activity
20182025
most citedIntegrating Machine Learning for Planetary Science: Perspectives for the Next Decade

32 citations · 97 across the 8 of their papers we have counts for

collaborators

8 papers

astro-ph.IM2025

Science Autonomy using Machine Learning for Astrobiology

Victoria Da Poian, Bethany Theiling, Eric Lyness +13

In recent decades, artificial intelligence (AI) including machine learning (ML) have become vital for space missions enabling rapid data processing, advanced pattern recognition, a…

astro-ph.IM2023★ 1 cited

The case for studying other planetary magnetospheres and atmospheres in Heliophysics

Ian J. Cohen, Chris Arridge, Abigail Azari +37

Heliophysics is the field that "studies the nature of the Sun, and how it influences the very nature of space - and, in turn, the atmospheres of planetary bodies and the technology…

physics.space-ph2023★ 18 cited

Magnetic Field Draping in Induced Magnetospheres: Evidence from the MAVEN Mission to Mars

A. R. Azari, E. Abrahams, F. Sapienza +8

The Mars Atmosphere and Volatile EvolutioN (MAVEN) mission has been orbiting Mars since 2014 and now has over 10,000 orbits which we use to characterize Mars' dynamic space environ…

astro-ph.IM2020★ 9 cited

Advancing the Scientific Frontier with Increasingly Autonomous Systems

Rashied Amini, Abigail Azari, Shyam Bhaskaran +19

A close partnership between people and partially autonomous machines has enabled decades of space exploration. But to further expand our horizons, our systems must become more capa…

astro-ph.IM2020★ 32 cited

Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade

Abigail R. Azari, John B. Biersteker, Ryan M. Dewey +13

Machine learning (ML) methods can expand our ability to construct, and draw insight from large datasets. Despite the increasing volume of planetary observations, our field has seen…

physics.space-ph2020★ 29 cited

Incorporating Physical Knowledge into Machine Learning for Planetary Space Physics

A. R. Azari, J. W. Lockhart, M. W. Liemohn +1

Recent improvements in data collection volume from planetary and space physics missions have allowed the application of novel data science techniques. The Cassini mission for examp…

physics.space-ph2020★ 8 cited

The STONE curve: A ROC-derived model performance assessment tool

Michael W. Liemohn, Abigail R. Azari, Natalia Ganushkina +1

A new model validation and performance assessment tool is introduced, the sliding threshold of observation for numeric evaluation (STONE) curve. It is based on the relative operati…

astro-ph.EP2018

Solar System Ice Giants: Exoplanets in our Backyard

Abigail Rymer, Kathleen Mandt, Dana Hurley +110

Future remote sensing of exoplanets will be enhanced by a thorough investigation of our solar system Ice Giants (Neptune-size planets). What can the configuration of the magnetic f…