On the need for open, reproducible and explainable experiments at the interface of ML
Channel: CyberColombia
Date: 2022-07-21

5 HPC Summer School Official Website
https://cybercolombia.org/summer_school_5/

Speaker: Ricardo Barros Lourenço (McMaster University)

Abstract:   In this talk, I will introduce with some concepts of Open Science, Reproducible Experiments and Model Explainability and their relevance in Machine Learning applications for Science. In a second part, I will discuss some latest developments in their application in Remote Sensing, as well as challenges and opportunities for research in this nexus.

Short Bio: Ricardo Barros Lourenço is a Ph.D. Student in Geography at the School of Earth, Environment & Society at McMaster University, and the Communications Editor at Environmental Data Science, a journal published by Cambridge University Press. He is a member of McMaster University's Remote Sensing Laboratory led by professor Alemu Gonsamo. His research interests lie in the interface of Geosciences and Computer Science, more specifically in the spatial analysis of remotely sensed data supported by machine learning methods.