Peter McMahon

Peter McMahon is an Associate Professor in the School of Applied and Engineering Physics at Cornell University. He holds a Ph.D. in Electrical Engineering from Stanford University (2014) and a B.S. in Electrical and Computer Engineering from the University of Cape Town. His research focuses on unconventional computing paradigms, including quantum computing, photonic computing, and neuromorphic systems. He explores quantum information processing in platforms like semiconductor spins, superconducting circuits, and optical systems, with applications in optimization, machine learning, and quantum simulation.

Education

• B.S., Electrical and Computer Engineering, University of Cape Town (2003–2008)
• M.S., Electrical Engineering, University of Cape Town (2003–2008)
• M.S., Computer Science, University of Cape Town (2003–2008)
• M.S., Electrical Engineering, Stanford University (2008–2010)
• Ph.D., Electrical Engineering, Stanford University (2010–2014)
• Postdoctoral Fellow, Applied Physics, Stanford University (2014–2019)

Research Interests

His lab investigates the physics of computation, emphasizing quantum and classical alternatives to conventional von Neumann architectures. Key areas include quantum annealing, photonic neural networks, and neuromorphic systems. McMahon’s work bridges theoretical foundations and experimental implementations, with a focus on leveraging physical systems for computational advantage in optimization and machine learning.

Awards

• Optica Adolph Lomb Medal (2025)
• IUPAP Early Career Scientist Prize (2022)
• Office of Naval Research Young Investigator Award (2022)
• Sloan Research Fellowship (2022)
• Packard Fellowship in Science and Engineering (2021–2026)
• CIFAR Azrieli Global Scholar (2020–2022)

Advising & Grants

McMahon oversees a research group focused on experimental and theoretical exploration of quantum technologies. His funding includes awards from the Packard Foundation, Office of Naval Research, and Google Quantum Research. He collaborates with industry and academic partners to advance quantum and photonic computing hardware.

Labs & Teams

He leads the McMahon Lab, which develops novel optical and quantum computing platforms. The lab collaborates on projects such as optical neural networks and quantum annealing systems, with applications in imaging, optimization, and quantum simulation.