Amaru is completing her undergraduate degree in Physics with minors in Computer Science and Latin American studies. Her interest in physical behavior and planetary science, along with her knowledge of computer science, has allowed her to participate in previous ATOMS lab research.

In her previous work, Amaru was involved in a project modeling the relationship between landfill-leachate parameters and methane concentration in biogas. Additionally, she explored the impact of various topological and physical parameters on simulated wind turbine farms. To optimize wind turbine layout, she employed and modified Python libraries.

Currently, Amaru’s research focuses on analyzing the spatial distribution of contaminants in Fort William First Nation. She employs vector-similarity-based Self-Organizing Maps to achieve this, integrating recently acquired geophysical data with historical hydrogeochemical information. The ultimate objective is to compare these findings with results from probabilistic machine learning methods, specifically Gaussian Mixture Modelling and Generative Topographic Maps.