My name is Guangzhi Tang (Pronunciation: g uu ung, j ee, t ah ng). I am a PhD candidate in computer science at Rutgers University and a member of the Computational Brain Lab (ComBra). My main research interests are neurorobotics and neuromorphic computing. More specifically, developing Spiking Neural Networks (SNN) on neuromorphic processors to solve robotic problems with robustness, efficiency, and adaptivity.

We think the most crucial task for neuromorphic computing is to build the bridge between robotics and brain science. Robotics can provide real-world interactions and intelligent applications as testbeds for brain modeling, and brain theory can inspire robust and efficient solutions for robotic problems. By using SNN, we believe questions of both areas can be answered simultaneously.

Before starting my PhD, I received my MSc degree in computer science from Rutgers University with the thesis targeting SNN model of brain’s navigational system solving cue integration, and my BSc degree in computer science from Nanjing University with the thesis targeting adaptive algorithm for imperfect extensive game.

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