In this episode, Francesco Colosimo and Rhys Paterson sit down with Alexis Pascual, PhD student in the Electrical and Computer Engineering department, as he updates us on his research with machine learning and AI in space applications. Alexis explains how he uses linear algebra and statistics on images to teach extraterrestrial vehicles to pick out interesting features on a martian surface. This episode is full of questions to be answered such as: the probability of the MARS rover becoming a self-sufficient machine, what the Mars yard is like and who is better: Canadian Space Agency or NASA?

To hear more from Alexis, head over to his website https://alexispascual.github.io 

You can listen to his previous episode here.  

Recorded on September 28th, 2021.

Produced by Hira Nadeem.

Theme song provided by https://freebeats.io/ Produced by White Hot.