Head Of Department Analytics

Fraunhofer IIS

Biography

Dr. Paulina Prantl conducts research with her department, Analytics, and specifically with the group “Data Efficient Automated Learning,” focusing on the applications of Machine Learning (ML) in industrial contexts. In industrial environments and production, ML-based process optimizations or decision support systems are often difficult to implement. This is either because there are too few large, annotated datasets or because the available data is too narrow for machine learning methods. Additionally, algorithms developed for a specific application cannot typically be easily transferred to other systems, even if they are identical in construction, which further complicates the use of ML methods in industry. Therefore, Paulina Prantl and her team are advancing methods such as Few Labels Learning or Domain Adaptation to facilitate the transferability of ML techniques in the future. Furthermore, the group is working on the automation of machine learning (AutoML), meaning the automatic selection and adaptation of suitable ML models for industrial processes, in order to build data-driven and, when possible, largely automated decision systems.