Van-Lan Dao

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About

Van-Lan Dao is a leading researcher at the intersection of fog computing, industrial automation, and intelligent positioning systems. His work primarily focuses on enabling low-latency, on-demand resource architectures for industrial robotics, demonstrating how fog computing can overcome the limitations of cloud-based systems in factory and warehouse environments. His most impactful contribution, the 2020 paper "Enabling Fog-based Industrial Robotics Systems," has garnered 26 citations and is recognized as a foundational framework for deploying fog-enabled robotic applications in real-time industrial settings. In parallel, Dao has advanced indoor positioning technologies through deep neural networks, using channel impulse response data to achieve high-precision localization critical for factory automation and underground mining. His 2022 work in this area, while newer, addresses the pressing need for sub-threshold positioning errors in safety-critical industrial contexts. Presented at the IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), his research bridges theoretical models with practical deployment challenges, making him a key voice in the evolution of smart manufacturing and fog-based cyber-physical systems.