Ultra-low-energy skyrmion-based learning automata element for adaptive edge intelligence

Santhosh Sivasubramani

Submission Type: I want my submission to be considered for both oral and poster presentation.

Keywords: Magnetic skyrmions, Ultra-low-energy computing, Edge AI hardware, In-memory learning, Tsetlin Machine

TL;DR: This paper introduces a physics-informed, skyrmion-based hardware primitive for learning automata, bridging nanomagnetism and interpretable machine learning to enable energy-efficient AI acceleration at the edge.

Confirmation Of Submission Requirements: I submit a previously published paper. It was published in an archival peer–reviewed venue on or after September 1st 2025, I specify the DOI in the field below, and I submit the camera-ready version of the paper.

DOI: https://doi.org/10.1088/1361-6528/ae1a90

Submission Number: 167