Time-series analysis is one of the core pillars of statistics. However, the high dimensionality and sheer size of today’s datasets pose new statistical and algorithmic challenges.

Our project tackles these challenges while also addressing classical questions like stability and stationarity. More broadly, we aim to contribute to the modernization and expansion of the theoretical and applied foundations of time-series analysis.

Why does this matter?
Time series are everywhere:
📈 Stock markets
🛒 Sales forecasting
🌦 Weather prediction
🤖 Even text data (especially relevant in the era of ChatGPT)

A deeper understanding and more efficient, reliable models for high-dimensional time series can lead to significant advances across industries and research domains.

We’re grateful for the support from:
• Deutsche Forschungsgemeinschaft (DFG) – German Research Foundation for the funding
• University of Hamburg for continuous support
• Rainer von Sachs (Belgium) for the collaboration

Excited to get started — let’s get to work! 💪