MESS 2024: Metaheuristics Summer School

Automated Deep Learning meets High-Performance Computing

The 3rd international Metaheuristics Summer School – MESS 2024 – ( is aimed at qualified and strongly motivated MSc and PhD students; post-docs; young researchers, and both academic and industrial professionals to provide them with an overview on the metaheuristics techniques, and an in-depth analysis of the state-of-the-art. It is a full-immersion four-days course in the beautiful city of Catania whose goal is to offer all participants with a stimulating environment to study and learn advanced concepts and recent research in the fields of Metaheuristics, Optimization, Machine Learning and Artificial Intelligence, in general.

The main theme of this third edition is focused on “Automated Deep Learning Meets High-Performance Computing”, that is how these research areas may interact and affect each other in order to develop reliable and robust solving methodologies for Big Data analysis, and data-driven problems.

The courses will be taught by world-renowned experts in the field and will involve a total of 36-40 hours of lectures, therefore according to the academic system, all PhD and master students attending the summer school will can get 8 ECTS points. To this end, during the school the students will tackle homework, and/or project development for final evaluation. Furthermore, during the four days, the participants will have plenty of opportunities to debate and work with leaders in the field, benefiting from direct interaction and discussions in a friendly environment. 

MESS 2024 also offers the possibility to all attendants to present their recent results and/or their works in progress through interaction with their scientific peers, in a professional and constructive environment.

As carried out in the past editions, also in this edition all participants will be involved in the “Metaheuristics Competition Race”, where each of them, individually or divided in working groups (no more than 3 people), will develop a metaheuristic solution for a given problem presented during the school. The top three of the competition ranking will receive the MESS 2024 award and will be involved in the writing of a manuscript dedicated to the competition that, afterwards, will be submitted to an international journal for possible publication. In addition, the remaining best ten in the ranking (excluding the top three, of course) will be invited to report their work in a manuscript which will be published in the special MESS 2024 Volume of the AIRO Springer Series.


Thomas Bartz-Beielstein, TH Koln, Germany
Lecture 1: Introduction to Surrogate-Based Hyperparameter Tuning in Classical Machine Learning, Online Machine Learning, and Deep Learning
Lecture 2: Exploring Hyperparameter-Tuning Applications:
Optimizing scikit-learn, River, and PyTorch with SPOT and Other Tuning

Aaron Klein, AWS Research Berlin, Germany
Lecture 1: Introduction into AutoML: Hyperparameter Optimization
Lecture 2: Introduction into AutoML: Neural Architecture Search

El-Ghazali Talbi, University of Lille1, France
Lecture 1: TBA
Lecture 2: TBA

~ More Lecturers will be announced soon ~

Important Dates

Application Deadline: March 16, 2024

Notification of acceptance: March 30, 2024

Early Registration: by April 30, 2024

Late Registration: from May 1, 2024