Currently I am working for an early-stage startup in Silicon Valley. I hold a bachelor's degree in Informatics (Computer Science) from Technische Universität München (TUM) with a minor in Psychology with focus on Human-Computer-Interaction from Ludwig-Maximilians-Universität München (LMU). Feel free to connect with me!
I am passionate about music so I am a heavy user of various music streaming services like Spotify and SoundCloud. Also being interested in data analysis, I started working on a side project to visualize my listening behaviour. As a first step, I created a small web app to surface the tracks you have listened to the most on Spotify, retrieved via the Spotify API.
I participated in the 2015/16 iPraktikum and it was one of the best modules I took in college. If you are going to TUM and are thinking about taking the course, do it!
From the course website:
This lab course covers mobile applications for smart devices, ranging from standalone applications, embedded systems including hardware and sensors to the design of modern interfaces for complex business applications. Students learn and apply software engineering and usability engineering techniques. This includes object oriented modeling and system design as well as the realization of graphical user interfaces, usability testing, continuous integration and continuous delivery. Real industrial partners provided the problem statements and acted as clients. 11 companies participated in the iOS Praktikum WS 15/16, each with a different problem statement and its own team. More than 100 students delivered these applications using agile techniques and communicating continuously to their clients.All of us 7 students worked together with Roche to create a prototype of an iOS app for diabetes patients connecting with Apple Watch, HealthKit, and Bluetooth blood glucose readers. In addition to being a coder, I was also the team's Modeling Representative, which means I was responsible for the creation of informal (mockups, trailer) and formal (UML) models with help of the whole team.
During my year abroad at University of Illinois at Urbana-Champaign, I worked with a data set covering four years of taxi operations in New York City, containing 697,622,444 trips.
The goal of my work was to explore the data set and propose ideas on how to predict where passengers can be found in real time.
This lightweight app shows the next departure times for S-Bahn trains in and around Munich. It includes precise real-time data.
This was a small project during my first year at university and has not been touched since then. I created this app by reverse-engineering the S-Bahn München API and learning Android as I went along. The app needs a redesign, small bugfixes, and lots of refactoring, but apart from that, the app is quite reliable. It therefore comes "as is".
Update: Looks like the API has been changed, so I need to re-reverse-engeineer the API. Since I currently do not live in Munich, this project is put on hold for now. :-( Please contact me if you need this app to be working again!