Philippe Gaussier
École Nationale Supérieure de l'Électronique et de ses Applications, Centre National de la Recherche Scientifique, CY Cergy Paris Université, Equipes Traitement de l'Information et Systèmes, Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, Institut Universitaire de France, Université Paris-Seine, Neuro-Dol, École Polytechnique Fédérale de Lausanne, Laboratoire Traitement du Signal et de l'Image
Papers
110
Total Citations
2,013
H-Index
23
About
Philippe Gaussier is a pioneering French researcher in computational neuroscience and autonomous robotics, whose work sits at the rich intersection of biological intelligence and artificial systems. Based at ENSEA (École Nationale Supérieure de l'Électronique et de ses Applications), Gaussier has dedicated his career to understanding how cognitive capabilities — navigation, imitation, communication, and social learning — can emerge from biologically inspired neural architectures implemented in real robotic systems. His most influential contributions explore how robots can learn through imitation without having imitation explicitly programmed, instead allowing it to emerge from perceptual ambiguity and perception-action coupling — a landmark idea developed across several highly cited papers totaling over 300 citations alone. His work on hippocampal modeling, view cells, and place cells (145 citations) has advanced our understanding of spatial cognition and visual navigation, while his grid cell architecture research bridges cutting-edge neuroscience with mobile robotics. Gaussier's research consistently demonstrates that social behaviors — from gestural communication to facial expression recognition — can develop organically in robots through developmental, bottom-up learning processes. More recently, his team has explored how robots can individuate people through imitative encounters, connecting artificial systems to infant developmental psychology. With a body of work spanning three decades and hundreds of citations, Gaussier remains a uniquely creative voice in embodied cognitive robotics.
Research Focus
Key Achievements
Top Papers
- 1
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- 3Learning and communication via imitation: an autonomous robot perspective118 citations · 2001
- 4PerAc: A neural architecture to control artificial animals91 citations · 1995
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- 6Toward communication67 citations · 2004
- 7Visual navigation in an open environment without map56 citations · 2002
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