ML3 seminar / DecomNN
Artificial intelligence and machine learning models are a hotly debated topic in media studies, and contemporary life. We created this course to introduce students with a background in humanity studies, to the technological background of machine learning, its concepts but likewise its ideas behind the working behavior. So yes, this course does include mathematics. However, it does not focus on the mathematical definition, but rather tries to foster a deeper understanding on how machine learning model are capable of learning various disciplines. We want that students develop more technical understanding to be able having deeper discussions about machine learning regarding areas like computer vision, generative networks or language models.

Jennifer Matthiesen is a PhD student at the Machine Learning Group of Prof. Dr. Ulf Brefeld at the Leuphana University of Lüneburg. Her research focusses on is to investigate mouse movement for determining users, user intention and behaviour. The aim is to leverage machine learning techniques to investigate data from mouse movements to identify single users and predict the short- and long-term behaviour of users.

Tino Paulsen is a research associate at the Leuphana University of Lüneburg and a PhD student at the Machine Learning Group of Prof. Dr. Ulf Brefeld. He has a background in psychology, mathematics and datascience. While his work is centered around anomaly detection, his research has a special focus on non-euclidean geometry (e.g. hyperbolic space) and how to incorporate them in deep learning methods.