We welcome Teresa Scheidt, who joins our group for a research internship over the summer. Teresa is a Master student at Lund University, where she is currently in the first year of the Master program ‘Machine Learning, Systems and Control’. She completed her bachelor’s degree in ‘Medizintechnik’ (Medical Engineering) at the University of Tübingen and the University of Stuttgart with excellence. After her Master, Teresa hopes to pursue a PhD in the area of Machine learning in medical applications, combining her knowledge in both areas.
The goal of her current research project here in Siegen is to quantify how the performance of recommender systems changes over time, an issue that has recieved too little attention so far. To achieve this goal, Teresa will work with different state-of-the-art algorithms and libaries as well as many well-known recommender datasets, such as MovieLens and the Netflix Prize dataset. With her work, Teresa contributes to an ongoing discussion about evaluation of recommender systems by giving a new perspective. She will gain valuable insight in the field of recommender systems and the work of PhD students.