Kevin Rossi

University of Bergamo — Italy

Materials Science · Physical Sciences

18h-index1.0kcitations67works0.82yr avg
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Research Topics

Machine Learning in Materials Science(29), nanoparticles nucleation surface interactions(13), Catalytic Processes in Materials Science(12), Electrocatalysts for Energy Conversion(9), Computational Drug Discovery Methods(9)

Publications66 total

Replication Package for "Evaluating coverage and fault detection capability of scenarios for the validation of Asmeta specifications"
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
Replication Package for "Evaluating coverage and fault detection capability of scenarios for the validation of Asmeta specifications"
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
Machine Learning-Based Predictions of Henry Coefficients for Long-Chain Alkanes in One-Dimensional Zeolites: Application to Hydroisomerization
The Journal of Physical Chemistry C·2025Open Access
Bridging Structure and Activity in Nanocatalysts via Machine Learning and Global Structure Representations
arXiv (Cornell University)·2025· 1 citedOpen Access
Annealing Effects on Cu Migration in the Colloidal Synthesis of Pd-Chalcogenides Nanoheterostructures
Nano Letters·2025Open Access
Author response for "Uncertainty in the era of machine learning for atomistic modeling"
2025
Author response for "Uncertainty in the era of machine learning for atomistic modeling"
2025
Uncertainty in the era of machine learning for atomistic modeling
arXiv (Cornell University)·2025Open Access
Learning the Electrostatic Response of the Electron Density through a Symmetry-Adapted Vector Field Model
The Journal of Physical Chemistry Letters·2025· 4 citedOpen Access
Learning the Electrostatic Response of the Electron Density through a Symmetry-Adapted Vector Field Model
arXiv (Cornell University)·2025Open Access
Uncertainty in the era of machine learning for atomistic modeling
Digital Discovery·2025· 2 citedOpen Access
Bridging the complexity gap in computational heterogeneous catalysis with data-driven approaches
2024
Quantitative Description of Metal Center Organization and Interactions in Single‐Atom Catalysts (Adv. Mater. 5/2024)
Advanced Materials·2024· 2 citedOpen Access
Divide-and-conquer potentials enable scalable and accurate predictions of forces and energies in atomistic systems
Digital Discovery·2023· 6 citedOpen Access
Divide-and-conquer potentials enable scalable and accurate predictions of forces and energies in atomistic systems
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
Quantitative Description of Metal Center Organization and Interactions in Single‐Atom Catalysts
Advanced Materials·2023· 35 citedOpen Access
Dataset for Quantitative description of metal center organization in single-atom catalysts
2023Open Access
Dataset for Quantitative description of metal center organization in single-atom catalysts
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
Dataset for Quantitative description of metal center organization in single-atom catalysts
2023Open Access
Modeling and characterization of the nucleation and growth of carbon nanostructures in physical synthesis
Carbon Trends·2023· 5 citedOpen Access
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Frequent Co-authors

Francesca Baletto(18), Claudio Zeni(9), Raffaella Buonsanti(6), Núria López(5), Stefano de Gironcoli(5), Aldo Glielmo(5), Andrea Ruiz‐Ferrando(4), Dario Faust Akl(4), Javier Pérez‐Ramírez(4), Sharon Mitchell(4), Julien Lam(4), Anna Loiudice(3), Michele Ceriotti(3), Andrea Anelli(3), Akshay Krishna Ammothum Kandy(3), Alexis Raulin-Foissac(3), Nicholas A. DiNubile(3), Theodoros Pavloudis(2), Joseph Kioseoglou(2), Richard E. Palmer(2)