2° Encontro de Inteligência Artificial: Machine Learning School for Materials (2023)

The event aims to bridge the gap between the scientific community working in Machine Learning and Materials Science and the future generation of scientists interested in this field. The main objective is to consolidate the field of Machine Learning for Materials in Brazil.

Event format

The event will be hybrid (in-person + online) and will last two days. It will include hands-on tutorials at the undergraduate level and a poster session. There is a registration fee of 50,00 reais for in-person attendance, while there is no registration fee for the online modality.

Scientific committee

Adalberto Fazzio (Ilum/CNPEM)
Amauri J. de Paula (Ilum/CNPEM)
Daniel Roberto Cassar (Ilum/CNPEM) CHAIR
James Mores de Almeida (Ilum/CNPEM) CHAIR
Felipe D. C. de Lima (Ilum/CNPEM)
Gustavo Dalpian (UFABC)

Agenda

September 18

Speaker/Activity Starts at Ends at
Oppening 8:45 9:00
Maicon Lourenço: Artificial Intelligence for Chemistry and Materials Science – from Automatic Structural Determination to Prediction of New Materials 9:00 10:30
Coffee break 10:30 11:00
Maicon Lourenço: Artificial Intelligence for Chemistry and Materials Science – from Automatic Structural Determination to Prediction of New Materials 11:00 12:00
Lunch 12:00 14:00
Daniel CassarFinding new materials with AI (and learning something new in the process) 14:00 15:30
Coffee break 15:30 16:00
Daniel CassarFinding new materials with AI (and learning something new in the process) 16:00 17:00
Poster session 17:00 18:00

September 19

Speaker/Activity Starts at Ends at
Marcos Quiles: Introduction to deep learning and its application in chemistry and materials. 9:00 10:30
Coffee break 10:30 11:00
Marcos Quiles: Introduction to deep learning and its application in chemistry and materials. 11:00 12:00
Lunch 12:00 14:00
Gabriel SchlederData science without data? Solving partial differential equations of quantum systems using Physics-informed Neural Networks (PINNs) 14:00 15:30
Coffee break 15:30 16:00
Gabriel SchlederData science without data? Solving partial differential equations of quantum systems using Physics-informed Neural Networks (PINNs) 16:00 17:00