths and colour interpolation galore.
A write-up of the mathematics behind the “cubehelix” colour space.
A utility to generate Wireguard configurations for the Mullvad VPN service written in Haskell.
I still maintain sandydoo/ember-google-maps from my days as an Ember.js developer. It’s probably the most, if not the only, pleasant way of working with Google Maps, and is consistently in the Top #100 of Ember addons.
MSc Applied Statistics, University of Oxford, 2016
What’s “Applied Statistics”? It’s statistical theory, the mathematics of uncertainty, applied to data: from data visualisation and linear regression, all the way to computationally intensive Bayesian methods and machine learning.