-
model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
-
to study chemical transformations in materials. 2. Artificial Intelligence Applications: - Leveraging conventional machine learning techniques for materials property prediction and Bayesian approaches
-
key element of the two-beam acceleration concept Emphasize Bayesian optimization approaches and integrate these methods into the facility control system Design, execute, and analyze accelerator
-
pipelines, including pulse processing (e.g., optimal filtering), pileup mitigation, drift correction, and energy-scale stability. Design, propose, and execute high-impact in-house spectroscopy experiments