de Melo, G. A., Maximo, M. R. O. D. A., Soma, N. Y., & de Castro, P. A. L. (2024). On the Undecidability of Artificial Intelligence Alignment: Machines that Halt. arXiv [Cs.AI]. Retrieved from http://arxiv.org/abs/2408.08995
G. A. Melo, M. Máximo and P. A. Castro, "High Speed Marker Tracking for Flight Tests," in IEEE Latin America Transactions, vol. 20, no. 10, pp. 2237-2243, Oct. 2022, doi: 10.1109/TLA.2022.9885171.
G. Adriano de Melo, D. N. Sugimoto, P. M. Tasinaffo, A. H. Moreira Santos, A. M. Cunha and L. A. Vieira Dias, "A new approach to river flow forecasting: LSTM and GRU multivariate models," in IEEE Latin America Transactions, vol. 17, no. 12, pp. 1978-1986, December 2019, doi: 10.1109/TLA.2019.9011542.
Coelho, Mateus Menezes Azevedo, Dylan Nakandakari Sugimoto, Gabriel Adriano Melo, Vitor Venceslau Curtis, and Juliana de Melo Bezerra. "A MapReduce Based Approach for Circle Detection." In Proceedings of the 14th International Conference on Software Technologies (ICSOFT 2019), edited by Marten van Sinderen and Leszek A. Maciaszek, 454-459. Prague, Czech Republic: SciTePress, 2019. https://doi.org/10.5220/0007827604540459.
Gabriel Adriano Melo, Paulo Marcelo Tasinaffo. "Gated Recurrent Unit Hierarchical Architecture for Fundamental Stock Analysis and Forecast." Presented at the Workshop of Artificial Intelligence Applied to Finance 2019 (WAIAF 2019).
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA
Talk at London School of Testing, London, UK
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA
Talk at UC San Francisco, Department of Testing, San Francisco, California