The Computational Materials team is led by Haasa Gaddipati and Guilherme Nakamura.

Overview

The Computational Materials L&D Team uses modeling, simulation, and data analysis to explain structure-properties-processing relationships in engineering materials and their design. Our goals are to gain experience in the field of computation materials, learn how to develop machine learning models, and to have fun while doing so!

Learn and use common modeling, simulation, and data science methods in computational materials science to explain structure-properties-processing relations in materials.

In 2024-2025 school year, the group is developing machine learning models to interpret FTIR data using Convolutional Neural Network and Clustering Methods. This is a built up on the knowledge of data collection and model development from last year.

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