Quantum computing researcher | Computational physicist

Gian Gentinetta

I am a computational physicist working on hybrid quantum-classical methods for simulating quantum many-body systems. My research combines quantum computing algorithms with modern classical methods, including machine learning and variational Monte Carlo.

Portrait of Gian Gentinetta

Bio

About me

Born and raised in Zurich, Switzerland, I obtained my B.Sc. and M.Sc. degrees in Physics from ETH Zurich. In my masters I focused on machine learning and quantum computing, culminating in a thesis on quantum machine learning performed at IBM Research Zurich. After an internship at IBM, I joined EPFL in 2022 to pursue a Ph.D. in computational quantum physics under the supervision of Prof. Giuseppe Carleo. My research focuses on hybrid quantum-classical algorithms for simulating quantum many-body systems. During my Ph.D., I had the opportunity to join Phasecraft in London for a summer internship, where I worked on quantum algorithms for quantum chemistry and materials science. When I'm not in the lab, I am usually found on Swiss trains, on top of a mountain, or swimming in a lake.

Research profile

Interests and methods

Quantum computation Quantum simulation Quantum many-body systems Near-term quantum algorithms Neural quantum states Tensor networks Variational Monte Carlo Machine learning