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Large scale analysis of material properties through the use of machine learning


Co-PI: Ronaldo Cristiano Prati – UFABC – ronaldo.prati@ufabc.edu.br

The overall objective of this project is the development and application of machine learning algorithms and intelligent data analysis in large datasets of material properties, in property prediction tasks and discovery of knowledge that enable the screening of new materials on a large scale. For this, it is intended to apply these algorithms in public data repositories, as well as datasets collected from calculations of chemical-quantum properties performed by several members of the division.


Postdocs

Marinalva Soares – UNIFESP


PhD Student

Johnatan Mucelini – USP – Institute of Chemistry


MSc Student

Luis Cesar Azevedo – UFABC


Scientific Initiation Student

Danielle Lopes – ICMC – Institute of Mathematical and Computer Sciences
Felipe Calderan – UNIFESP – Science and Technology Institute

UNICAMP - Cidade Universitária
"Zeferino Vaz" Barão Geraldo
Campinas - São Paulo | Brasil
Rua Michel Debrun, s/n
Prédio Amarelo CEP: 13083-084
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