Purpose

Building connections to advance applications

Machine learning (ML), and other large-data analysis techniques, have become essential tools for analyzing the ever-increasing sizes of scientific data returned from planetary missions. In addition, ML methods have demonstrated potential to assist in mission planning and operations. Planetary science and space physics have often been fields defined by sparse data concerns and extreme environments. These aspects provide a uniquely challenging, and rewarding field to apply data science methods.

This seminar series aims to bring together researchers in planetary science, space physics, data science, and other domain applications of data science. We welcome presentations from a broad array of fields including: Earth based and planetary science applications, educational efforts, and basic data science research.

Upcoming Seminar

June 29 2021
9 AM Pacific / 12 PM Eastern / 5 PM Dublin

Victor Pinto
University of New Hampshire

Reproducibility in Space Sciences: Do we really need to publish our codes?

St├ęphane Aicardi
Observatoire de Paris

Deep Learning on Jovian Decametric Emissions

Full seminar series schedule with abstracts.

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Abigail Azari

Space Sciences Lab, University of California Berkeley

Caitriona Jackman

Dublin Institute for Advanced Studies

Andy Smith

University College London