MORE | Spring 2024

Integrated Machine Learning Approaches for Advanced Analysis of Semiconductor Materials

FURI Semiconductor Research theme icon

The performance of most electronic materials is capped by their inherent properties. Analyzing these materials is a complex, time-consuming task. This research employs novel machine learning techniques to enhance efficiency, consistency, and quality control in line with industry advancements. By streamlining analysis and eliminating manual feature engineering, it offers an automated, efficient solution for material characterization and nanoscience research. The insights gained will advance our understanding of nanoscale structures and material interactions, benefiting various industries like semiconductors, biomechanics, materials science, and electronics.

Student researcher

Aishwarya Katkar

Mechanical engineering

Hometown: Tempe, Arizona, United States

Graduation date: Spring 2024