Michael Solinski

Background

About Michael Solinski

Analyzing data and understanding how systems work in their inner parts is the way to get knowledge for outperforming them. Data science and the skills needed to find models, patterns and opportunities for future acting is a key skill in the information age. Big data is yesterday. Let us extract the oil from the harvested data of the last decade. With enthusiasm for computer science since I was at school I started to learn coding when doing my school education very early. Started with doing Basic, learned C/C++, flipped to C#, forced to learn Java at the university, liked Dart, needed to learn JavaScript, played around with Go and finally used Python on machine learning projects. I have a good and broad skill in coding. I learned how to structure code in patterns and design it around features customers needed. My student job, I was working on while I was learning for my bachelor degree in systems engineering, taught me skills in requirements engineering up to designing software for longstanding products. After reaching the bachelor degree I flipped my focus to research and education at the university and worked at a faculty's department there. At this position and during my master's studies I learned how to do research and how the research community works. I focused on machine learning and soft-computing because the topic of complex and dynamic systems is of big importance for me. I am very interested in game design and how discrete systems work. I designed and coded some small games in past for a hobby and I always like to brainstorm how to optimize or describe patterns seen in systems. My analytic skills are very important to me and I like mathematics. New technologies in the computer science field are a fascinating news field for me which I follow regularly. Those topics as VR/AR, block chain or Internet of Things and cloud structures are my daily read.