A shared goal of neuroscience and robotics is to understand how systems can be built to move effectively and autonomously through the world. However, state-of-the-art algorithms for selecting and executing limb behaviors in robots are still quite primitive compared with neural controllers used by animals. To inform the design of artificial systems, we are investigating how the fly, Drosophila melanogaster, selects and controls its behaviors and how this process can be modulated by learning. I will discuss how we are pursuing this research program by developing and using machine learning, microscopy, and modeling.
Pavan Ramdya, Firmenich Next Generation Chair of Neuroengineering, is the Director of the Neuroengineering Laboratory at EPFL in Lausanne, Switzerland. Dr. Ramdya received his PhD in Neurobiology from Harvard University and then performed postdoctoral work in robotics and neurogenetics. His laboratory aims to draw inspiration from animals in order to design more intelligent artificial and robotic controllers. To accomplish this, they develop and use computational, engineering, genetic, and microscopy approaches to investigate how neural population dynamics, biomechanics, and gene expression sculpt limb-dependent behaviors in Drosophila melanogaster. In recognition of his work, he has been awarded an HFSP Career Development Award, a Swiss National Science Foundation Eccellenza Grant, the UNIL Young Investigator Award in Basic Sciences, and membership in the FENS-Kavli Network of Excellence.