Dr Eriita Jones
Planetary and Space Scientist
Research Fellow at the School of IT and Mathematical Sciences and Computational Learning Systems Laboratory, University of South Australia
Dr Eriita Jones is a Planetary and Space Scientist (PhD in Astrophysics from the Australian National University), and Research Fellow at the University of South Australia. Her passion is finding and understanding present-day liquid water and habitable environments on Mars and other planetary bodies in the solar system, though analyses and modelling of multispectral satellite data, elevation data, and surface features which may be expressions of groundwater at greater depths.
She previously worked as postdoctoral researcher at the Centre for Planetary Science and Exploration at the University of Western Ontario, Canada, and was Project Manager for a Mars analogue site selection contract with the Canadian Space Agency.
She is particularly interested in applications of machine learning, human and robotic site selection processes, planetary analogue sites, analysis of big spatial and spectral data sets, and new methods of indirect subsurface water detection.
Outside of space research, Dr Jones is passionate about women in STEM, environmental protection, veganism, animal rights, and sci-fi.
Exploring the surface of Mars with machine learning
Imagine a phenomenon that does not occur anywhere on planet Earth: metres thick deposits of carbon dioxide ice become transparent, allowing sunlight to pass through them and warm the dark sand down beneath the ice. The base of the ice warms up just enough to sublimate, causing an explosive eruption of CO2 gas back up through the surface of the ice and spouting huge jets of dust and dirt into the air. The debris is carried a short distance by the wind before settling back down onto the surface. No human has even witnessed this springtime drama at the southern polar terrain of Mars, but satellites have captured many hundreds of high-resolution images of the dark fans and blotches left behind on the surface.
This talk will discuss how a neural network can find these features and help us understand them, how we can use machine learning to learn about the surfaces and subsurface of other planets, and even how neural networks can help us search for life elsewhere in the solar system.
Register to see Eriita's presentation on December 6th, 2018 here.