My expertise lies in hybrid quantum algorithms and experimental physics with superconducting and optical devices.
I am working on quantum and quantum-inspired algorithm development, covering quantum linear algebra, quantum optimization, tensor networks, simulation of complex systems, and algorithms for quantum sensing. Hybrid algorithm development includes searching for optimal resource allocation in quantum hardware with limited resources.
My hardware research includes engineering, manufacturing, developing, and operating microwave and optical systems for quantum information processing. Mainly, I focus on applications in computing, machine learning, and sensing. I develop both qudit-based devices and continuous-variable superconducting systems.
Record-size linear system solution on quantum computers
Optimization of work flows at the assembly line using quantum algorithms
Hybrid quantum algorithms realised in a memory-centric multiprocessing architecture for optimisation, machine learning and simulation
Image recognition using hybrid quantum neural networks with a novel tensor networks-based hyperparameter optimisation
Cover Picture of the July Issue
Enhanced sensing with optical components and quantum algorithms
Quantum sensing algorithm for multi-level artificial atoms in the presence of decoherence
Superconducting Quantum Optics
Quantum-limited superconducting amplifier with a straightforward fabrication process
High-quality generation and control of entanglement between multiple microwaves
Microwave superconducting entanglement generator with the record-breaking bandwidth
Numerical analysis of correlations between microwaves in a superconducting cavity
Hybrid Quantum Computation Architecture for Solving Quadratic Unconstrained Binary Optimization Problems
US 17482288 Filed Mar 31, 2022
US20220245498A1 Filed Feb 2, 2022