Regular biography
Giuseppe Carleo is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Physics (PHY). His research focuses on computational quantum science, including machine learning for quantum physics, numerical methods for strongly-correlated quantum systems, quantum computing, and characterization of quantum hardware. He leads the Computational Quantum Science Laboratory (CQSL) at EPFL. Carleo's work includes the development of advanced numerical algorithms for quantum systems and the application of machine learning techniques to study quantum states and dynamics. He is also involved in teaching and mentoring PhD students in computational physics and quantum science.
Scholar-generated biography
Giuseppe Carleo is an Associate Professor of Physics at EPFL, specializing in strongly correlated quantum systems, variational methods, quantum dynamics, and quantum computing. His research focuses on developing and applying machine learning techniques to solve complex quantum many-body problems. Carleo's work includes neural-network quantum states, variational simulations, and quantum simulators, with applications in quantum chemistry and many-body dynamics. His publications explore topics such as quantum natural gradient, dissipative quantum dynamics, and ab initio electronic structure calculations. Carleo's contributions have advanced the use of artificial neural networks in quantum physics, particularly through tools like NetKet.