Software Engineer with focus on machine learning, distributed systems and a little bit of IT security. In addition, I am quite experienced with mobile app development.
For machine learning projects I use Python with Tensorflow or PyTorch. Sometimes in combination with Jupyter.
I like Swift and Kotlin and have experience in mobile app development as well as macOS, Linux, and Windows.
My daily friends are git, TDD and CI. I have experience with Docker, Jenkins as well as the Atlassian software development tools.
In 2015 we developed an Apple Watch application for activity and exercise recognition for eGym during the MPD course at CDTM. For the recognition I ported the Gesture Recognition Toolkit to the Apple Watch OS and we trained a Dynamic Time Warping model to classify movements (accelerometer values).
In 2014 I developed an open source library for my bachelor thesis to access USB mass storage devices from Android phones and tablets without rooting your device. This included impleneting the SCSI command set as well as FAT32 in Java. The library is used in a couple of other projects, like AnExplorer, and in ongoing development.
In 2015 we developed an Industry 4.0 showcase called AgileFactory together with the software engineering faculty at TUM and T-Systems Innovation Center.
In 2015 we trained an AlexNet using Caffe to classify German Traffic Signs.