Guangzhi Tang (G.)

I am an Assistant Professor in Edge Computing in the Department of Advanced Computing Sciences at Maastricht University. My research in Edge AI and Neuromorphic Computing develops cost-effective, brain-inspired computing paradigms to tackle the high expenses of modern AI systems. I also have extensive research and industry experience in hardware-aware optimization and reinforcement learning, focusing on practical applications in edge computing and robotics.

Before joining academia, I was a researcher at imec, the world-leading research & innovation center for nanoelectronics and digital technologies. I was a core member at imec advancing the SENECA neuromorphic processor, event-based neural networks, and the corresponding software. I completed my PhD at Rutgers University in the United States, advised by Dr. Konstantinos Michmizos. During my PhD, I bridged robotics and brain science by developing robust, efficient, and adaptive brain-inspired Spiking Neural Networks (SNNs) that address a wide spectrum of robotics challenges on neuromorphic processors.

Expertises
  • Edge AI
  • Sustainable AI
  • Neuromorphic Computing
  • Efficient Deep Learning
  • Robotics
  • Brain-inspired Computing
  • AI-enabled Automation
Career history