Area of research
Artificial Intelligence · Electrical and Electronic Engineering
Research interest
Research interests include Neural Networks and Reservoir Computing, Quantum Information and Cryptography, Quantum Computing Algorithms and Architecture, and Photonic and Optical Devices.
Programmable on-chip nonlinear photonics.
Exponential advantage in quantum sensing of correlated parameters
Hamiltonian-reconstruction distance as a success metric for the variational quantum eigensolver
Training of physical neural networks
Quantum-limited stochastic optical neural networks operating at a few quanta per activation
Roadmap on Neuromorphic Photonics
Programmable on-chip nonlinear photonics
Training of physical neural networks.
Synthetic High Angular Momentum Spin Dynamics in a Microwave Oscillator
Quantum-limited stochastic optical neural networks operating at a few quanta per activation.
Arbitrary control over multimode wave propagation for machine learning
An integrated microwave neural network for broadband computation and communication
An integrated microwave neural network for broadband computation and communication
Roadmap for unconventional computing with nanotechnology
Roadmap for unconventional computing with nanotechnology
Quantum variational solving of nonlinear and multidimensional partial differential equations
Quantum variational solving of nonlinear and multidimensional partial differential equations
Microwave signal processing using an analog quantum reservoir computer
Nonlinear computation with linear systems
Microwave signal processing using an analog quantum reservoir computer.
The physics of optical computing
The physics of optical computing
Image sensing with multilayer nonlinear optical neural networks
Image sensing with multilayer nonlinear optical neural networks
Programmable large-scale simulation of bosonic transport in optical synthetic frequency lattices
Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions
Linear-depth quantum circuits for loading Fourier approximations of arbitrary functions
Quantum-noise-limited optical neural networks operating at a few quanta per activation
Deep physical neural networks trained with backpropagation
Ising machines as hardware solvers of combinatorial optimization problems