Develop methods to integrate machine learning techniques with automatic control systems, creating a data-based control system capable of increasing system efficiency and stability.
Increasing the Efficiency of Mineral Processing Processes through Data-Driven Control
Canaã dos Carajás-PA
Carajás
São Gonçalo do Rio Abaixo
São Luiz
Research Group
Increasing the Efficiency of Mineral Processing Processes through Data-Driven Control
Area of activity
Processamento e beneficiamento aprimorado
Coordinator

Thomás Vargas Barsante e Pinto
PhD student in Electrical Engineering
Researchers

PhD in Computer Science and Computational Mathematics

PhD student in Electrical Engineering

Thomás Vargas Barsante e Pinto
PhD student in Electrical Engineering
Thomás Vargas Barsante e Pinto is a PhD candidate in the Graduate Program in Electrical Engineering at the Federal University of Minas Gerais (UFMG) and holds a master’s degree in Instrumentation, Control, and Automation of Mining Processes from the PROFICAM program, a partnership between ITV MI and the Federal University of Ouro Preto (UFOP). Graduated in Control and Automation Engineering from UFOP, he is a researcher at ITV MI and works mainly in the development of advanced and regulatory control systems, dynamic simulation of mining processes, and vehicle traffic.
Projetos relacionados
Projeto
Increasing the Efficiency of Mineral Processing Processes through Data-Driven Control
Publicações relacionadas

Gustavo Pessin
PhD in Computer Science and Computational Mathematics
Gustavo Pessin holds a PhD in Computer Science from the University of São Paulo (USP), with a sandwich period at Heriot-Watt University (UK) and a postdoctoral fellowship at the Massachusetts Institute of Technology (MIT). He has worked in various research laboratories in Brazil, the UK, and Switzerland, focusing on mobile robotics and intelligent systems. He is a member of the graduate programs at UFOP/ITV, Unifesspa/ITV, and a collaborating professor at the Federal University of Pará (UFPA). His research involves machine learning, intelligent instruments, and robotics applied to mining.
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Developing Process Routes
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Miniaturized System for Monitoring Equipment Conditions
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Increasing the Efficiency of Mineral Processing Processes through Data-Driven Control
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Thomás Vargas Barsante e Pinto
PhD student in Electrical Engineering
Thomás Vargas Barsante e Pinto is a PhD candidate in the Graduate Program in Electrical Engineering at the Federal University of Minas Gerais (UFMG) and holds a master’s degree in Instrumentation, Control, and Automation of Mining Processes from the PROFICAM program, a partnership between ITV MI and the Federal University of Ouro Preto (UFOP). Graduated in Control and Automation Engineering from UFOP, he is a researcher at ITV MI and works mainly in the development of advanced and regulatory control systems, dynamic simulation of mining processes, and vehicle traffic.
Projetos relacionados
Projeto
Increasing the Efficiency of Mineral Processing Processes through Data-Driven Control
Publicações relacionadas