|M.S. Student (Graduate Research Assistant)
Department of Civil, Construction and Environmental Engineering
North Carolina State University
Fitts-Woolard Hall, Room 3121
915 Partners Way
Raleigh, NC 27606
Hola! I’m a first-year Master’s student in the Coastal and Computational Hydraulics Team (CCHT) at NC State. I am from Chile, a country with a long history of natural disasters, and some of them related to the ocean. As a kid, I always wanted to study civil engineering. After the devastating 2010 tsunami that hit Chile, hydraulics engineering came into my mind.
I did my undergrad studies at the Faculty of Physical and Mathematical Sciences (FCFM) at the Universidad de Chile. During my bachelor’s, I only had one course related to coastal engineering, but after that course, I decided to do my last summer internship at PRDW where I had my first experience doing numerical modeling of coastal processes. Right after that, I started my thesis under the supervision of two PRDW engineers and a faculty professor. The goal of the work was to develop a series of python scripts to correlate and correct the results of wave hindcast models with satellite altimetry.
After my graduation, I joined the numerical modeling team of PRDW of the Chilean office, where I worked from July 2016 to December 2021. I was involved in a large range of coastal processes studies such as wave climate, wave agitation, sediment transport, hydrodynamics, moored vessel’s dynamics, CFD, etc. The other area where I developed some expertise is in Python programming, I started coding for my thesis and never stopped, I’m a data science enthusiast! My experience on this can be split into three main areas: (1) managing environmental datasets, like waves, wind, temperature, salinity, etc, (2) development of scripts and tools written in python related to coastal engineering, and (3) applying machine and deep learning models or techniques to subjects related to coastal engineering.
I am currently working on the DHS project “Improving the Efficiency of Wave and Surge Models via Adaptive Mesh Resolution.”
My main areas of interest are numerical modeling of coastal processes, applying machine learning (ML) in coastal processes to improve the time-performance and accuracy of the numerical modeling. I’m also interested in statistics and probabilistic methods since they allow handling the uncertainties of the models. And at last, in the combination of GIS tools with both ML and the outputs of coastal models, and in improving the communication of the numerical modeling results to allow better risk management and a resilient use of the coastal environment.