Short CV

Andrey Bagrov is an Assistant Professor in neuro- and data-inspired theory since September of 2021. He got his PhD degree from Leiden University (2015), where he has been working on application of string-theoretical methods to strongly correlated condensed matter systems.

Prior to joining the faculty of Radboud University, he held postdoctoral positions at the TCM group at Raboud University (2015-2019) and at the Materials Theory division at Uppsala University (2019-2021).

He is pursuing a number of research lines in mathematical and computational aspects of condensed matter physics with the main focus on many-body phenomena. Nowadays, his main field is machine learning applications to the study of correlation effects in lattice quantum Hamiltonians. Besides that, he is working on the holographic description of the finite density fermionic matter, developing the theory of structural complexity of natural patterns, and doing research on some topics in high-energy physics.