Cy Pettit

About

Cy Pettit is a leading researcher in neuromorphic engineering and biologically inspired visual systems, with a focus on the Lobula Giant Movement Detector (LGMD)—a wide-field visual neuron in the locust nervous system that responds to looming objects. His major contributions include developing modified neural network models that enhance the LGMD’s ability to detect depth movement features, bridging computational neuroscience with hardware implementation. Notably, his 2010 paper on a modified LGMD model and its FPGA implementation (27 citations) demonstrates how biological principles can be translated into efficient, real-time collision detection circuits. His earlier 2009 work (18 citations) further refined the model, improving sensitivity to object velocity and proximity. Pettit’s research has significant implications for autonomous systems, robotics, and visual processing technologies, offering energy-efficient solutions inspired by insect neurobiology. His work is widely cited in both engineering and neuroscience communities, highlighting its interdisciplinary impact.

Research Focus

Key Achievements

Top Papers

1. 1
   A modified model for the Lobula Giant Movement Detector and its FPGA implementation

   27 citations · 2010
2. 2
   A modified neural network model for Lobula Giant Movement Detector with additional depth movement feature

   18 citations · 2009

Key Collaborators

Contact & Links