Hi! 👋🏼
I am Philipp. I've been working as a research associate and doctoral student at TU Dresden since December 2021. Here I am responsible for the development of the PrioBike app and do research on the intelligent integration of cycling and infrastructure data. Previously, I was a tutor in the Software Technology and Software Practicum courses for several years. Since 2016, I have also been implementing freelance software projects for clients. Here are a few projects I have worked on:
Pacebox
iOS App
INLOOP
E-Assessment
jsExam
Enrollment Tool
ordered.online
React Native App
Manni
iOS App
☕️💻.ws
Blog
PeerBridge
Blockchain Messenger
INLOOP Gamified
Gamification
3Dify
iOS App
Benno Netzwerk
Social Network
Watchapp
WatchOS App
Salut
iOS and MacOS App
Vokabular
iOS App
NO2
iOS App
OUTPUT.DD
iOS App
fragenautom.at
E-Learning
Lautstärke
iOS App
Toothpaste
iOS App
MDR Koalitionspoker
Online Game
Neural Greenscreen
Machine Learning
Gitgraph
Data Science
Carnivora
Instagram Bot
victoria-scheer.de
Homepage
Apps.
I developed my first iOS app in 2016. Since then, I've added numerous others - including Android apps. Today, I have over 25,000 downloads and a large portfolio of technologies.
Tech Stack
Cross-Platform: Flutter, Dart. Native: Swift (UI), Kotlin. Web: SCSS, Yarn & Webpack, TypeScript. CI/CD: Fastlane, GitHub Actions.
ML.
Machine Learning is an important solution concept for complex problems. For example, I have already used ML to recognize the transportation mode by porting to smartphones, or to reconstruct my own voice by transfer learning. ML is also a central part of my research.
Tech Stack
Data Analysis: Jupyter, Matplotlib, Pandas, Numpy. Training of Models: TensorFlow (Keras), SciKit-Learn. Porting: TensorFlow Lite, CoreML. Hardware: Google Colab.
Tech Stack
Data Analysis: Jupyter, Matplotlib, Pandas, Numpy. Training of Models: TensorFlow (Keras), SciKit-Learn. Porting: TensorFlow Lite, CoreML. Hardware: Google Colab.
Big Data
Machine learning means understanding data. My research focuses on how data can be used to generate added value for app users.
Big Data
Machine learning means understanding data. My research focuses on how data can be used to generate added value for app users.
Cloud.
I primarily work with backend architectures of containerized microservices to maximize extensibility, scalability, and robustness.
grep "Advanced Experience" tech.stack
Containerization: Docker.
Deployment: Docker Compose.
Monitoring: Prometheus, Grafana, Sentry.
CI/CD: GitHub Actions, Watchtower.