# About the Blog
Hello and welcome to the blog.
As you may have noticed, its prominent topics are Computer Science, Finance and
Productivity. Specifically for Computer Science I write about Reinforcement
Learning, Quantum Computing and Machine Learning (mostly Clustering right now),
but sometimes even classical topics such as Binary Resolution. There are also
tidbits from the Telecommunications domain here and there.
Note the litte tags in the list of posts
- at the bottom of this page you will find a legend.
As for me, I worked in Telecommunications for nearly 5 years while studying Computer Science. The main topics I did was building product modules (DOCSIS, USP, FBC impairments) and data science (we built classification/outlier models and e.g. used density based clustering extensively). My main interest then was Reinforcement Learning (together with TRAIL lab at LMU Munich we published an ALIFE paper). After that, I switched to Quantum Computing and published two more papers. I cofounded Aqarios, a spin-off out of the lab I worked in, we scaled it to 25 employees, after which I left to cofound rhome, a remote work play. If you want to find out more about my open-source technical projects, check out my Github.
If you have questions or want to contact me, send an e-mail to whodis@instancedev.com. I am especially interested in projects that combine multiple domains. For instance, if yours is medicine, law or finance, and mine is CS, maybe something interesting (either academic or business) might come out of it. In this case, do not hesitate to contact me. You can also add me on LinkedIn. Lastly, if you like you may check out a small family business I co-own, Kerzenmadl.de, and more of my companies (overpassage, alphalerts, aqarios, rhome) here.
In any case, I hope you enjoy your stay.
BIZ | Business |
PHY | Physics |
QC | Quantum Computing |
CS | Computer Science |
RL | Reinforcement Learning |
ML | Machine Learning |
FIN | Finance |
TELCO | Telecommunications |
P | Productivity |
P.S.: This is a test: niemiarytmiczny