Group lead of “Sensor Technology & Data Science” research group (10 researchers & developers, since 04/2023).
Sensor technology & machine/deep learning applications in mechanical recycling processes for plastics, construction & demolition waste & metals.
Student assistant in the research areas metal recycling and sensor technology.
Tutor for the courses “Principles of Mechanics and Machinery Components 1” (SoSe 2017), “Principles of Mechanics and Machinery Components 2” (WiSe 2017/18) and “Introduction to Process Engineering” (SoSe 2018).
Part-time job during my university studies.
Voluntary internship during my master studies.
Voluntary internship on wind turbine project development in preparation for my university studies.
Voluntary school internship on surface water monitoring.
Grade: summa cum laude (with distinction) Topic: “Sensor-based characterization of anthropogenic material systems: Developing characterization methods and novel applications for optimizing the mechanical recycling of lightweight packaging waste”
Supervisors: Univ.-Prof. Dr. rer. nat. Kathrin Greiff & Univ.-Prof. Dr. mont. Dipl.-Ing. Roland Pomberger
Grade: 1.1 (with distinction) [top 0.3% of all graduates] Area of Specialisation: Recycling
Master Thesis: “Optical material flow characterization of metal-containing fine fractions through machine learning” Grade: 1.0 (very good)
Project Thesis: “Development of a calibration software for dual camera 3D laser triangulation measurements” Grade: 1.0 (very good)