Ivan Herreros
Papers
10
Total Citations
68
H-Index
5
About
Ivan Herreros is a computational neuroscientist and roboticist whose work bridges theoretical neuroscience, artificial intelligence, and embodied robotics. His research centers on two major themes: cerebellar-inspired learning models and the computational characterization of consciousness. Drawing on the well-established Marr-Albus-Ito framework, Herreros has made significant contributions to understanding how the cerebellum enables motor skill acquisition, translating these biological insights into working robotic systems. His implementations span balance control, postural stabilization, motor sequence learning, and even robot painting — demonstrating the practical power of biologically grounded control architectures on platforms such as the iCub humanoid robot. Equally notable is Herreros's conceptual work on consciousness. His "Morphospace of Consciousness" papers (2017 and 2023), his most-cited contributions with 19 and 8 citations respectively, introduce a principled, information-theoretic framework for comparing biological minds with artificial systems — a timely contribution as debates around machine consciousness intensify. By mapping agents along axes of autonomic, computational, and social complexity, this framework offers researchers a rigorous vocabulary for evaluating conscious machines. Across roughly a decade of output, Herreros has carved out a distinctive intellectual niche at the intersection of neuroscience, robotics, and philosophy of mind.
Research Focus
Key Achievements
Top Papers
- 1The Morphospace of Consciousness19 citations · 2017
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- 8A Digital Neuromorphic Implementation of Cerebellar Associative Learning3 citations · 2012
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