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About

Davide Zambrano is a researcher at the intersection of robotics, neuroscience, and artificial intelligence, whose work explores how biological principles can inform the next generation of intelligent machines. His research spans three key areas: the socio-economic impact of automation, bio-inspired sensory-motor control for humanoid robots, and neuromorphic systems for balance and spatial orientation. Zambrano’s most cited work, “How to compete with robots by assessing job automation risks and resilient alternatives” (35 citations), addresses the pressing societal question of how humans can adapt to an increasingly automated workforce. In robotics, he has made significant contributions by implementing bio-inspired models of the Vestibulo-Ocular Reflex (VOR) on the iCub robot, enabling human-like image stabilization and predictive visual tracking—even across occlusions. His work on a neuromorphic vestibular system (15 citations) further advances real-time hardware models for balance, drawing directly from mammalian biology. Zambrano’s research demonstrates a rare ability to bridge high-level societal concerns with low-level neural mechanisms, offering both practical robotic implementations and frameworks for human resilience in the age of AI.