Alejandro De La Noval (Computer Science)
Alejandro De La Noval is a graduate student at Florida International University and a U.S. Department of Energy (DOE) Fellow currently pursuing a Master of Science degree in Computer Science. His interests mainly lie in computer science applications and machine learning. Alejandro plans to move to industry after getting his master’s degree, either in a private company or in public organization like DOE.
Alejandro’s research involves development on machine learning applications and algorithms that can help find relationships between groundwater wells and aquifer tube wells across and near the Colombia River shoreline at DOE’s Hanford Site in WA to aid in the goal of keeping hexavalent chromium below a certain threshold in the aquifer tube wells. He also focuses on development and maintenance of the Advanced Automated Machine Learning System (AAMLS), a system that allows domain experts to create models and predictions for their datasets from a centralized web application automatically, without any need for coding as the name of the system suggests. The AAMLS framework allows for continuous expansion and scaling for the system as more algorithms and techniques come into the main. Most recent efforts have been in adding computer vision capabilities across areas of classification, object detection, and anomaly detection.