I am a Postdoctoral Researcher at the University of Technology Nuremberg, working on efficient, automated, and explainable machine learning systems, with a focus on:
- Automated machine learning
- Hyperparameter optimization
- Interpretable deep learning
- Tabular foundation models
- In-context learning & model efficiency
- End-to-End Compression for Tabular Foundation Models β ICML 2026 (Spotlight, Top 2.2%)
- Interpretable Mesomorphic Networks for Tabular Data β NeurIPS 2024
- Quick-Tune: Learning Which Pretrained Model to Finetune β ICLR 2024 (Oral, Top 1.2%)
- Scaling Laws for Hyperparameter Optimization β NeurIPS 2023
- Supervising the multi-fidelity race of hyperparameter configurations β NeurIPS 2022 (Spotlight, Top 1.91%)
- Well-Tuned Simple Nets Excel on Tabular Datasets β NeurIPS 2021
- OpenML-Python API β JMLR 2021
π More:
- Google Scholar: [Link]