Technology Experience

Martin and technology

Next to music and piano and languages and philosophy Martin has always been interested in Technology and Computer Science too. On this page some of the experience in technology and information technology of Martin Kaptein is listed. Martin also has experience working in the field.

Martin Kaptein cover picture

Martin Kaptein


Martin Kaptein finished the general qualification for university entrance (=Abitur) in Germany (Gymnasium). Thus, he has an advanced school-leaving certificate with splendid marks. Martin has both a bachelor as well as a master degree, but in the field of classical piano.

IT experience

Familiar with following technologies

  • JavaScript
  • Wordpress (PHP and MySQL backend)
  • Humhub (PHP), used to run a social network based on it
  • KaiOS Webapp building
  • Android custom roms
  • Python development
  • Machine learning (Python)
  • git, docker, Travis CI, Netlify
  • Linux (Bash, architecture)
  • Golang
  • Hugo (Static Site Generation Framework)
  • C (basic)
  • System Administration (sysadmin) Experience with VPS (Linux)
  • Experience with Gemini protocol and running a Gemini server
  • Google Firebase
  • XMPP protocol (setting up servers and clients)
  • Networking (DDWRT), creating mesh wifi networks, etc.
  • Microsoft Dynamics Navision (NAV) programming experience in the context of accounting
  • Nextcloud full manual installation, setup and administration (nginx)
  • Full manual Arch installation



Here, on his website, Martin writes a blog, in which regularly dives into deeper topic, in very great detail. This blog is a good representation of all the (Information-)Technology skills Martin possesses.

Blog highlights:

And much more! Seriously, check out the blog.

Bachelor research

During his studies at the ArtEZ conservatory (bachelor) in Zwolle, The Netherlands, Martin made an interesting connection between the worlds of music and of information technology, in his choice of his bachelor research topic: Can J.S. Bach be immitated using machine learning?

A link to this paper can be found here. The referenced codebase (Python) resides on Github and can be found here.

Github highlights

Some of the stuff I made / I worked on / Projects. Contains only links to Github.

Besides all the above, I am interested in:

  • Science
  • Physics
  • Math
  • Crypto

I am a musician and participate in various non-profit organizations. Also, I like to read.


You can contact me here.