Gabriel San Martin Silva, MSc. Department of Civil and Environmental Engineering University of California, Los Angeles 420 Westwood Plaza 5731 Boelter Hall Los Angeles, CA 90095 e-mail: gsanmartin@ucla.edu Gabriel San Martín Silva is a Chilean Engineer, with a Bachelor and Master’s in Science degrees in mechanical engineer from the University of Chile. Since 2020, he has worked as a senior data scientist and developer, developing data-driven analytical models to optimize extraction processes in the copper mining industry and building the architecture required to implement them into production. In September 2021, he started a PhD at the University of California, Los Angeles (UCLA) under the supervision of PhD. Enrique López Droguett, at the Civil and Environmental Engineering Department. San Martín’s undergraduate and graduate research has been primarily focused on the application of Deep Learning models and Bayesian inference to prognosis and health management (PHM) problems, such as the identification of failure modes in ball-bearings and sea water pumps or the prediction of remaining useful life in turbo-fan machinery. From this body of work, San Martín has published one peer-reviewed paper and two conference papers. Currently, he has two additional papers in review process. His main research interests lie on the application of state-of-the-art probabilistic deep learning models to real-world industrial problems, with the objective of improving safety and efficiency in important extraction and production processes, generating value to both companies and society. In particular, his current research is based on applying quantum computing techniques to PHM problems to generate faster and improved solutions, that can provide engineers fast and accurate suggestions.