Neuromorphic Circuits

Neuromorphic circuits for rapid learning and robust classification of olfactory signals

For my Master’s Thesis at Cornell University (2019-2020), I worked on developing a computational system to emulate the mammalian olfactory system using chemosensors, microcontrollers, and a machine learning classification algorithm. The goal of this system is to learn and classify new odors rapidly and robustly despite interference from other smells, much like our own olfactory system. More information on my thesis can be found in the link above!