FURI | Fall 2022

Characterization of Synaptic Electronic Devices for Brain-Inspired Computing Systems

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The project, a continuation from Spring 2022, seeks to answer the research question: Is hexagonal boron nitride (h-BN), a layered two-dimensional (2D) material, a promising candidate to implement brain-inspired (neuromorphic) computing devices and circuits? Research this semester will extend beyond testing the standalone behavior of individual memristor devices to investigating their collective ability to implement machine learning algorithms in a memristor array. The focus will be on performing dot-product operations, an action fundamental to nearly all neural network models. Comprehensive electrical measurements and statistical analysis will be used to demonstrate pulsed programming of a memristor array and its ability to carry out dot-product operations as part of executing a logistic regression classification task.

Student researcher

Sritharini Radhakrishnan

Electrical engineering

Hometown: Gilroy, California, United States

Graduation date: Spring 2023