Alumni of the Condensed Matter Theory Curriculum

Name Year Supervisors Thesis
Riccardo Bertossa 2022
  • Stefano Baroni
Theory, codes, and numerical simulation of heat transport in multicomponent systems
Fabio Caleffi 2022
  • Massimo Capone
  • Alessio Recati
  • Iacopo Carusotto
Collective Modes and Strong Correlations from a Quantum Gutzwiller Ansatz
Alberto Scazzola 2022
  • Massimo Capone
Interplay between electron-phonon interaction and electron-electron repulsion in multiorbital Hubbard models
Martino Stefanini 2022
  • Alessandro Silva
  • Massimo Capone
Studies on impurities moving in Tomonaga-Luttinger Liquids
Davide Tisi 2022
  • Stefano Baroni
Green-Kubo simulation of transport properties: from ab initio to neural-network molecular dynamics
Adu Offei-Danso 2022
  • Giuseppe Santoro
  • Ali Hassanali
  • Alex Rodriguez
Unsupervised Learning of the Structure and Dynamics of Liquid Water
Federica Surace 2021
  • Marcello Dalmonte
  • Alessandro Silva
Lattice gauge theories and constrained systems: from quantum simulation to non-equilibrium dynamics
Cristiano Malica 2021
  • Andrea Dal Corso
From ab-initio thermodynamics to quasi-harmonic thermoelastic properties of crystals: A new workflow and selected applications
Matteo Seclì 2021
  • Massimo Capone
  • Iacopo Carusotto
  • Marco Schiró
Topology and Nonlinearity in Driven-Dissipative Photonic Lattices: Semiclassical and Quantum Approaches
Claudia Artiaco 2021
  • Michele Fabrizio
  • Antonello Scardicchio
Quantum effects in glasses at ultra-low temperatures
Lucas Kohn 2021
  • Giuseppe Santoro
Simulating non-equilibrium dynamics and finite temperature physics: efficient representations for matrix product states
Mattia Angeli 2020
  • Michele Fabrizio
Emergent phenomena in twisted Van der Waals materials
Karla Baumann 2020
  • Massimo Capone
Mott transition, topology, and magnetism of interacting fermions in confined geometries
Lorenzo Crippa 2020
  • Massimo Capone
  • Adriano Amaricci
Local and non-local correlations in Topological Insulators and Weyl Semimetals
Matteo Ferri 2020
  • Simone Piccinin
  • Stefano Fabris
  • Stefano de Gironcoli
Ab-initio Characterization of a Novel Photocathode for Water Splitting: Bulk and Surface Properties of CuFeO2
Claudio Genovese 2020
  • Sandro Sorella
Geminal Power in QMC
Jacopo Marcheselli 2020
  • Stefano Baroni
  • Marco Garavelli
  • Stefano Corni
Simulating Plasmon Enhancement of Optical Properties in Hybrid Metal-Organic Nanoparticles
Silvia Pappalardi 2020
  • Rosario Fazio
  • Alessandro Silva
Entanglement dynamics and chaos in long-range quantum systems
Giulia Piccitto 2020
  • Alessandro Silva
Cluster mean-field dynamics of the long-range interacting Ising chain
Yusuf Shaidu 2020
  • Stefano de Gironcoli
Interatomic Potential for Li-C Systems from Cluster Expansion to Artificial Neural Network Techniques
Andrea Urru 2020
  • Andrea Dal Corso
Lattice dynamics with Fully Relativistic Pseudopotentials for magnetic systems, with selected applications
Matteo Wauters 2020
  • Giuseppe Santoro
Adiabatic approaches to non-equilibrium systems: Topology, Optimization, and Learning
Francesco Ferrari 2019
  • Federico Becca
Static and dynamical properties of frustrated spin models
Martina Teruzzi 2019
  • Giuseppe Santoro
  • Erio Tosatti
  • Alessandro Laio
Markov State Modeling of 2D Nanofriction
Muhammad Nawaz Qaisrani 2019
  • Stefano Baroni
  • Ali A Hassanali
  • Ralph Gebauer
A Multi-scale Approach to Studying the Complexity in Glutamine Aggregates: Structure, Dynamics and Electronic Properties
Glen Bigan Mbeng 2019
  • Giuseppe Santoro
Quantum annealing and digital quantum ground state preparation algorithms
Deepak Bahadur Karki 2019
  • Michele Fabrizio
  • Mikhail Kiselev
Multi-color Fermi-liquid theory of quantum transport through a multilevel Kondo impurity
Daniele Guerci 2019
  • Michele Fabrizio
  • Massimo Capone
Beyond simple variational approach for strongly electron systems
Luca Arceci 2019
  • Giuseppe Santoro
Dissipation effects in driven quantum many-body systems
Juraj Hasik 2019
  • Federico Becca
Towards next-generation methods to optimize two-dimensional tensor networks: Algorithmic differentiation and applications to quantum magnets