Seminario - Big Data, Data Science, Artificial Intelligence: challenges, perspectives, outreach

Il seminario sarà tenuto dal Prof. Mario Rasetti, Presidente di ISI Foundation, nell'ambito del corso "Trends in Electronics M".

  • Data: 17 aprile 2018

  • Luogo: Aula 2.5, Scuola di Ingegneria e Architettura, viale Risorgimento 2, Bologna

Contatto di riferimento:

Recapito telefonico per contatti: + 39 051 209 3013

About the speaker

Mario Rasetti got his degree (MSc) in Nuclear Engineering and a second one in Mathematics at the Politecnico of Torino in 1967/68. He got his Ph.D. in Theoretical Physics at the CTH in Göteborg. From the very beginning, his scientific activity had an international profile (Yale, Coral Gables at Miami University, Princeton at the Institute for Advanced Studies). Back to Italy, after winning a national competition for a full professorship in theoretical physics at the Politecnico, he funded the ISI Foundation. He is author or co-author of more than 250 papers on scientific journals and 4 books. He has been awarded with the following prizes and honors:

1) Majorana Prize for Theoretical Physics, 2009
2) Volta Medal for Science, 2010
3) Outstanding Referee, American Institute of Physics, 2009

The most relevant fields of research and contribution are: quantum theory of vortices; statistical mechanics of classical spin models; high Tc superconductivity: metal-insulator transition; strongly interacting fermion systems; non-abelian crystallography; generalized coherent states and  non-classical states of light; number-phase problem; decoherence-free states for quantum computation; holonomic quantum computation; single-boson realization of Virasoro algebra; quantum algorithms for links; knots and 3-manifold topological invariants; dynamical algebras (super, quantum) in condensed matter physics; quantum combing of parenthesized groups; quantization of dynamical systems over discrete sets; Spin Network Quantum Automaton scheme for quantum computation; quantum solitons and Peierls deformation; topological methods in data science.