Tim Ruhkopf, M. Sc.
Leibniz Universität Hannover
Institut für Künstliche Intelligenz
Appelstr. 9A
30167 Hannover
phone: +49 511 762 5312

Since july 1st 2022,  Tim Ruhkopf is a member of the new AI Institute. For any updates please take a look there.

Tim Ruhkopf received his M.Sc. in Applied Statistics and B.Sc. in Economics from the University of Göttingen. In his studies, he focused on Machine & Deep Learning, (Bayesian) Generalized Linear Regression methods and Econometrics respectively. His thesis concerned itself with extracting main effects from Bayesian Neural Networks using grouped shrinkage priors and splines; inferring its parameters using Stochastic Gradient Markov Chain Monte Carlo methods.

Since Sep. 2021, he is pursuing his Ph.D. as a member of Prof. Lindauer’s group.
His current research interests are Bayesian- and multi-fidelity optimization in particular, aiming at boosting the performance of machine learning algorithms by choosing appropriate hyperparameters in a data-driven, principled and efficient manner. His distinct objects of study are Knowledge Graphs and Graph Neural Networks.

  • Tim Ruhkopf Aditya Mohan
    Towards Meta-learned Algorithm Selection using Implicit Fidelity Information
    ArXiv Preprint, June 2022
  • Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, René Sass, Frank Hutter
    SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
    Journal of Machine Learning Research (JMLR) -- MLOSS, Vol. 23, No. 54, pp. 1-9, January 2022