Dr. Viana's work is focused on the application of machine learning, Bayesian methods, uncertainty quantification, and multidisciplinary optimization to new designs and improvement of fielded products. Applications have ranged from aircraft propulsion, to power generation, to oil and gas systems, and healthcare. Over the years, his research has generated a number of peer reviewed publications and patents. He serves as Review Editor for the Structural and Multidisciplinary Optimization Journal and as reviewer in top journals and conferences.
Before joining UCF, Dr. Viana was a Sr. Scientist at GE Renewable Energy, where he led the development of state-of-the art computational methods for improving wind energy asset performance and reliability. Prior to moving to that role at GE, he spent five years at GE Research, where he led and conducted research on design and optimization under uncertainty, probabilistic analysis of engineering systems, and services engineering.
Andre Von Zuben
Research: Anatomically-guided deep learning for ventricle geometry reconstruction using MR images
Augusto D. Marques
Research: Accelerating high-fidelity simulations with physics-informed neural networks and distributed computing
Research: Mission-specific prognosis of Li-ion batteries with hybrid physics-informed neural networks