Journal-Based Publications
[working paper] M. R. Machado, and S. Karray, ”Enhancing Risk-Adjusted Revenue Assessments Using Topic Modelling Tools” . International Journal of Forecasting [Under review since Dec 2021].
[working paper] M. R. Machado, and S. Karray, ”Customers’ Risk-Adjusted Revenue Assessments Through a Hybrid Machine Learning Framework” . Electronic Commerce Research and Applications [Under review since Nov 2021].
Machado, M. R., & Karray, S. (2022). Assessing credit risk of commercial customers using hybrid machine learning algorithms. Expert Systems with Applications, 200, 116889.
Machado, Marcos & Fujii, Murilo & Ribeiro, Celma & Rego, Erik. (2019). An Agent-Based Model Applied to Brazilian Wind Energy Auctions. IEEE Latin America Transactions. 17. 865-874. 10.1109/TLA.2019.8891956.
Conference Proceedings
M. R. Machado, S. Karray and I. T. de Sousa, ”LightGBM: an Effective Decision Tree Gradient Boosting Method to Predict Customer Loyalty in the Finance Industry,” 2019 14th International Conference on Computer Science & Education (ICCSE), Toronto, ON, Canada, 2019, pp. 1111-1116. doi: 10.1109/ICCSE.2019.8845529.
[accepted paper] M. R. Machado, and S. Karray, ”Integration of Customer Portfolio Theory and Multiple Sources of Risk Methods to Assess Customers’ Risk-Adjusted Revenue”. Control Applications of Optimization - 18th CAO 2022 [Conference scheduled for July 2022].
Olimpio, J. C., Machado, M. R., ed. (2018). Process optimization during contracting in real estate - A case study. In: 18ª LARES – Latin American Real Estate, Sao Paulo. Conference Anais. ISBN: 978-85-66934-09-0.
Machado, M. R., C.O. Ribeiro (2015). Logistic regression applied to real estate business. In: XXXV Production Eng. National Conference, Fortaleza. Conference Anais. SSN ENEGEP: 2594-9713 / ISSN ICIEOM: 23178000.
Machado, M. R., R. C. Marina, A. C. Rocha, C.O. Ribeiro (2015). Analysis of investment quality in a real estate fund: a case of study. In: 15ª LARES – Latin American Real Estate, Sao Paulo. Conference Anais. ISBN: 978-85-66934-06-9. Best paper award*.
More details on my google scholar: Marcos Machado