Alexandre Pitti

About

Alexandre Pitti is a computational neuroscience and robotics researcher whose work sits at the intersection of brain-inspired computing, sensorimotor integration, and embodied cognition. His most influential contribution, "Information Transfer at Multiple Scales" (2007, 92 citations), established foundational methods for mapping interaction networks in complex systems, demonstrating his early interest in how information flows across coupled subsystems. Building on this, Pitti has made significant strides in understanding how biological principles can be translated into robotic systems, exploring mechanisms such as gain-field modulation — a neural computation found in the parietal cortex — to enable robots to perform visuomotor transformations and spatial perception across multiple reference frames. His research on agency and contingency perception sheds light on how self-awareness and motor authorship emerge in both infants and artificial neural networks. Pitti has also advanced tactile robotics, developing neural controllers for compliant robotic arms guided by artificial skin, and pioneered tensegrity-based vertebral column robots for postural balance. His editorial leadership on body representations and peripersonal space further reflects his role as a unifying voice in the broader community studying embodied intelligence in humans, animals, and robots.

Research Focus

Key Achievements

Top Papers

1. 1
   Information transfer at multiple scales

   92 citations · 2007
2. 2
   Contingency Perception and Agency Measure in Visuo-Motor Spiking Neural Networks

   29 citations · 2009
3. 3
   Touch-based admittance control of a robotic arm using neural learning of an artificial skin

   19 citations · 2016
4. 4
   Creating and modulating rhythms by controlling the physics of the body

   16 citations · 2010
5. 5
   Gain-field modulation mechanism in multimodal networks for spatial perception

   15 citations · 2012
6. 6
   Synergistic control of a multi-segments vertebral column robot based on tensegrity for postural balance

   14 citations · 2018
7. 7
   Exploiting the gain-modulation mechanism in parieto-motor neurons: Application to visuomotor transformations and embodied simulation

   13 citations · 2014
8. 8
   Brain-Inspired Coding of Robot Body Schema Through Visuo-Motor Integration of Touched Events

   13 citations · 2019
9. 9
   Neural model for learning-to-learn of novel task sets in the motor domain

   11 citations · 2013
10. 10
    Editorial: Body Representations, Peripersonal Space, and the Self: Humans, Animals, Robots

    9 citations · 2020

Key Collaborators

Contact & Links