Marcelo Azevedo Costa

Prof. Marcelo A Costa is a full professor of Applied Statistical Methods in the Department of Production Engineering at the Federal University of Minas Gerais (UFMG) and faculty member of the Graduate Program in Production Engineering (Stochastic Modeling and Simulation) at the same institution. He holds a degree in Electrical Engineering from the Federal University of Minas Gerais (1999), a PhD in Electrical Engineering from the Federal University of Minas Gerais (2002) in Computational Intelligence. He has done post-doctorate from Harvard Medical School & Harvard Pilgrim Health Care (2007) in Spatial Statistics and Epidemiological Surveillance, and post-doctorate from Linköping University (2018/Sweden) in Statistical Analysis, Diagnosis and Fault Detection in Industrial Environments. He is currently a collaborating professor in the Laboratory of Intelligence and Computational Technology (LITC/UFMG), developing research projects in artificial neural networks. He is also a collaborating professor at the Center of Research in Efficiency, Sustainability and Productivity (NESP/UFMG), developing research projects in economic regulation in the electricity sector. He has published several papers in international journals such as Socio-Economic Planning Sciences, IEEE Transactions on Power Delivery, Statistical Methods in Medical Research, PLOS One, Measurement, among others. He is a reviewer of international and national journals, as well as the author of book chapters published in English. He is a CEMIG/FAPEMIG R&D project coordinator and researcher in R&D projects. He supervises undergraduate, specialization, masters and doctoral students in the following areas: statistical models applied to the electrical sector, applied statistics, network analysis, spatial statistics, time series analysis, artificial neural network theory and applications. He is enthusiastic about using R language programming, which he has applied to solve many practical statistical problems including Big Data analysis.


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