Seminar “From medical imaging to climate: machine learning for social good” – January 28, 2019 – Sophie Giffard-Roisin

STEEP Seminar :

Date / time: January 28, 2019 – 11:00 AM
Location : F107 – building INRIA Montbonnot

Title : From medical imaging to climate: machine learning for social good
Lecturer: Sophie Giffard Roisin, post-doctoral researcher at the University of Colorado, Boulder.

Abstract :
By building collaborations with experts in specific areas, we can use the strength of artificial intelligence to help making diagnosis, and also finding concrete and local solutions for our societies. I will first talk about my PhD work in medical imaging and non-invasive cardiac techniques for surgery prediction at Inria Sophia-Antipolis. Together with cardiologists, I developed a non-invasive cardiac electrophysiological model personalisation and I generated a simulated database for training a sparse Bayesian regression. While there is still a strong need for machine learning in medicine, I also realized how it was nearly absent in other critical domains such as climate and computational sustainability. During my post-doctoral position (CNRS Saclay and University of Colorado), I worked on predicting hurricane trajectories from image-like meteorological measures. We developed a fusion of convolutional neural networks, combining past trajectory data and reanalysis atmospheric images (wind and pressure 3D fields). A comparison with current forecast models shows that deep methods could provide a valuable and complementary prediction.