Explores optimization-based uncertainty quantification for ill-posed inverse problems in the physical sciences, focusing on regularization methods and interval constructions.
Covers the Statistical Finite Element Method, focusing on the construction of a prior measure, dealing with model misspecification, and combining sensor data with FEM models.
Covers advancements in sensory feedback restoration through peripheral nerve stimulation and the integration of cognitive complexity in prosthetic technology.
Covers the Likelihood Ratio Test in choice models, comparing unrestricted and restricted models through benchmarking and testing different model specifications.
