Mr Mateus Maia Marques

  • Research Associate (Statistics)

Biography

My research primarily focuses on statistical machine learning models, with a strong emphasis on predictive tasks. My core interests include Bayesian methodologies and ensemble methods, although my work is not limited to these areas.

Over the past few years, I have developed and extended statistical methodologies to suit various contexts and assumptions. This has been complemented by my work in creating and maintaining R packages, which are openly accessible to the community, facilitating broader use and collaboration.

Currently, I am involved in the Project 4 Resilience initiative, where I apply statistical methodologies, particularly extreme value theory and spatio-temporal models, to enhance energy forecasting. This project aims to improve the resilience of energy systems by providing more accurate and reliable forecasts under varying conditions.

Research interests

My research interests currently cover:

- Spatio-temporal modelling

- Bayesian Tree Models

- Ensemble models

- Statistical Learning Models

Publications

Prior publications

Article

Mateus Maia, Keefe Murphy, Andrew C. Parnell (2024) GP-BART: A novel Bayesian additive regression trees approach using Gaussian processes Crossref. (doi: 10.1016/j.csda.2023.107858)

Mateus Maia, Jonatha Sousa Pimentel, Raydonal Ospina, Anderson Ara (2023) Wavelet Support Vector Censored Regression Crossref. (doi: 10.3390/analytics2020023)

(2022) Regression random machines: An ensemble support vector regression model with free kernel choice Mateus Maia. ISSN 0957-4174 (doi: 10.1016/j.eswa.2022.117107)

Mateus Maia, Arthur R. Azevedo, Anderson Ara (2021) Predictive Comparison Between Random Machines and Random Forests Mateus Maia. ISSN 1683-8602 (doi: 10.6339/21-jds1025)

Anderson Ara, Mateus Maia, Francisco Louzada, Samuel Macêdo (2021) Random Machines: A Bagged-Weighted Support Vector Model with Free Kernel Choice Mateus Maia. ISSN 1683-8602 (doi: 10.6339/21-jds1014)

Mateus Maia, Jonatha S. Pimentel, Ivalbert S. Pereira, João Gondim, Marcos E. Barreto, Anderson Ara (2020) Convolutional Support Vector Models: Prediction of Coronavirus Disease Using Chest X-rays Multidisciplinary Digital Publishing Institute. (doi: 10.3390/info11120548)

Hellen Paz, Mateus Maia, Fernando Moraes, Ricardo Lustosa, Lilia Carolina Carneiro da Costa, Samuel Macêdo, Marcos E. Barreto, Anderson Ara (2020) Local Processing of Massive Databases with R: A National Analysis of a Brazilian Social Programme Multidisciplinary Digital Publishing Institute. (doi: 10.3390/stats3040028)