Transitioned to AI-based AD software stack (end-to-end). - Executed data engineering tasks, including preprocessing, filtering, transformation, and conversion of data for training datasets used in AI-based behavior planning and high-definition (HD) mapping.- Developed and deployed an automated data filtering system to extract small snippets from our data lake, facilitating model training.

- Developed tools for performance evaluation and inspection.- Optimized code, improving performance and reducing processing time. - Established CI/CD/CT pipelines in a new Azure DevOps environment. - Migrated tools to Bazel build system.

Team: Digital Testing Feature Team / Sensor Fusion - Led a cross-functional feature team and managed agile project planning. - Enhanced automated driving development and verification with efficient CI/CD processes. - Unified fragmented tooling environments across L4 AD teams.

- Designed project-wide testing and evaluation strategies for L4 AD. - Integrated sensor fusion testing into the broader project framework. - Fostered international collaboration through bi-annual workshops.

- Developed comprehensive evaluation and testing strategies for sensor fusion. - Implemented a robust evaluation framework and performance metrics, enhancing system performance and accuracy insights. - Planned and led international workshops and hackathons, fostering collaboration and innovation.

Projects:- Integrated new data sources into advanced HMI for L4 Autonomous Driving. - Designed and implemented an evaluation framework for state estimation algorithms, increasing perception system accuracy. - Supported CES 2017 demo team, boosting company visibility with VR experiences.

One (worth to mention) of several projects during the time as a researcher at the university. - Designed and implemented a real-time image processing system for an autonomous driving model car.- Developed a model based Lane-Keeping-Assistant and Lane-Tracking-Assistant for an autonomous driving model car.Motivation: The main motivation in this project is the development of an autonomous driving model car. This development should secure the participation at the "Carolo Cup". This cup contains two dynamic disciplines, the autonomous parallel parking and the autonomous drive on a track without obstacles.

- Designed a prototype for an adaptive „recommendation service“ HMI.- Implemented the software architecture of the recommendation system, interface specification and integration into the existing software architecture of the infotainment system.

Developed a model-based compensation algorithm for the rotor position calibration.