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I like both the problem and the solution. This is why I studied Psychology and Computer Science. Learning is a fascinating and complex process I aim to understand and improve using the modern toolbox of quantitative methods. These tools are classical statistics, gradient-based, hierarchical function approximators (neural networks), including language models.

Research #

  • Currently, I am working on my Master’s Thesis on adapting Large Language Models for language practice with a focus on English grammar acquisition. This work is co-supervised by Mrinmaya Sachan at ETH Zurich and Detmar Meurers at the University of Tübingen. I will present related work on educational text generation that I did at Yale at the BEA workshop at NAACL24 in Mexico-City in June.
  • Under the supervision of Christian Fischer and Renzhe Yu, I investigated Machine Learning models for student dropout prediction in higher education. I presented our work at LAK24 in Kyoto.
  • Previously, I worked on the creation of Knowledge Graphs with Álvaro Tejero-Cantero in the ML Science Colaboratory at the University of Tübingen.
  • With Sascha Schroeder, I improved the preprocessing of eye-tracking for psychological studies of reading acquisition. The novel algorithm achieved state-of-the-art performance for text line assignment of noisy gaze data.
  • At the Hasso Plattner institute, I investigated the data-privacy-compliant integration of third-party educational resources into cloud learning platforms using a pseudonymization approach under Jan Renz. I wrote an article (in German) about didactics within e-learning environments in their blog: Dialogisches Lernen

Education #

2024 (expected) - Master of Science Quantitative Data Science Methods, University of Tübingen

2023 - Visting Graduate Student, Yale University

2021 - Bachelor of Science Psychology, University of Göttingen

2021 - Erasmus scholar, Universidad de Sevilla

2018 - Bachelor of Science IT-Systems Engineering, Hasso-Plattner-Institut, Potsdam