Welcome to the Machine Learning Lab at the University of Freiburg!

Machine learning (ML) is the key technology of our time. However, so far, its success crucially relies on human machine learning experts to perform manual tasks, thus limiting its potential impact. To overcome this issue, here at the ML Lab, we focus on the progressive automation of machine learning (AutoML) in order to democratize access to ML by making state-of-the-art ML solutions accessible for everyone, in world-leading open source systems. Framed differently, and from a technical point of view, our lab develops AI that builds and improves AI.

Particular technical fields of interest for us include meta-learning, neural architecture search, efficient hyperparameter optimization, deep learning for tabular data, multi-objective optimization, proper benchmarking, and AutoRL. We also apply AutoML to improve practical deep learning for several applications of high societal importance, such as RNA folding and design, EEG decoding, and data from the medical sector in general.

We co-organize the MOOC on AutoML at KI Campus and the lab's prof, Frank Hutter, is general chair of the AutoML conference and also the head of the ELLIS unit Freiburg, one of the 17 founding units of the European Laboratory for Learning and Intelligent Systems (ELLIS).

On this university website, we provide information about our publications, teaching, open student projects, and how to get in touch to start working with us. We discuss AutoML in detail on our project webpage, including our open-source libraries, our blog, upcoming and past events, and our MOOC.

07.2024 Our team will present 6 papers at ICML 2024: 3 at the main conference and 3 at workshops!
04.2024 We'll present 7 papers at ICLR 2024: 2 at the main conference and 5 at workshops
09.2023 We’re delighted to announce that 6 AutoML papers from our team have been accepted to the NeurIPS2023 main track, including an oral for a paper on AutoML for Trustworthy AI! We also have 2 additional workshop papers and Frank has a keynote at the Table Representation Workshop
09.2023 We are organizing the 2023 AutoML Conference in Potsdam
08.2023 Auto-WEKA received the KDD 2023 Test of Time Award for Research
08.2023 We take part in the Small Data project that aims to overcome the challenges of learning on small data
07.2023 Frank received the Award for Excellent Supervision of Doctoral Students at the University of Freiburg
07.2023 Frank nominated by the Technical Faculty for the University Teaching Award
07.2023 Our AutoML course received the Best Teaching Evaluation at the Technical Faculty
01.2023 Konrad Zuse School of Excellence in Learning and Intelligent Systems (ELIZA) research grant awarded as part of consortium of 7 German ELLIS Units, sponsored by BMBF and DAAD
12.2022 We are organizing the next AutoML Conference! All important dates and details can be found through
12.2022 TabPFN won the best paper award at the NeurIPS'22 TRL Workshop
11.2022 We'll present 17 papers at NeurIPS 2022: 2 at the main conference, 2 at the datasets and benchmark track, and 13 at workshops!
10.2022 We're organizing the AutoML Fall School 2022 here in Freiburg
07.2022 Our GECCO’22 paper Theory-Inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration won the best paper award on the GECH track
07.2022 Frank is the co-initiator and inaugural general chair of the first AutoML conference
07.2022 We won the first prize of the AutoML 2022 Competition on Multiobjective Optimization for Transformers
05.2022 With a consortium of 10 partners, we have been awarded a grant by the ZEISS Foundation for the ReScale project
03.2022 Frank has been awarded an ERC Consolidator Grant for the topic Deep Learning 2.0!
2021 Frank was appointed as ELLIS Director for the Freiburg Unit
2021 Frank was elected fellow of the European Association for Artificial Intelligence (EurAI)
2021 Our work on Algorithm Runtime Prediction received the 2021 AIJ Prominent Paper Award
2021 Frank receives Best Teaching Evaluation at the Technical Faculty
2021 Frank gave a keynote talk at the Toronto Machine Learning Summit and the Applied AI Summit
2020 Frank has been awarded an ERC Proof of Concept Grant on AutoML
2020 We won the first prize in the NeurIPS 2020 Blackbox Optimization Challenge
2020 We launch the first MOOC on Automated Machine Learning
2020 Frank gave a keynote at ICAPS
2020 We joined the TAILOR network, focusing on the AutoAI work package.
2020 Renormalized Flows research grant awarded by the German Federal Ministry of Education and Research (BMBF)
2019 Frank was elected to the fellows of the European Laboratory for Learning and Intelligent Systems (ELLIS)
2018 Frank received the Google Faculty Research Award
2018 We won the 2nd ChaLearn AutoML Challenge 2017-2018
2018 Frank gave a keynote at ISC High Performance and a tutorial on AutoML at NeurIPS
2018 Our industrial grant proposal in collaboration with Bosch & Uni Freiburg has been approved
2017 Frank received the ICLR Best Reviewer Award
2017 Frank gave a keynote on AutoML at ECML-PKDD and at the NeurIPS Symposium on Meta-Learning
2016 Frank has been awarded an ERC Starting Grant for the topic “Beyond Blackbox – Data-Driven Methods for Modelling and Optimizing the Empirical Performance of Deep Neural Networks”
2015 Auto-sklearn won the 1st ChaLearn AutoML challenge 2015-2016
2015 SATzilla and AutoFolio won the first 3 prizes in the ICON Challenge on Algorithm Selection
2015 We worked on the project “RobDREAM” (funded by Horizon 2020 initiative) with a consortium of 7 participating institutions
2014 Frank received five awards at the IPC 2014 Planning and Learning Track
2013 Frank has been awarded the Emmy Noether Fellowship
2013 Frank’s work on High Dimensional Bayesian Optimisation received the IJCAI distinguished paper award