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About

Dong Seon Cheng is a leading voice at the intersection of edge computing and artificial intelligence, with a primary focus on Tiny Machine Learning (TinyML) and the safety architectures of Industry 4.0. His most impactful contribution is a comprehensive machine learning-oriented survey on TinyML, which has garnered 117 citations since 2024. This work has been pivotal in defining how resource-constrained IoT hardware can be jointly designed with lightweight AI software, effectively democratizing intelligence for embedded devices. Cheng’s research addresses the critical challenge of bringing powerful learning capabilities to millimeter-scale, battery-powered systems without relying on cloud connectivity. Additionally, his case study on the ICE Laboratory explores the dual imperatives of safety and privacy in connected manufacturing environments, contributing to the discourse on human-centric Industry 4.0. By bridging the gap between theoretical AI efficiency and practical hardware constraints, Cheng’s work is essential reading for students and researchers developing next-generation autonomous systems, wearable health monitors, and smart industrial sensors.