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and research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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trials, multiple endpoints, adaptive designs, Bayesian design and analysis methods, estimands, meta-analyses, benefit-risk analyses, subgroup analyses, biosimilars, patient experience data, bioequivalence
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Implementing Bayesian networks and uncertainty quantification techniques to account for sensor noise and model confidence limits Designing, training, and fine-tuning computer vision models to extract clinically
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