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Guangzhi Tang is an Assistant Professor in the Department of Advanced Computing Sciences at Maastricht University. His research focuses on Edge Artificial Intelligence (AI) and Neuromorphic Computing, specifically on developing cost-effective, brain-inspired computing paradigms to address the high expenses associated with modern AI systems. He has extensive industry experience in hardware-aware optimization and reinforcement learning, which aims to facilitate practical applications in edge computing and robotics. Prior to joining academia, he worked at imec, a leading research and innovation center in nanoelectronics and digital technologies. He was a core member of the team advancing the SENECA neuromorphic processor and event-based neural networks, contributing to corresponding software developments. Dr. Tang completed his PhD in Computer Science at Rutgers University in the United States, where he was advised by Dr. Konstantinos Michmizos. His doctoral research focused on bridging robotics and brain science, developing robust, efficient, and adaptive Spiking Neural Networks (SNNs) to tackle a wide spectrum of challenges in robotics utilizing neuromorphic processors.
The School of Business and Economics (SBE) encompasses departments like Organization, Strategy, Entrepreneurship, Finance, and Economics.