On Wednesday, Oct 2nd, CROSH Student Member Elmira Saffarvarkiani is defending her thesis for her M.Sc. in Computational Sciences. All are welcome to come out (virtually) and support her!

Date: October 2nd

Time: 9:00 AM ET

Thesis Title: Injury Prediction for Canadian Mineral Exploration Using Machine Learning and Time Series.

Supervisors: Dr. Alison Godwin and Dr. Kalpdrum Passi

Zoom Link: Email croshtech@laurentian.ca for the Zoom link

Abstract: The mineral exploration industry, vital to Canada’s economy, is also one of the most hazardous sectors, with workers facing significant risks of severe injuries or fatalities. This research focuses on improving occupational health and safety by predicting nature of injury within the industry. Utilizing an extensive dataset from the Prospectors and Developers Association of Canada (PDAC), the study applies advanced machine learning (ML) techniques to forecast injury severity across four classes. Eight ML methods, including Support Vector Machine, Convolutional Neural Network, Bayesian Neural Network, and more, along with four time series methods, were used. The findings offer critical insights into injury patterns, enabling the development of enhanced safety protocols. By providing quantitative predictions, this research aims to reduce injury rates and improve safety measures in the mineral exploration sector, contributing to a safer working environment.