I specialise in the convergence of quantum information, quantum energetics, data, complexity science, focusing on developing quantum-enhanced agents, models, neural networks and model reduction. I aim to leverage quantum better to understand complex data, improve predictive accuracy, enhance energy efficiency and devise sophisticated strategies for shaping the future, and to do so using less memory, data and energetic resources than what is classically possible. Potential applications include analysing rare events in finance, processing real-time data streams, quantum-enhanced energy harvesters and quantum-enhanced AI.

Selected publications:

• Implementing quantum dimensionality reduction for non-Markovian stochastic simulation, Nature Communications 14 (1), 2624 (2023)
• Practical unitary simulator for non-Markovian complex processes, Physical Review Letters 120 (24), 240502 (2018)
• Interfering trajectories in experimental quantum-enhanced stochastic simulation, Nature Communications 10 (1), 1630 (2019)
• Quantum adaptive agents with efficient long-term memories, Physical Review X 12 (1), 011007 (2022)
• Quantum Mechanics can reduce the complexity of classical models, Nature Communications 3, 762 (2012)