Modeled After the Brain’s Neural Networks

Dr. Bhavin Shastri aims to create computers that operate millions of times faster than current technology. As the Canada Research Chair in Neuromorphic Photonic Computing, he focuses on using light (photonics) instead of traditional electronics to build energy-efficient processors. His research explores integrating nanophotonic devices that emulate brain-like neural networks, enabling new forms of computing such as neuromorphic photonic computing and, most recently, quantum neuromorphic computing, which combines quantum principles like entanglement and superposition with neural networks.

These photonic processors have the potential to address complex challenges in areas such as search optimization for drug discovery, compressed sensing in astronomy, deep neural network training for artificial intelligence (AI), resource optimization for wireless networks, which remain challenging even for supercomputers. To date, Dr. Shastri’s processors have found applications across various fields, including accelerating AI training, enabling real-time processing of radio signals to improve wireless and fiber-optic communications, and enhancing the efficiency (fidelity) of quantum networks.