Guangzhi Tang is a researcher at imec, based in Eindhoven, the Netherlands. As a core member at imec advancing the SENECA neuromorphic processor, his current research focuses on neuromorphic and hardware-aware algorithm designs. Guangzhi has an extensive research experience in neuromorphic and brain-inspired computing, reinforcement learning, and their applications in real-world robotics problems.

Before joining imec, Guangzhi completed his PhD at Rutgers University in the United States, advised by Dr. Konstantinos Michmizos. During his PhD, he built the bridge between robotics and the brain, where robotics can provide real-world interactions and intelligent applications as testbeds for brain modeling, and the brain can inspire robust and efficient solutions for robotic problems. He has developed brain-inspired Spiking Neural Networks (SNN) solving a wide spectrum of robotics problems on neuromorphic processors with robustness, efficiency, and adaptivity.