COSPAR cross-disciplinary workshops

November 1, 2020, from Mark Cheung

Dear colleagues,

We would like to bring your attention to the following cross-disciplinary workshops at COSPAR 2021.

Machine Learning for Space Sciences https://cospar2021.gitlab.io/ml4ss/

The widespread availability of machine learning (ML) technologies promises to disrupt scientific disciplines. Popular open source ML frameworks are not only useful for data-driven model fitting, but also for efficient computation of physics-based models. This cross-disciplinary workshop is dedicated to showcasing use cases of ML technologies to observational and simulation data. This includes applications to:

– satellite imagery classification and image restoration (including super-resolution),
– space weather prediction,
– exoplanet detection and characterization,
– astrophysical simulations,
– data augmentation, and
– compressed sensing and inverse problems.

Autonomy for Future Space Science Missions https://cospar2021.gitlab.io/autonomy/

The rise of machine learning (ML) and artificial intelligence (AI) techniques is creating opportunities for space science missions with unprecedented capabilities. By augmenting traditional rule-based decision making with AI techniques (such as decision policies in deep reinforcement learning), robotic missions may become highly autonomous. Furthermore, ML advances will augment the capabilities of crews serving in extended space missions. Questions to be explored in this cross-disciplinary workshop include:

– Across the many disciplines in space sciences, what are the mission requirements that drive the need for autonomy?
– How will ML/AI enable autonomous capabilities?
– What platforms are available for low-power, high-throughput compute in space?
– How can advances in ML augment human capabilities in crewed missions?

Cloud Computing for Space Science https://cospar2021.gitlab.io/cloudcomputing/

This cross-disciplinary workshop will include tutorials and case studies addressing the following questions:

– What cloud compute offerings are available for space researchers to develop workflows?
– How can we use open source software and cloud compute to massively scale scientific data processing?
– How can scientists equip ourselves with the skills to take advantage of these technologies?
– How can cloud compute and web technologies be used to engage the public in citizen science, and for enhancing STEAM* education?

The aim of these workshops is to let researchers share techniques / case studies / solutions / visions of interest to a broad audience beyond target audiences of individual COSPAR scientific commissions.

The abstract submission deadline for the workshops has been extended to Nov 10th. Note: abstracts for these workshops are processed separately than abstracts for COSPAR scientific sessions. We look forward to your contribution.

http://cospar2021.gitlab.io/ml4ss/


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