Application of untrained machine learning analysis of multivariate sediment provenance data to critical metals exploration
Drs. Joel E. Saylor (EOAS) and Michael Friedlander (Computer Science) have been awarded the DSI Postdoctoral Matching Fund for their project "Application of untrained machine learning analysis of multivariate sediment provenance data to critical metals exploration".
Summary
Joel E. Saylor
Associate Professor, Earth, Ocean and Atmospheric Sciences
Prediction and management of the long-term environmental risk of mine waste rock piles via 5G-enabled instrumentation and monitoring
Drs. Wenying Liu (Materials Engineering) and Roger Beckie (Earth, Ocean and Atmospheric Sciences) are the latest recipients of the DSI Postdoctoral Matching Fund for their project "Prediction and management of the long-term environmental risk of mine waste rock piles via 5G-enabled instrumentation and monitoring".
Summary
Roger Beckie
Professor, Earth, Ocean and Atmospheric Sciences