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About

Vivian M. De La Cruz is a cognitive robotics researcher whose work sits at the fascinating intersection of developmental psychology, embodied cognition, and artificial intelligence. Her research focuses primarily on how robots can model human cognitive development, with particular emphasis on numerical cognition, language learning, and mental imagery in robotic systems. De La Cruz's most significant contributions center on using humanoid robots — particularly the iCub platform — to investigate how children acquire mathematical skills. Her highly cited 2014 work on finger counting and number cognition (48 citations) demonstrated that motor-based representations of number, grounded in finger-counting activity, can be meaningfully replicated in cognitive robots, lending computational support to developmental and neuroscientific theories. This research thread continued through her explorations of the transition from concrete to symbolic numerical reasoning, accumulating over 100 citations across related publications. Beyond numeracy, De La Cruz has explored mental imagery and motor learning in robotics, examining how mental practice influences movement execution. Her 2015 deep learning study introduced biologically inspired neural architectures to model number cognition across cultures using the iCub. Through combining computational modeling with developmental theory, her work provides researchers and students a compelling framework for understanding how embodied experience shapes human-like cognitive abilities.