4th AutoML
School 2024

Date: September 2nd - 6th 2024 Place: Hannover, Germany


By increasing the efficiency of ML-application development and supporting users in crucial design decisions, AutoML became a key approach in the toolkit of many developers and researchers. Although there is an exponentially growing interest in AutoML, AutoML is so far only rarely taught at universities and there is a large gap between the current state of the art in research and disseminated knowledge. The AutoML Summer School will cover core topics of AutoML, covering basics, state-of-the-art approaches and hands-on sessions. Enthusiastic AutoML experts will present their diverse views on AutoML to ML practitioners, developers, research engineers, researchers and students. 

Key Features

Learn from world-leading
experts in AutoML

Hands-on sessions with
open-source packages

Talk to  people --
Increase your network

Social Events

Keynote Speakers by 

Kristian Kersting

Professor of ML & AI
at TU Darmstadt
Topic: AutoML and Neural Architecture Search

Professor of ML
at Technical University Nürnberg

Topic: Modern Hyperparameter Optimization

Oliver Bringmann

Professor of Embedded Systems
at University of Tübingen

Topic: Energy-efficient Machine Learning in Hardware 

Jan van Rijn

at Leiden University 

Topic: Overview on AutoML

Oleksandr Shchur

Applied Scientist at AWS AI

Topic: Foundational Models and AutoML for Time Series Forecasting

Markus Wagner

Professor at the Data Science & AI Department of Monash University (Melbourne) 

Topic: Optimization

Invited Speakers 

Setareh Ariafar 

Research Engineer at Google Brain

Topic: Practical Bayesian Optimization for Hyperparameter Optimization 

Katharina Strecker

Centre of Solar Energy and Hydrogen Research Baden-Württemberg

Topic: Hands-On Experience from Real-World Use Cases

Thomas Meißner
Kaggle Master. Senior Data Scientist at SumUp

Topic: Hands-On Experience with BlueCast 

Basic Lectures By

Frank Hutter

Professor of ML
at University of Freiburg /
ELLIS Institute Tübingen

Topic: AutoML and foundational Models

Professor of Statistical Learning and Data Science  
at Ludwig-Maximilians-University Munich 

Topic: Hyperparameter Optimization

Matthias Feurer

Professor and Thomas Bayes Fellow
at Ludwig-Maximilians-University Munich

Topic: AutoML Systems

Marcel Wever
PostDoc at Ludwig-Maximilians-University Munich

Topic: Green AutoML

Tutorials by

Danny Stoll and Neeratyoy Mallik
University of Freiburg

Topic: NEPS

Carolin Benjamins

Leibniz University Hannover

Topic: SMAC & Benchmarking

Daphne Theodorakopoulos

Leibniz University Hannover
Topic: Analysing Multi-Objective AutoML

Theresa Eimer and Andre Biedenkapp

Leibniz University Hannover and University of Freiburg

Topic: AutoRL with Applications to Sustainability

Christoph Gerum

University of Tübingen

Lennart Purucker

University of  Freiburg
Topic:  Automated Data Science / TabPFN

Ivo Rapant

University of Freiburg
Topic: Quicktune

In the meantime, join our AutoML MOOC

... available for free at ai-campus.org and a perfect opportunity for getting a basic background in AutoML before attending our AutoML Fall school.

Organized by Members of

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The welcome dinner and christmas market footage is lincensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.