Research Scientist - Technische Universitaet Chemnitz, Germany
2018 - 2024Research career focused on machine learning for engineering simulation, 3D deformation modeling, automotive body production, and environmental sensor analysis across BMBF-funded applied research projects.
ML@Karoprod: Machine Learning for Automotive Body Production
BMBF project with Fraunhofer IWU, SCALE GmbH, and TU Chemnitz.
- Created large-scale FEM training datasets for sheet metal forming where no suitable dataset existed.
- Used implicit neural representations, including signed distance functions, for dense deformable geometries.
- Developed surrogate models for geometric deviation, thickness distribution, and thinning on high-resolution shell meshes, including the ML-Karoprod MeshPredictor.
- Built reinforcement learning approaches for inverse process design and sequential deformation modeling.
Smart Airsense: AI-Based Health Assistant
January 2022 - 2024BMBF project with Corant GmbH / air-Q and TU Chemnitz.
- Worked with air-quality sensor measurements logged over time by Corant / air-Q devices.
- Added machine learning methods for predicting environmental events from noisy real-world time-series data.
- Developed and validated predictive models in a human-in-the-loop machine learning setting.