Workshop on Machine Learning for Astroparticle Physics and Astronomy,
co-located with INFORMATIK 2022

26 Sep 2022 (2pm – 6pm) — Hamburg, Germany

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Machine learning algorithms have emerged as one of the driving forces for advancements in astroparticle physics and astronomy.

The future of this development can be expected to hold nothing less than groundbreaking scientific discoveries. The involved data analysis tasks, e.g. particle property reconstruction, particle classification and ML-based deconvolution, require a diverse set of algorithms, such as ensemble methods, regression, unsupervised learning, imbalanced learning and various types of neural networks. The efficient generation of large amounts of annotated examples in Monte Carlo simulations is a key characteristic of the field, as well as one of its largest challenges.

This interdisciplinary workshop will bring together leading experts from Computer Science, astroparticle physics and astronomy, to present and discuss recent developments at the intersection of these fast evolving fields. The ultimate goal of this workshop is to foster collaborations that span multiple disciplines to further advance all fields involved. We invite all submissions that are in line with this goal, including methodological, theoretical and practical works, as well as proofs of concepts. Submissions can address, without being limited to, the following topics:

Details regarding the dates, the submission, and the program are given below.


All accepted papers will be published in the proceedings of INFORMATIK 2022. These proceedings appear in the series Lecture Notes in Informatics (LNI).

Update: The proceedings are now published.


This half-day workshop will host 1 physics keynote, 2 computer science keynotes, and oral presentations of all accepted papers.

Update: You can now download the slides from our cloud server.


14:30 – 15:00 Katharina Morik, TU Dortmund University: Machine Learning for Astroparticle Physics
15:00 – 15:30 Daniel Nieto, Universidad Complutense de Madrid: Applications of Machine Learning to Gamma-Ray Astronomy
15:30 – 16:00 Alejandro Moreo, Instituto di Szienza e Tecnologie dell’Informazione: Quantification
16:00 – 16:30 break
  Contributed Talks
16:30 – 16:50 Mirko Bunse, TU Dortmund University: Unification of Algorithms for Quantification and Unfolding
16:50 – 17:10 Janis Kummer, Center for Data and Computing in Natural Sciences (CDCS)/ Universität Hamburg: Radio Galaxy Classification with wGAN-Supported Augmentation
17:10 – 17:30 Dmitry Malyshev, Erlangen Centre for Astroparticle Physics: To split or not to split classes of gamma-ray sources?
17:30 – 17:50 Shreyas Kalvankar, K. K. Wagh Institute of Engineering Education and Research: Astronomical Image colorization and up-scaling with Conditional Generative Adversarial Networks
17:50 – 18:10 Pranav Sampathkumar, Karlsruhe Institute for Technology: Sequential networks for cosmic ray simulations
18:10 – 18:30 Jigar Bhanderi, University of Erlangen-Nurenberg: Calculation of the Photon Flux in a Photo-Multiplier Tube with Deep Learning

Keynote Speakers


All submissions must adhere to the following requirements:

or copy the template on Overleaf


All submission deadlines correspond to Anywhere-on-Earth (AoE) time.

4 Mar 2022 Submission opens
21 May 2022 Submission deadline (extended)
17 Jun 2022 Notification
8 Jul 2022 Camera-ready deadline
26 Sep 2022 Workshop (2pm – 6pm)


The program committee of this workshop consists of renowned experts in astroparticle physics, machine learning, and astronomy. Clicking on one of the profiles will take you to their websites.

Contact: Any remaining question may be directed to Tim Ruhe or Dominik Elsässer.