Machine Learning, Complex Networks and Multidimensional Time Series

• Grant number: 24/17823-4
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: December 01, 2024
• End date: November 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Alexandre Plastino de Carvalho
• Grantee: Ronald Chiesse de Souza
• Host Institution: Instituto de Computação. Universidade Federal Fluminense (UFF). Ministério da Educação (Brasil). Niterói , SP, Brazil
• Company: Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC)
• Associated research grant: 20/09835-1 - IARA - Artificial Intelligence in the Remaking of Urban Environments, AP.PCPE

Abstract

This project has three objectives, listed below: (i) To investigate how structural data from multiplexed networks derived from time series of telephone data configure relevant events. From there, we intend to (ii) develop methods for detecting and predicting relevant events as well as trends associated with a set of events. In particular, we will analyze the potential of using Machine Learning (ML) techniques to generate classification metrics from time series. Finally, we will seek to (iii) apply such data and techniques in the scope of Smart Cities; more specifically, in the creation of maturity diagnostic metrics for Brazilian Smart and Sustainable Cities that advance the state of the art in light of the method proposed here. Consequently, we seek to formulate policy suggestions that lead to the improvement of the indices measured by such metrics.