Neuromimetic sensorimotor processing



The tactile features that generate the space of tactile inputs correspond to specific contact conditions governed by contact mechanics encoded by the brain. At a fundamental level these features correspond to mathematical invariants which are hypothesized to be learned by the neural circuits of the brain, and for which we recently provided experimental evidence. In this project, we will use a (artificial) deep neural network to learn these invariants from neural recordings and data obtained from stimulating artificial skin.

Expected Results

Identification of neural coding invariants of haptic sensing.


Host institution: Actronika

Enrolments (in Doctoral degree): Lunds Universitet


Vincent Hayward, Etienne Burdet

My name is Aruna Ramasamy. I am 23 years old. I pursued my undergraduate studies in Electronics and Communication Engineering in Anna University in my home country India. My inquisitiveness in Machine learning and Robots landed me in a master’s titled Computer vision, Robotics and Machine learning at University of Surrey in United Kingdom. I am always gravitated towards research as it provides a platform to explore and enrich one’s knowledge. Eventually, I found my way as a research student in the INTUITIVE project.