Max Robotics — Global Service Robot Directory + US Certification

About

Jonathan Tapson’s research lies at the intersection of computational neuroscience and robotics, with a focus on spiking neural networks, neuromorphic hardware, and biologically inspired cognitive systems. His most cited work, “Optimization Methods for Spiking Neurons and Networks” (52 citations), provides foundational techniques for designing spiking neural circuits used in robotic locomotion, neuroprosthetics, and sensory processing. Tapson is also known for pioneering implementations of the Neural Engineering Framework (NEF) on digital hardware, including a compact neural core that enabled large-scale cognitive models like SPAUN. A standout achievement is his live demonstration of “Spiking ratSLAM” (21 citations), which modeled rat hippocampus place, grid, and border cells using SpiNNaker hardware on a mobile robot—bridging neural theory with real-world robotic navigation. His work extends to humanoid robotics, including self-collision detection and motion transfer for service robot arms. More recently, Tapson introduced the Salience-Affected Artificial Neural Network (SANN), which models neuromodulatory effects like dopamine and noradrenaline to enable one-time learning, a step toward more adaptive and efficient neural systems. With contributions spanning from neural optimization to embodied cognition, Tapson’s research continues to shape how we build intelligent, brain-inspired machines.