79110 Freiburg, Germany
My 3 word address: park.gravel.removes
I am a researcher at the University of Freiburg, Germany. My primary research interest is in the field of artificial intelligence, with a focus on automated machine learning and algorithm configuration, i.e., the problem of automatically tuning (machine learning) algorithms to maximize their performance. In particular, I focus on using reinforcement learning to tackle the problem of dynamically configuring algorithms.
I completed my bachelor’s degree in 2015 and my master’s degree in 2017 in computer science at the University of Freiburg. From February 2018 to October 2022, I did my Ph.D. at the University of Freiburg, at the Machine Learning Chair under the supervision of Prof. Dr. Frank Hutter and Prof. Dr. Marius Lindauer (Leibniz University Hannover). In October 2022 I successfully defended my PhD (Dr. rer. nat.) with the topic Dynamic Algorithm Configuration by Reinforcement Learning.
|Nov 11, 2022|| We have two new workshop papers tackling AutoRL accepted at MetaLearn@NeurIPS’22: |
|Oct 14, 2022||🎉 I successfully defended my PhD thesis with the title Dynamic Algorithm Configuration by Reinforcement Learning with summa cum laude (the best possible grade) 🥳|
|Sep 20, 2022||On the 10th of November I’ll be giving a talk about my research in the Seminar on Advances in Probabilistic Machine Learning of the Aalto University and ELLIS unit Helsinki.|
|Aug 11, 2022||I am Chair of COSEAL jointly with Alexander Tornede and Lennart Shäpermeier. You can find the announcement here.|
|Jul 13, 2022||Our GECCO’22 paper Theory-Inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration won the best paper award on the GECH track.|
|Jun 24, 2022||We just uploaded the talk for ou GECCO’22 paper Theory-Inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration which is nominated for the best paper award.|
|Jun 19, 2022||Checkout our new paper on DeepCAVE, a tool to analyze and explain AutoML meta-data, which was just accepted at the ReALML@ICML workshop.|
|Jun 3, 2022||I am co-organizing the 2nd AutoML Fall School. The fall school will be held from 10th - 13th of October. Checkout the exciting list of invited speakers and hands-on sessions.|
|Jun 3, 2022||We just released a new paper on DAC for AI Planning. I’ll present the paper on the 13th of June at the PRL Workshop. You can also checkout the recorded talk.|
|Jun 1, 2022||Our survey on AutoRL has been published in the Journal of Artificial Intelligence Research.|
|May 30, 2022||We just released a new paper on Dynamic Algorithm Configuration (DAC) in which we discuss the DAC journey so far and give a glimpse of the future of DAC.|
|May 18, 2022||Our GECCO’22 paper Theory-Inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration has been nominated for the best paper award.|
|Apr 16, 2022||The paper Theory-Inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration is accepted for publication in the proceedings of the Genetic and Evolutionary Computation Conference (GECCO’22).|
|Apr 16, 2022||I created this personal webpage|
- Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm ConfigurationIn Proceedings of the Genetic and Evolutionary Computation Conference (GECCO’22) 2022 *Joint first authorship 🏅Won the best paper award on the GECH track.
- Automated Reinforcement Learning (AutoRL): A Survey and Open ProblemsJournal of Artificial Intelligence Research (JAIR) 2022
- TempoRL: Learning When to ActIn Proceedings of the 38th International Conference on Machine Learning (ICML 2021) 2021
- Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic FrameworkIn Proceedings of the Twenty-fourth European Conference on Artificial Intelligence (ECAI’20) 2020