I have a background in cognitive neuroscience (Heidelberg University & LMU Munich), and in statistics & machine learning (LMU Munich & Tübingen University). In my research, I’m focused on cross-pollinating the fields of machine learning and statistics, looking for ways to make either more efficient. Here are some buzzwords: Simulation-based inference, Bayesian data analysis, latent variable modeling.

My PhD is funded by the German Academic Scholarship Foundation and the Helmholtz Institute for Human-Centered AI.

Publications

• Alex Kipnis, Marcel Binz, Eric Schulz (2025). metabeta - A fast neural model for Bayesian mixed-effects regression. arXiv:2510.07473. Code.
• Alex Kipnis, Konstantinos Voudouris, Luca M. Schulze Buschoff, Eric Schulz (2025). metabench - A sparse benchmark of reasoning and knowledge in Large Language Models. ICLR 2025. Poster, Code.
• Heiko Schütt, Alex Kipnis, Jörn Diedrichsen, Nikolaus Kriegeskorte (2023). Statistical inference on representational geometries. eLife 12:e82566. Code.