The goal of the ML- Helio conference is to leverage the advancements happening in disciplines such as machine learning, deep learning, statistical analysis, system identification, and information theory, in order to address long-standing questions and enable a higher scientific return on the wealth of available heliospheric data.

We aim at bringing together a cross-disciplinary research community: physicists in solar, heliospheric, magnetospheric, and aeronomy fields as well as computer and data scientists. ML- Helio will focus on the development of data science techniques needed to tackle fundamental problems in space weather forecasting, inverse estimation of physical parameters, automatic event identification, feature detection and tracking, times series analysis of dynamical systems, combination of physics-based models with machine learning techniques, surrogate models and uncertainty quantification.

The conference will consists of classic-style lectures, complemented by hands-on tutorials on Python tools and data resources available to the heliophysics machine learning community.

The conference will be hosted in hybrid mode (in-person and virtual).

Please read our Code of Conduct.

Program

Invited Speakers (confirmed)

Jonathan Citrin (Google DeepMind)
Henrik Eklund (ESA)
Opal Issan (UCSD)
Caitriona Jackman (DIAS)
Robert Jarolim (NCAR/HAO)
Sabrina Guastavino (Univ. of Genova)
George Miloshevich (KU Leuven)
Paul Wright (Univ. of Exeter)

Program

The preliminary program can be downloaded here.
The book of abstracts can be downloaded here.

Publications

Call for papers
Submission deadline: Thursday, 31 December 2026
Click here to submit a manuscript

This Special Collection, inspired by the ML-Helio conference, highlights emerging advances in machine learning and data-driven methodologies that are transforming heliophysics research. Rapid developments in machine learning, deep learning, statistical inference, system identification, and information theory are opening new pathways to address long-standing scientific challenges and to realise greater value from the growing volume and diversity of heliospheric data.

The collection brings together a highly interdisciplinary research community—including experts in solar, heliospheric, magnetospheric, and aeronomy physics alongside computer scientists and data scientists—to advance methodological innovation and scientific discovery in heliophysics. Contributed works span a broad range of topics central to modern space science, including space weather forecasting, inverse estimation of physical parameters, automated event identification, feature detection and tracking, time-series analysis of dynamical systems, physics-informed machine learning, surrogate modelling, and uncertainty quantification.

Reflecting the integrative spirit of the ML-Helio conference, this Special Collection emphasises both fundamental advances and practical tools that drive progress across AGU journals such as JGR: Machine Learning and Computation, JGR: Space Physics, Space Weather, and Earth and Space Science. Together, these contributions chart the rapidly evolving landscape of machine learning in heliophysics and foster a collaborative community dedicated to accelerating scientific understanding of the Sun–Earth system.

Important Dates

15 July 2025: Abstract submission deadline
31 August 2025: In-person registration closes
 20 September: Registration for online participation closes
22–26 September 2025: Conference
 31 December 2026: Paper submission deadline for AGU Special Collection ( Click here to submit a manuscript)
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Registration & Abstracts

Submit your abstract via this link (deadline: July 15th)

Conference fees: EUR 250 (in-person) or EUR 30 (virtual)

Registration is open here (online only)
Note: The venue has a maximum capacity of 100 in-person attendees, and therefore registration might close earlier. We encourage to not delay your registration if you intend to attend in person.

Invitation letter: Email enrico.camporeale@colorado.edu if you need an invitation letter.
(Letters are for registered participants only.)
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Venue & Travel

The conference will be held at the European Space Astronomy Centre (Madrid). A shuttle bus will be arranged to/from Madrid.

Venue and transport: click here

Accomodation: click here

Travel grants application: here

Dependent Care Support Application : here

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Committee

Scientific Organizing Committee

Abigail Azari (U. Alberta)
Jacob Bortnik (UCLA)
Enrico Camporeale (CU/QMUL, chair)
Yang Chen (U. Michigan)
Veronique Delouille (ROB)
Laura Hayes (DIAS)
Farzad Kamalabadi (U. Illinois)
Michael Kirk (NASA)
Stefan Lotz (SANSA)
Naoto Nishizuka (NICT, Japan)
Pete Riley (Predictive Science Inc.)
Simon Wing (APL, Johns Hopkins)

Local Organizing Committee

Arnaud Masson (ESA)
Jan Reerink (ESA)
Domenico Trotta (ESA)

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Sponsors

Interested in sponsoring? Download the sponsor prospectus .

Microsoft CMT provided the peer-review platform and infrastructure free of charge.
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