Data Driven Management - Artificial Intelligence and Data Science

• Grant number: 25/21099-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2025
• End date: September 30, 2026
• Field of knowledge: Agronomical Sciences - Agronomy
• Principal Investigator: Elisabete Aparecida de Nadai Fernandes
• Grantee: Filipe Borges Mendes
• Host Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Associated research grant: 22/12732-5 - Transparency in the Brazilian production chains of agricultural export commodities: a holistic study of elemental and isotopic fingerprints, AP.TEM

Abstract

In the context of the Fapesp thematic project "Transparency in the Brazilian production chains of agricultural export commodities: A holistic study of elemental and isotopic fingerprints", Process 2022/12732-5, the fellow will implement a data-driven project management system, introducing artificial intelligence tools and the Toyota Management System. Initially, the objectives and goals of each subproject will be defined, as well as the sequence of actions to achieve the goals (method), with special attention to the identification of metrics and key performance indicators (KPIs). Data collection and analysis will be implemented using data science tools and inductive artificial intelligence (machine learning) in four categories: supervised for classification and prediction, and unsupervised for dimension reduction and calculation of clusters and multivariate distances. Robust univariate and multivariate data science tools and process quality control techniques will be used. The results will be presented permanently to the team on the project website using visual analysis techniques and dashboards, as well as on the project blog. The aforementioned techniques will be implemented using the computer languages Python, SAS, and SQL.