Max Robotics — Global Service Robot Directory + US Certification

About

Jing Pei is a pioneering researcher at the frontier of neuromorphic computing and intelligent robotics. Her work focuses on developing brain-inspired hardware and platforms that enable robots to process complex, dynamic environments with human-like efficiency. Pei’s major contributions center on creating scalable, hybrid neuromorphic systems that bridge the gap between biological neural networks and artificial computing. Her landmark 2022 paper on a neuromorphic chip with spatiotemporal elasticity for multi-intelligent-tasking robots (64 citations) introduces a novel architecture that allows robots to execute computationally intensive algorithms locally with low latency and high efficiency—a critical advance for real-time multitasking in unpredictable settings. Earlier, her 2020 work on a hybrid and scalable brain-inspired robotic platform (23 citations) laid foundational principles for integrating neural-inspired computing with robotic control. These contributions are driving the next generation of autonomous systems, enabling robots to handle multiple tasks simultaneously without relying on cloud computing. Pei’s research is not only advancing theoretical understanding but also delivering practical hardware solutions for agile, energy-efficient robotics.