Postal addressInstitut für Informatik
Sekretariat Hutter/Maschinelles Lernen
79110 Freiburg, Germany
Fax+49 761 203-74217
OfficeBuilding 74, Room 00-014
In 2020 I joined the Machine Learning Lab as a PhD student under the supervision of Frank Hutter. Before that I joined the Stanford AI Lab for my master’s thesis to work in Jeannette Bohg’s IPRL group on robotic manipulation. As a student research assistant, I also worked at Tamim Asfour’s H2T Lab with focus on robot perception. I hold a M. Sc. from KIT in CS/Machine Learning and am alumnus of the German National Academic Scholarship Foundation.
- Self-supervised Learning
- Transfer Learning
Getting in touch
If you are a very good student and interested in working with me on the above mentioned research interests, please feel free to reach out via email. In order to assess a good fit, please answer the questions listed on this webpage. Also, if you have any nice material such as code, figures, paper summaries, work results or a paper in which you had major contributions in please attach them to your email.
Current project offerings:
- Learning to learn finetuning (Hiwi / Project / Thesis, preferred MSc Project or MSc Thesis)
Former project offerings
- Adversarial Image Transformations for Self-Supervised Learning (Hiwi / Project / Thesis, preferred MSc Project or MSc Thesis)
- Extension of our “Zero-Shot AutoML with Pretrained Models” Work (Hiwi / Project / Thesis)
- Extension of our “Learning Synthetic Environments” Work (Hiwi / Project / Thesis)
On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning Workshop
ICML Pre-training Workshop, 2022.
Zero-shot AutoML with Pretrained Models Inproceedings
In: International Conference on Machine Learning (ICML), 2022.
Learning Synthetic Environments and Reward Networks for Reinforcement Learning Inproceedings
In: 10th International Conference on Learning Representations (ICLR), OpenReview.net, 2022.
MDP Playground: A Design and Debug Testbed for Reinforcement Learning Inproceedings
In: arXiv:1909.07750, 2021.
Learning Synthetic Environments for Reinforcement Learning with Evolution Strategies Journal Article
In: AAAI workshop on Meta-Learning Challenges, 2021.
Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019 Journal Article
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 9, pp. 3108-3125, 2020.