Research interests
I am a computational condensed-matter physicist specializing in the development of Monte Carlo and Quantum Monte Carlo algorithms, both for classical and quantum computers.
On the application side, I am particularly interested in the physics of materials under pressure and in creating new methods that bridge the size, time-scale, and accuracy gaps between current state-of-the-art simulation techniques and the requirements needed for quantitative predictions of phase diagrams and other physical properties of interest.
Moreover, I have worked in quantum computing since 2015, starting with analog platforms and later extending to digital quantum processors. My main research focus is understanding the origin of quantum speed-up and evaluating its practical limitations, since many textbook quantum algorithms do not provide the expected advantage once realistic constraints, such as gate times, error rates, and input–output bottlenecks, are taken into account.My interests in quantum algorithms are broad: I have developed or studied quantum approaches for sampling, optimization, chemistry, genomics, and finance.
I also work with machine learning, but only when it is genuinely needed to enable simulations that would otherwise be computationally infeasible.