Frank Hutter

Frank Hutter received his academic training in computer science at Darmstadt University of Technology, where he completed his Vordiplom (comparable to a BSc) and Hauptdiplom (equivalent to MSc) by 2004. He later pursued his PhD at the University of British Columbia, under the supervision of Profs. Holger Hoos, Kevin Leyton-Brown and Kevin Murphy,{{Cite web |title=Kevin Murphy |url=https://scholar.google.com/citations?user=MxxZkEcAAAAJ&hl=en |access-date=2025-03-16 |website=scholar.google.com}} where his doctoral thesis, titled "Automated Configuration of Algorithms for Solving Hard Computational Problems," was awarded the CAIAC Doctoral Dissertation Award for the best thesis in Artificial Intelligence completed at a Canadian university in 2009.{{Cite web |title=Best Doctoral Dissertation Award {{!}} CAIAC |url=https://www.caiac.ca/en/best-phd-award |access-date=2025-03-16 |website=www.caiac.ca}}

Hutter did his postdoctoral research at the University of British Columbia, where he worked from 2009 to 2013. In 2013, he moved to the University of Freiburg, initially leading an Emmy Noether Research Group, and in 2017, he was appointed as a Full Professor. His contributions to machine learning have been recognized globally, particularly his work in AutoML and hyperparameter optimization. Overall, Hutter has authored over 180 peer-reviewed publications,{{Cite web |last=Hutter |first=Frank |title=Machine Learning Lab |url=https://ml.informatik.uni-freiburg.de/profile/hutter/#tppubs}} which have garnered more than 89,000 citations,{{Cite web |title=Frank Hutter |url=https://scholar.google.com/citations?user=YUrxwrkAAAAJ&hl=en |access-date=2025-03-16 |website=scholar.google.com}} reflecting the high impact of his work.

Hutter's early research laid the groundwork for the field of Automated Machine Learning (AutoML). He has been a key figure in establishing AutoML as a distinct research area. Along with various colleagues, he organized the AutoML workshops from 2014 to 2021, wrote the first book on AutoML and taught the first MOOC on AutoML. He also co-founded the AutoML conference in 2022 and served as its general chair the first two years.

He also published prominent works in various subfields of AutoML, such as hyperparameter optimization,{{Cite web |title=AutoML {{!}} Hyperparameter Optimization |url=https://www.automl.org/hpo-overview/ |access-date=2025-03-16 |language=en}} neural architecture search,{{Cite web |title=AutoML {{!}} Neural Architecture Search |url=https://www.automl.org/nas-overview/ |access-date=2025-03-16 |language=en}} meta-Learning{{Cite web |title=AutoML {{!}} Meta-Learning |url=https://www.automl.org/meta-learning/ |access-date=2025-03-16 |language=en}} and AutoML systems.{{Cite web |title=AutoML {{!}} AutoWeka |url=https://www.automl.org/automl-for-x/tabular-data/autoweka/ |access-date=2025-03-16 |language=en}}{{Cite web |title=AutoML {{!}} Auto-Sklearn |url=https://www.automl.org/automl-for-x/tabular-data/auto-sklearn/ |access-date=2025-03-16 |language=en}}{{Cite web |title=AutoML {{!}} Auto-PyTorch |url=https://www.automl.org/automl-for-x/tabular-data/autopytorch/ |access-date=2025-03-16 |language=en}} He is currently the most highly cited researcher in AutoML.{{Cite web |title=Profiles |url=https://scholar.google.com/citations?view_op=search_authors&hl=en&mauthors=label:automl |access-date=2025-03-16 |website=scholar.google.com}}

Hutter has also made many contributions to machine learning for tabular data. He led the development of the first widely adopted AutoML system for tabular data, AutoWEKA, which was published at KDD 2013 and received the test of time award at KDD (2023). Subsequently, he led the development of Auto-sklearn, the first highly used AutoML system for tabular data in Python, and with it, won the first international AutoML challenge{{Cite web |title=CodaLab - Competition |url=https://competitions.codalab.org/competitions/2321 |access-date=2025-03-16 |website=competitions.codalab.org}} and the subsequent second international AutoML challenge,{{Cite web |title=CodaLab - Competition |url=https://competitions.codalab.org/competitions/17767 |access-date=2025-03-16 |website=competitions.codalab.org}} both of which only included tabular data. More recently, he focused on tabular foundation models, including TabPFN, which was published in Nature magazine. In 2024, he also co-founded Prior Labs, the first company focusing on tabular foundation models.

Hutter has received numerous awards throughout his career. In 2023, he won the KDD Test of Time Award for Research{{Cite web |title=Awards |url=https://kdd.org/kdd2023/awards/index.html |access-date=2025-03-16 |website=KDD 2023 |language=en-US}} together with Chris Thornton, Holger H. Hoos, and Kevin Leyton-Brown. He has received three grants from the ERC, including the ERC Starting Grant (2016){{Cite web |date=2025-01-31 |title=Starting Grant |url=https://erc.europa.eu/apply-grant/starting-grant |access-date=2025-03-16 |website=ERC |language=en}} and ERC Consolidator Grant (2022),{{Cite web |date=2025-01-31 |title=Consolidator Grant |url=https://erc.europa.eu/apply-grant/consolidator-grant |access-date=2025-03-16 |website=ERC |language=en}} as well as an ERC Proof of Concept Grant (2020).{{Cite web |date=2025-01-23 |title=Proof of Concept |url=https://erc.europa.eu/apply-grant/proof-concept |access-date=2025-03-16 |website=ERC |language=en}} In 2021, he became an ELLIS Unit Director and was also recognized as a EurAI Fellow,{{Cite web |title=Awards |url=https://www.eurai.org/award/fellows |access-date=2025-03-16 |website=www.eurai.org |language=en}} in addition to receiving the AIJ Prominent Paper Award.{{Cite web |title=AIJ Awards: List of Current and Previous Winners – Artificial Intelligence Journal |url=https://aij.ijcai.org/aij-awards-list-of-previous-winners/ |access-date=2025-03-16 |language=en-US}} Earlier, he was a recipient of the Google Faculty Research Award in 2018.{{Cite web |title=Google Faculty Research Awards 2017 |url=https://docs.google.com/document/d/1IfCmWZ-ClmvmB4gzlApR4htAhYBjKliPGQxLpu6KmaU/edit?tab=t.0 |access-date=2025-03-16 |website=Google Docs |language=en}} His groundbreaking research was acknowledged early in his career with the IJCAI Distinguished Paper Award in 2013{{Cite web |title=IJCAI-13, Awards and Distinguished Papers |url=https://www.ijcai.org/Proceedings/13/Papers/006.pdf}} and the IJCAI/JAIR Best Paper Prize in 2010.{{Cite web |title=IJCAI-JAIR Awards {{!}} Journal of Artificial Intelligence Research |url=https://www.jair.org/index.php/jair/IJCAIJAIR |access-date=2025-03-16 |website=www.jair.org}}

• Hutter, F. Kotthoff, L. and Vanschoren, J., editors. Automated machine learning: methods, systems, challenges, Springer Nature, 2019. www.automl.org/book.{{Cite journal |date=2019 |editor-last=Hutter |editor-first=Frank |editor2-last=Kotthoff |editor2-first=Lars |editor3-last=Vanschoren |editor3-first=Joaquin |title=Automated Machine Learning |url=https://link.springer.com/book/10.1007/978-3-030-05318-5 |journal=The Springer Series on Challenges in Machine Learning |language=en |doi=10.1007/978-3-030-05318-5 |isbn=978-3-030-05317-8 |issn=2520-131X|url-access=subscription }}
• Feurer, M., Klein, A., Eggensperger, K., Springenberg, T., Blum, M., Hutter, F. Efficient and Robust Automated Machine Learning. In NeurIPS 2015.{{Cite journal |last1=Feurer |first1=Matthias |last2=Klein |first2=Aaron |last3=Eggensperger |first3=Katharina |last4=Springenberg |first4=Jost |last5=Blum |first5=Manuel |last6=Hutter |first6=Frank |date=2015 |title=Efficient and Robust Automated Machine Learning |url=https://papers.nips.cc/paper_files/paper/2015/hash/11d0e6287202fced83f79975ec59a3a6-Abstract.html |journal=Advances in Neural Information Processing Systems |publisher=Curran Associates, Inc. |volume=28}}
• Loshchilov, I., and Hutter, F. Decoupled weight decay regularization. In ICLR 2018.{{cite arXiv |eprint=1711.05101 |last1=Loshchilov |first1=Ilya |last2=Hutter |first2=Frank |title=Decoupled Weight Decay Regularization |date=2017 |class=cs.LG }}
• Zela,A.,Elsken,T.,Saikia,T.,Marrakschi,Y.,Brox,T.,Hutter.,F.Understanding and Robustifying Differentiable Architecture Search. In ICLR 2020.{{cite arXiv |eprint=1909.09656 |last1=Zela |first1=Arber |last2=Elsken |first2=Thomas |last3=Saikia |first3=Tonmoy |last4=Marrakchi |first4=Yassine |last5=Brox |first5=Thomas |last6=Hutter |first6=Frank |title=Understanding and Robustifying Differentiable Architecture Search |date=2019 |class=cs.LG }}
• Hollmann, N., Mu ̈ller, S. and Hutter, F. TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second, In ICLR 2023.{{cite arXiv |eprint=2207.01848 |last1=Hollmann |first1=Noah |last2=Müller |first2=Samuel |last3=Eggensperger |first3=Katharina |last4=Hutter |first4=Frank |title=TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second |date=2022 |class=cs.LG }}

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Category:Living people

Category:Year of birth missing (living people)

Category:German computer scientists

Category:University of British Columbia alumni