Max Robotics — Global Service Robot Directory + US Certification

About

Runmian Chang is an emerging researcher specializing in intelligent robotics, warehouse automation, and machine learning-driven optimization systems. Their work sits at the intersection of artificial intelligence and logistics technology, addressing critical challenges in modern supply chain operations driven by the explosive growth of global e-commerce. Chang's most significant contributions center on applying machine learning and reinforcement learning algorithms to enhance the performance of automated warehouse robots. Their highly cited 2025 study on machine learning for picking and packing operations — accumulating 23 citations within its publication year — demonstrates how integrating intelligent control systems can substantially improve both operational efficiency and motion execution precision. Complementing this, their research on reinforcement learning-based task scheduling explores how cloud computing and advanced AI can overcome existing limitations in robotic intelligence. Across their published portfolio, Chang has consistently advanced the use of deep learning and reinforcement learning to boost picking accuracy, reduce system errors, and maximize throughput in automated fulfillment environments. With a total citation count exceeding 50 across six publications — all released in 2024–2025 — Chang has quickly established a focused and impactful research trajectory, making their work highly relevant to researchers and practitioners building next-generation smart warehouse systems.