Nick Wicklund

Research overview

Nick researches neural network-based predistorters and channel equalizers for optical communications. His work treats the optical link as a physical plant whose device dynamics, fabrication history, channel behaviour, and receiver constraints all shape the signal that can be recovered.

The project connects photonic-device and link modelling with compact learned compensation. Its purpose is not to use intelligence as decoration, but to determine when a hardware-aware learned block can correct an impairment more effectively than a conventional alternative.

Education and experimental background

Nick holds an MSc in Physics from McGill University and a BEng in Electrical Engineering with a Physics minor from Carleton University. His graduate physics work examined helium flow through nanopores using ultrahigh-vacuum systems, custom experimental fixtures, sensitive measurement, and fabricated devices.

Fabrication and characterization skills

• Electron-beam and optical lithography
• Thin-film deposition, spin coating, wet chemistry, and plasma processing
• Deep reactive-ion etching
• SEM, TEM, optical microscopy, and profilometry
• Electrical metrology, vacuum systems, and automated technical reporting
• Embedded systems and digital verification

Industry experience

Nick has worked in nanofabrication engineering, SEM and failure analysis, embedded systems, and digital verification. These roles give his optical-communications research a strong process-and-measurement perspective.

Current direction

The current focus is process-aware modelling of microring-resonator links and the design of compact local neural predistortion or receiver-equalization strategies that remain credible under realistic physical and implementation constraints.