Research Assistant
Department of Applied Science and Technology (DISAT)
Profile
Research interests
Biography
I work with Molecular Dynamics simulations, usually with coarse-granied models, in the field od supramolecular self-assembly. I also work in developing tools of data analysis devoted to the analysis of the simulation trajectories.
Research topics
- Data analysis tools development.
- Molecular Dynamics simulations for supramolecular self-assembly.
Skills
ERC sectors
Publications
Latest publications View all publications in Porto@Iris
- Martino, Simone; Doria, Domiziano; Lionello, Chiara; Becchi, Matteo; Pavan, Giovanni M (2025)
A data driven approach to classify descriptors based on their efficiency in translating noisy trajectories into physically-relevant information. In: MACHINE LEARNING: SCIENCE AND TECHNOLOGY, vol. 6. ISSN 2632-2153
Contributo su Rivista - Doria, Domiziano; Martino, Simone; Becchi, Matteo; Pavan, Giovanni M. (2025)
Data-driven assessment of optimal spatiotemporal resolutions for information extraction in noisy time series data. In: JOURNAL OF CHEMICAL PHYSICS ONLINE, vol. 162. ISSN 1089-7690
Contributo su Rivista - Lionello, Chiara; Becchi, Matteo; Martino, Simone; Pavan, Giovanni M. (2025)
Relevant, Hidden, and Frustrated Information in High-Dimensional Analyses of Complex Dynamical Systems with Internal Noise. In: JOURNAL OF CHEMICAL THEORY AND COMPUTATION, vol. 21, pp. 6683-6697. ISSN 1549-9618
Contributo su Rivista - Becchi, Matteo; Fantolino, Federico; Pavan, Giovanni M. (2024)
Layer-by-layer unsupervised clustering of statistically relevant fluctuations in noisy time-series data of complex dynamical systems. In: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 121. ISSN 0027-8424
Contributo su Rivista - Becchi, Matteo; Capelli, Riccardo; Perego, Claudio; Pavan, Giovanni M.; Micheletti, ... (2022)
Density-tunable pathway complexity in a minimalistic self-assembly model. In: SOFT MATTER, vol. 18, pp. 8106-8116. ISSN 1744-683X
Contributo su Rivista