Snehamoy Chatterjee, Associate Professor and the Witte Family Endowed Faculty Fellow in Mining Engineering in the Department of GMES, is the principal investigator on a project “Mine Health and Safety Big Data Analysis and Text Mining by Machine Learning Algorithms” that has received a $288,343 R&D contract from the National Institute for Occupational Safety and Health (NIOSH).
Mine Safety and Health Administration (MSHA) collects mine inspections, violations, and accidents/injuries data. States also collect the workers’ compensation data related to mining accidents. These data are massive and complex, with many underlying risk factors for mining accidents. This research will identify the underlying risk factors of mining accidents and injuries by analyzing the complex datasets by exploiting state-of-the-art machine-learning algorithms. It will develop a web-based tool for visualizing the risk factors and run what-if scenarios to understand the potential risks for a mine.
This award will support a PhD and an MS student in Mining Engineering.
Aref Majdara (ECE/ICC) is a co-PI on this two-year project.