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Eran Lustig and Moti Segev, along with Or Yair and Ronen Talmon from the faculty of  electrical engineering, developed and demonstrated experimentally a machine-learning tool for identifying unexpected topological phase transitions in experimental data. Their research was published in Physical Review Letters.

 

The work was covered in physics world.