Institut
Tim Ruhkopf
Tim Ruhkopf
Adresse
Welfengarten 1
30167 Hannover
Gebäude
Raum
Tim Ruhkopf
Adresse
Welfengarten 1
30167 Hannover
Gebäude
Raum

I received my M.Sc. in Applied Statistics and B.Sc. in Economics from the University of Göttingen. In my studies I focused on Machine & Deep Learning, (Bayesian) Generalized Linear Regression methods and Econometrics respectively. My 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, I am pursuing my PhD as a member of Prof. Lindauer’s group. My current research interests are Bayesian- & multi-fidelity optimization and meta-learning, aiming at boosting the performance of machine learning algorithms by choosing appropriate hyperparameters in a data driven, principled and efficient manner. Most recently we investigated, how to combine multi-fidelity and meta-learning for algorithm selection using a transformer architecture. Currently I am involved in finding a way of training reinforcement learning agents more robustly as well as training graph-based models more efficiently using a novel fidelity type.

Research Interests

  • Bayesian Optimization
  • Multi-Fidelity for Hyperparameter Optimization
  • Multi-Fidelity for Graph Neural Networks
  • Meta-Learning for Hyperparameter Optimization
  • Reinforcement Learning for Algorithm Selection on partial learning curves 
  • Hyperparameter Optimization for Reinforcement learning

Curriculum Vitae

  • Work Experience

    2021-today Doctoral Researcher Leibniz University Hannover

    2021 (6 Monate) Student Assistant, Georg-August University Göttingen

    2019 (6 Monate) Internship: Data Architecture and Smart Analytics, Deutsche Bank AG

    2017-2018 (18 Monate) Student Assistant, Georg-August University Göttingen

  • Education

    Since 2021 Ph.D. Student in AutoML, Leibniz University Hannover

    2017-2020 M.Sc Applied Statistics, Georg-August University Göttingen

    2014-2017 B.Sc. Economics, Georg-August University Göttingen

Publications

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2023


Ruhkopf, T., Mohan, A., Deng, D., Tornede, A., Hutter, F., & Lindauer, M. (2023). MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information. Transactions on Machine Learning Research. https://openreview.net/forum?id=5aYGXxByI6
Tornede, A., Deng, D., Eimer, T., Giovanelli, J., Mohan, A., Ruhkopf, T., Segel, S., Theodorakopoulos, D., Tornede, T., Wachsmuth, H., & Lindauer, M. (2023). AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks. https://doi.org/10.48550/arXiv.2306.08107

2022


Mohan, A., Ruhkopf, T., & Lindauer, M. (2022). Towards Meta-learned Algorithm Selection using Implicit Fidelity Information. in ICML Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML) https://arxiv.org/abs/2206.03130