IIT People Search

Research center
Interests
About

I am a physicist interested in atomistic simulations, particularly the development of computational methods and their applications to complex problems ranging from biophysics to physics and chemistry.

I studied at the University of Milan, and then I obtained a Ph.D. in Physics at the Swiss Federal Institute of Technology (ETHZ), Zurich, Switzerland. Currently, I am a Fellow in the  Atomistic Simulations group at the Italian Institute of Technology, Genova, Italy.

My research is focused on the integration of machine learning and enhanced sampling techniques to study rare events in physics, chemistry and biology. Examples are the generation of machine learning-based potentials for phase transitions and reactive events, as well as improving on enhanced sampling methods using deep learning and reinforcement learning schemes and the data-driven identification of collective variables.

Top Publications
2023
Bonati L., Trizio E., Rizzi A., Parrinello M.
A unified framework for machine learning collective variables for enhanced sampling simulations: mlcolvar
Journal of Chemical Physics, vol. 159, (no. 1)
2023
Bonati L., Polino D., Pizzolitto C., Biasi P., Eckert R., Reitmeier S., Schlogl R., Parrinello M.
The role of dynamics in heterogeneous catalysis: Surface diffusivity and N2 decomposition on Fe(111)
Proceedings of the National Academy of Sciences of the United States of America, vol. 120, (no. 50)
Article Journal
2022
Yang M., Bonati L., Polino D., Parrinello M.
Using metadynamics to build neural network potentials for reactive events: the case of urea decomposition in water
Catalysis Today, vol. 387, pp. 143-149
Article Journal
2021
Bonati L., Piccini G.M., Parrinello M.
Deep learning the slow modes for rare events sampling
Proceedings of the National Academy of Sciences of the United States of America, vol. 118, (no. 44)
2021
Rizzi V., Bonati L., Ansari N., Parrinello M.
The role of water in host-guest interaction
Nature Communications, vol. 12, (no. 1)
Scientific Talks
2023
Bonati L.
A unified framework for machine learning collective variables for enhanced sampling: mlcolvar
Biomolecular & Pharmaceutical Modelling Group, University of Geneva, 30th June 2023
Institute
2023
Bonati L.
Enhancing sampling with machine learning: from data-driven collective variables to realistic applications in heterogeneous catalysis
MolSSI Workshop: Machine Learning and Chemistry: Are We There Yet? 31 May - 2 June, University of Maryland (USA)
Workshop/Symposium
2023
Bonati L.
Machine learning collective variables for enhanced sampling
CECAM Workshop: Machine learning collective variables for enhanced sampling, 5th July 2023, EPFL (CH)
Workshop/Symposium
2023
Bonati L.
Machine learning collective variables for enhanced sampling simulations
Molecular Biophysics, Stockholm (remote talk), 12th December 2023
Institute
2023
Bonati L.
Machine learning & enhanced sampling: a synergistic interplay
CECAM workshop Quantum2, 29th November 2023, EPFL (CH)
Workshop/Symposium
Awards and Achievements
2023
Bonati L.
Premio Innovazione Italiana in Svizzera
2022
Bonati L.
ETH Silver medal for outstanding doctoral thesis
2021
Bonati L.
Best communications presented at 106th National Congress of the Italian Physical Society
2021
Bonati L.
Poster prize - Machine learning interatomic potentials: Young researcher’s tutorial workshop