Jennifer Landes is an external doctoral researcher at the Chair of Data Engineering, University of Regensburg. Her research focuses on preprocessing pipelines for eye-tracking time series, data quality metrics, and the evaluation of robust data preparation methods for time-series analysis. In her doctoral work, she investigates how eye-tracking data can be standardized, cleaned, and evaluated across heterogeneous datasets in a reproducible way.