SME 2022 Presentations

March 2022 SME
Gaussian Process Presentation Bayesian Mass Balance Presentation

Thanks to those that attended the MPD: Chemical Processing: Modeling, Simulation, and Machine Learning for Hydrometallurgy sub session!

The slides for Gaussian Process Modeling of Hydrometallurgical Separations with Uncertain Dynamics can be found here.

The slides for Bayesian Mass Balancing of Hydrometallurgical Processes can be found here here.

Additionally, take a look at the BayesMassBal vignette and publication to learn how to conduct a Bayesian mass balance on your data.

Feel free to get in contact with me for any questions you may have, or if you are unable to access The utility of Bayesian data reconciliation for separations publication.

Bayesian Inference Economic Modeling Gaussian Process Machine Learning Mass Balance Modeling Optimization R REEs Software
Scott Koermer
Scott Koermer
Post-Doctoral Researcher

Post doctoral researcher at Los Alamos National Lab with the statistical sciences group. During my time at Los Alamos I have worked on explosion monitoring applications as well as model/prior selection for Bayesian Neural Networks. Much of my research in the past 6 years has focused on applying Bayesian methods to scientific and engineering applications, including modeling processes for optimizing the recovery of critical minerals from waste streams.

Related