Max Robotics — Global Service Robot Directory + US Certification

About

Andrew A. G. Mattar is a leading researcher in motor learning and sensorimotor control, whose work has fundamentally shaped our understanding of how the brain acquires and generalizes motor skills. His key research areas include observational learning, dynamics learning, and the interplay between motor and sensory systems. Mattar’s most influential contribution, "Motor Learning by Observing" (2005, 410 citations), demonstrated that humans can acquire new motor skills simply by watching others, a finding with profound implications for rehabilitation and skill training. He further advanced the field by showing that motor learning is not purely local; his studies on generalization (e.g., 2007, 98 citations; 2010, 63 citations) revealed that learning can transfer across different movement amplitudes and contexts, challenging earlier models. Mattar also uncovered that motor learning induces sensory changes, altering the perceived position of the limb (2012, 57 citations), and explored how limb impedance shapes learning and generalization (2009, 29 citations). His work bridges computational theory and behavioral experiments, offering deep insights into neural plasticity. For students and researchers, Mattar’s research is essential reading for understanding the dynamic, adaptable nature of human motor control.