Liekang Zeng

Papers

Total Citations

H-Index

About

Liekang Zeng is a researcher specializing in edge computing, artificial intelligence, and robotics, with a particular focus on bridging the gap between computationally intensive AI tasks and resource-constrained edge environments. His work addresses one of the most pressing challenges in modern computing: enabling sophisticated AI models and robotic systems to operate efficiently in real-world, distributed settings. Zeng's most influential contribution explores the implementation of large-scale AI models for wireless networks through collaborative edge computing, garnering 19 citations since its 2024 publication — a remarkable trajectory suggesting significant community interest. This work tackles the practical deployment of big AI models, such as those powering voice assistants and autonomous robotics, within edge network architectures. His research in multi-robot Simultaneous Localization and Mapping (SLAM) further demonstrates his interdisciplinary expertise, with ColaSLAM — a real-time collaborative laser SLAM system accelerated by edge computing — earning 13 citations since 2021. This system directly addresses the tension between limited on-device computational resources and the intensive demands of multi-robot coordination. Collectively, Zeng's portfolio positions him as an emerging voice at the intersection of edge intelligence and autonomous systems, contributing foundational work that has meaningful implications for smart factories, robotics deployment, and next-generation wireless networks.