College of Science & Engineering
The development of computationally efficient surrogates of complex and high-dimensional systems is essential for several scientific inquiries. The benefits brought by such models can be measured by the reduction of the computational cost of estimating hundreds, thousands, or even millions of responses of a single model due to the large number of combinations of its parameters. Applications can be found in the design of reliable structures as well as on the optimization of complex systems. Therefore, this line of investigation focuses on the development of robust, reliable, and efficient surrogate models using advanced mathematical concepts and computational tools.