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.

2024 Seminar Series

9th April 2024

Tuesday at 9 AM US Pacific

Opal Issan
University of California San Diego

Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction

Previous seminars with abstracts can be found on YouTube.


To receive invitations to our monthly series or to recommend speakers, please fill out our community form.


Indhu Varatharajan

Stony Brook University

Andy Smith

University College London

Past Organizers

Abigail Azari

Space Sciences Lab, University of California Berkeley

Caitriona Jackman

Dublin Institute for Advanced Studies