I am a machine learning researcher based in Copenhagen. I work on the numerics of machine learning, including topics such as probabilistic numerics, Gaussian process models, differential equations, state-space models, numerical methods for and with (Bayesian) deep learning, and differentiable programming (Google Scholar). I write a bunch of code, mainly in Python/JAX (Github: @pnkraemer). |
I am currently a postdoc in Søren Hauberg's group at DTU. Before that, I did probabilistic numerics in Philipp Hennig's group in Tübingen, and scattered data approximation with Christian Rieger in Bonn. I studied Mathematics and Business Mathematics in Bonn and Mannheim.
I go by Nico, but use Nicholas when writing papers. Online, I tend to be @pnkraemer (and "pn" stands for "Peter Nicholas", not for "probabilstic numerics"). Find my papers on Google Scholar and my code on GitHub.
Google Scholar: click here
GitHub: @pnkraemer
X: @pnkraemer
Email: pekra (at) dtu (dot) dk
Talk to me in English or German. I would love to hear from you.