Peter McMahon

Peter McMahon is an Assistant Professor of Applied & Engineering Physics at Cornell University, where he has been since 2019. He received his PhD in Electrical Engineering and his postdoctoral training in Applied Physics at Stanford University.

McMahon's lab at Cornell studies computing with physical systems, both classical and quantum. In their investigations of classical systems, they aim to re-think the development of computers from the ground up, seeking to engineer new forms of computer that can operate at the speed and energy limits of what physics allows, with a focus on special-purpose analog computers for machine learning and optimization.

Some of their research results include the development and demonstration of training methods for physical systems, including optical systems, to act as physical neural networks (Nature 2022); the investigation of the ultimate limits to optical energy consumption in optical neural networks (Nature Communications 2022 & 2025); optical neural networks as preprocessors for image-sensing systems (Nature Photonics 2023), and the development of 2D-programmable optical waveguides for neural networks and for light manipulation more generally. They have also begun a recent thrust to develop unconventional nanoelectronic neural networks that borrow ideas from their work on optical neural networks. In quantum experiments, they work with both optics and microwaves, and study special-purpose quantum computers, and the marriage of quantum computing with quantum sensing in the pursuit of quantum computational-sensing advantage.

McMahon has been awarded Packard and Sloan Fellowships, an Office of Naval Research Young Investigator Program Award, a Google Quantum Research Award, and was selected as a CIFAR Azrieli Global Scholar in Quantum Information Science. In 2025, he received the Adolph Lomb Medal, “For demonstrating new forms of optical-physics-based computing machines, that surpass the standard von Neumann computers that we are all familiar with.”