-
inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security
-
ecology, remote sensing, and computer science. UAV imagery and increasingly sophisticated and targeted AI algorithms can estimate forage quality, biodiversity, and the abundance of individual plant species
-
developing algorithms for RNA-seq and whole-genome data. Learning Objectives: Under the guidance of mentors, you will have the opportunity to learn to: (a) conduct research using swine infection models; and (b
-
-Informed Neural Networks (PINNs) and hybrid models that respect the physical laws governing the real-world system Applying Deep Reinforcement Learning (DRL) algorithms to optimize processes within simulation