Photonic Computing and Brain-Computer Interfaces

My lab’s research projects involve developing integrated silicon photonic devices for both brain-computer interfaces and artificial intelligence computing hardware. My focus will be developing photonic computing hardware that is neuromorphic, meaning it emulates the way our brains work. My main objectives will involve developing and characterizing integrated photonic chip designs that involve functional and trainable light-based neural networks, such as networks comprised of silicon waveguides and phase change materials. Working with photonics provides the computing benefits of high bandwidth and fast signaling properties, so these photonic neural networks can theoretically complement traditional electronic circuits to lead to machine learning and artificial intelligence that is orders of magnitude faster and more energy efficient than today, enabling data processing in data-intensive and power-critical applications such as edge-computing.

Faculty Supervisor:

Aimy Bazylak

Student:

Partner:

Max Planck Institute of Microstructure Physics

Discipline:

Engineering

Sector:

Nanotechnology; Technology; Biotechnology

University:

University of Toronto

Program: