Involved in multiple research projects on using physical systems for computation, particularly focusing on optimization, quantum simulation, and machine learning.
Research Experience
Conducts research at the School of Applied and Engineering Physics at Cornell University, exploring new ways of computation that offer benefits over traditional CMOS-based von Neumann processors. Also studying the potential applications of quantum computers in the near term (noisy, intermediate-scale machines) and long term (fault-tolerant machines).
Background
Research interests include experimental and theoretical quantum, photonic, and neuromorphic computing. Focuses on exploring different physical platforms for quantum information processing, such as spins in semiconductor devices, superconducting circuits, and quantum-optical systems.
Miscellany
Shows a keen interest in how unconventional computing technologies might impact real-world computations.