Hey! 👋🏼

Daniel (my colleague) and I attended ScaDS.AI's summer school on Big Data and AI. Over the course of several seminars, we learned a lot from new and exciting research fields, and met lots of cool people. 🔗 Read more

In 2021 I first joined the OUTPUT team as a student and rebuilt the OUTPUT app from the ground up for iOS. For OUTPUT 2023, we made a radical choice and decided to rebuild the event‘s app in Flutter to cut our future development efforts drastically. This was only possible thanks to the talented team of four students that I had the chance to guide. Over the semester, we planned and realized the rebuild and successfully deployed our app at OUTPUT 2023. Looking forward to OUTPUT 2024! 🔗 Read more

PrioBike was nominated for the German Cycling Award 2023, and got the third place! 🔗 Read more

Selecting Resource-Efficient ML Models for Transport Mode Detection on Mobile Devices 🔗 Read more

Matching Traffic Lights to Routes for Real-World Deployments of Mobile GLOSA Apps 🔗 Read more

The 3Dify app generates disparity maps for portrait images. On devices without that capability, it utilizes a machine-learning model for monocular depth interpretation. Based on the disparity maps, a technique called parallax occlusion mapping is applied to generate a 3D-like effect. Parallax occlusion mapping is utilized in video games to simulate 3D surfaces without having to generate any additional vertex geometries. The 3D process is calculated entirely in the GPU's fragment shader. 🔗 Read more

In many use cases of smartphones, such as activity recognition, we need machine learning models to solve the underlying problem. However, machine learning models can grow vastly under certain circumstances and consume many computational resources. Thus, it is crucial to consider the resource factor in the model development. In my Diploma thesis, I found for human activity recognition models that many research papers primarily focus on model accuracy and lack deeper considerations of resource consumption. I developed a 3-step engineering process for machine learning models that uses resource-enhanced grid search to identify a model configuration with the best resource-accuracy-tradeoff. In my talk at OUTPUT.DD 2022, I will outline my process and learning outcomes, and discuss why porting and engineering machine learning models for smartphones is still an ongoing problem. 🔗 Read more

I am excited to announce that I joined TU Dresden as a research associate and will work on the PrioBike project, which implements a smart velomobility app for cyclists in Hamburg. The planned time horizon is to finish my Ph.D. thesis together with the project by the end of 2024.

Together with my colleague Felix Kästner we developed a proof-of-stake blockchain in Go. The goal of this project was to learn more about blockchain - and what would be a better way than implementing one yourself? We deployed the blockchain in a small scale via Heroku, and were able to synchronize transactions to the blockchain from our mobile apps. The hardest part was getting the P2P networking right. 🔗 Read more

In this project, I wanted to challenge myself a bit more and develop a low-level camera interface that utilizes a machine-learning model for image segmentation to replace the background. The plugin can be plugged into any application since it acts as a virtual camera wrapper around the system's camera. The project is quite prototypical but was worth the laughs 😃

To aid learning for exams, I wrote my own questionnaire platform: fragenautom.at - It is available for free and provides unofficial questionnaires for the TU Dresden courses Distributed Systems, Computer Vision, Machine Learning, User Interface Engineering and more.

I supported the young author Victoria Scheer with the creation of unique covers. The fantasy-oriented books are matched by the special style we developed for this. The covers were created with 3D visualization or hand drawn and then stylized with neural networks. We used specific components of the Inception model to create a mystical mood.

I had the opportunity to collaborate with the MDR trainees and contribute to the development of the "MDR Koalitionspoker" game. It was a fulfilling experience to work on this browser-based game, where players negotiate coalitions and advocate for their party's positions. Whether playing with real individuals or a computer opponent, the game offers an engaging political simulation. As the external programmer, I assisted in bringing the vision to life. For more information, see: https://www.mdr.de/nachrichten/sachsen/politik/landtagswahl/video-320684.html

I had the opportunity to develop a social network for a client who wanted to stay in touch with other alumni, and had the idea to establish a platform for staying in touch even after graduation. The app features social features similar to Jodel. I implemented the app using Java (Android) and Swift (iOS), and utilized a Google Firebase backend.

I started to work as a tutor for Software Technology (seminar and lab) at TU Dresden. This job runs in parallel with my job as a software developer at INLOOP.

I started to work at TU Dresden chair of software technology as a backend and frontend developer for INLOOP, an e-learning platform.