Short Review of 2017

I have been meaning to do a quick recap of 2017 but have put it off until now. Thinking about it, I am quite surprised what happened this year and what I managed to accomplish. Of course, I have not written everything down, but mostly things that are at least in some way related to studying or computer science.

Since I am still a student, some achievements may feel a bit childish, but to me they actually do mean something.


I moved from a suburb of Wiesbaden to Kaiserslautern. The moving was prompted by a mandatory internship that is necessary to graduate from my university. I spent my time at the DFKI as a research student where I had my own project. It dealt with social media analysis in the context of companies on Twitter. I did write another blog post about it, although it has been written close to the start of it, and is not as up-to-date as I'd like.

Anyways, it was a lot of fun to actually do something that resembles research for the first time! It did also influence me in how I want to spend my time after my Bachelor's – which will be the next point.

(Under-) Graduating

I did start writing my thesis right after the internship while still staying at the research institute. Just a couple weeks shy of the year, I got the notice that I can pick up my certificate. I still did not get around to it, but I got a preliminary passing certificate already, so I know that I have passed.

Although I finished my studies for the Bachelor's, it did not mean that I am finished entirely. I turned in the thesis on the last day of the summer semester and started my Master's in the next winter semester. This left me an entire weekend to move again, as I did not continue to stay in Kaiserslautern but instead moved to Tübingen, which is where I still live and where I currently sit and write this.

In Tübingen

Now I live in Tübingen, where I continue to study. In addition to that, I managed to get ahold of a “HiWi” position at the Max-Planck-Institut here in Tübingen. I currently work with probabilistic programming languages and am preparing a small survey about it. This topic is super interesting and I am definitely happy to get to work in that direction.

As for the university courses, I have taken a couple courses that are associated with machine learning and neural networks. One discusses the ethics of machine learning, while another is a seminar about spiking and recurrent neural networks and discusses recent advances in theses areas. The third course deals with implementing parts of the research, most recently we were tasked with implementing adaptive inference1 and before that writing an Echo State Network. These are actually written without any machine learning frameworks and thus surprisingly challenging.

All in all, I really like the opportunities for learning that I have here, although I miss the teaching style and the familiarity that I know from my old university.


This has been my year. I am happy about the outcome and I am looking forward to what happens over the course of the next months. I have left some points out to not make this even longer and because some are too personal that I am not entirely comfortable sharing it. I Hope you, the reader, somewhat appreciated the read!

  1. Based on: S. Otte, T. Schmitt, K. Friston, and M. V. Butz, “Inferring Adaptive Goal-Directed Behavior within Recurrent Neural Networks,” in International Conference on Artificial Neural Networks (ICANN), Alghero, Italy, 2017. [return]

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