My main focus is on quantum algorithms, mainly (but not only) for healthcare and life sciences applications. With my collaborators I explore:

• Quantum generative models such as quantum generative adversarial networks, to enhance expressivity and trainability for drug discovery applications and data augmentation;
• Quantum simulations for NMR spectroscopy, both with quantum artificial intelligence and quantum (Hamiltonian) simulations;
• Quantum reservoir computing techniques, in particular for time series forecasting such as for wildfire prediction;
• Quantum optimization algorithms such as quantum approximate optimization algorithms (QAOA) and its variants, as well as quantum annealing approaches (applications for molecular docking, transport network, production scheduling, etc.).

A key aspect of our investigations is also to run our new algorithmic designs on actual quantum computing systems such as IBM superconducting-qubit computers or IonQ trapped-ion quantum computers, in order to compare performances and benchmark the end-user applications.