
About
Frank Hutter is a Full Professor for Machine Learning at the University of Freiburg since 2016 and an Emmy Noether Research Group Lead since 2013. His research focuses on Automated Machine Learning (AutoML), including neural architecture search, hyperparameter optimization, and meta-learning. He pioneered tools like Auto-WEKA, Auto-sklearn, and Auto-PyTorch, and co-authored the first book on AutoML.
- Received 2010 CAIAC award for best AI thesis in Canada
- Won multiple best paper awards and international ML competition prizes
- Director of ELLIS Unit Freiburg
- Recipient of 3 European Research Council (ERC) grants
His recent work explores the intersection of foundation models and AutoML, including TabPFN (the first foundation model for tabular data) and improved pretraining/fine-tuning frameworks. He co-organized 15 AutoML workshops at top ML conferences and founded the AutoML Conference in 2022.
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