Prof. Luiz Paulo L. Fávero

University of São Paulo, Bazil

Email：[email protected]

Qualifications

2009 Post-Doc., Columbia University, School of International and Public Affairs

2005 Ph.D., Business and Accountancy of University of São Paulo

2003 M.Sc., Business and Accountancy of University of São Paulo

2001 MBA, School of Business Administration of Getúlio Vargas Foundation

1997 Undergraduate, Undergraduate Polytechnic School of University of São Paulo

Publications (Selected)

1. Silveira, R. M. F., Façanha, D. A. E., de Vasconcelos, A. M., Leite, S. C. B., Leite, J. H. G. M., Saraiva, E. P., ... & da Silva, I. J. O. (2026). Physiological adaptability of livestock to climate change: A global model-based assessment for the 21st century. Environmental Impact Assessment Review, 116, 108061.
2. Silveira, R. M. F., de Vasconcelos, A. M., McManus, C., Fávero, L. P., & da Silva, I. J. O. (2025). Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change. Smart Agricultural Technology, 12, 101128.
3. Hair Jr, J. F., Fávero, L. P., Junior, W. T., & Duarte, A. (2025). Deterministic and Stochastic Machine Learning Classification Models: A Comparative Study Applied to Companies’ Capital Structures. Mathematics, 13(3), 411.
4. Fávero, L. P., Santos, H. P., Belfiore, P., Duarte, A., Costa, I. P. D. A., Terra, A. V., ... & Santos, M. D. (2024). A Proposal for a New Python Library Implementing Stepwise Procedure. Algorithms, 17(11), 502.
5. dos Santos, M. A., Fávero, L. P. L., Brugni, T. V., & Serra, R. G. (2024). Adaptive markets hypothesis and economic-institutional environment: a cross-country analysis. Revista de Gestão, 31(2), 215-236.
6. Fávero, L. P. L., Duarte, A., & Santos, H. P. (2024). A new computational algorithm for assessing overdispersion and zero-inflation in machine learning count models with python. Computers, 13(4), 88.
7. Silveira, R. M. F., McManus, C. M., Carrara, E. R., De Vecchi, L. B., de Sousa Carvalho, J. R., Costa, H. H. A., ... & Landim, A. V. (2024). Adaptive, morphometric and productive responses of Brazilian hair lambs: crossing between indigenous breeds-A machine learning approach. Small Ruminant Research, 232, 107208.
8. Araújo, E. F. D., Pereira, A. G., & Fávero, L. P. L. (2024). Relação entre modalidade de ensino e desempenho acadêmico: análise multinível do ENADE em Ciências Contábeis. Revista Contabilidade Vista & Revista, 34(2), 1-23.
9. Lima, F. G., Paulino, C. T., & Fávero, L. P. L. (2024). ESG e machine learning: o impacto na previsão de insolvência de empresas brasileiras. Contabilometria, 11(1).
10. Jacques, K. A. S., Lemes, S., Fávero, L. P. L., & Rodrigues, L. M. P. D. L. (2023). Composition of the board of directors and the probability of disclosure of social responsibility reports. Revista Brasileira de Gestão de Negócios, 25(4), 516-532.
11. Vasconcelos, F. F., Sátiro, R. M., Fávero, L. P. L., Bortoloto, G. T., & Corrêa, H. L. (2023). Analysis of judiciary expenditure and productivity using machine learning techniques. Mathematics, 11(14), 3195.
12. Ferreira, P., Limongi, R., & Fávero, L. P. (2023). Generating music with data: application of deep learning models for symbolic music composition. Applied Sciences, 13(7), 4543.
13. Doratiotto, K., Vidal Vieira, J. G., da Silva, L. E., & Fávero, L. P. (2023). Evaluating logistics outsourcing: a survey conducted with Brazilian industries. Benchmarking: an international journal, 30(3), 788-810.
14. Santos, M. D., Gomes, C. F. S., Pereira Júnior, E. L., Moreira, M. Â. L., Costa, I. P. D. A., & Fávero, L. P. (2023). Proposal for mathematical and parallel computing modeling as a decision support system for actuarial sciences. Axioms, 12(3), 251.
15. Moreira, M. Â. L., de Souza, G. V. P., de Araújo Costa, I. P., Junior, W. T., Fávero, L. P., dos Santos, M., & Gomes, C. F. S. (2023). Defense Perception in the Geopolitical Scope: An exploratory study through unsupervised machine learning. Procedia Computer Science, 221, 689-696.
16. Barbara, F., Moreira, M. Â. L., Fávero, L. P., & dos Santos, M. (2023). Interactive Internet-based Tool Proposal for the WASPAS method: a contribution for decision-making process. Procedia Computer Science, 221, 200-207.
17. Pinochet, L. H. C., Moreira, M. Â. L., Fávero, L. P., dos Santos, M., & Pardim, V. I. (2023). Collaborative work alternatives with ChatGPT based on evaluation criteria for its use in higher education: Application of the PROMETHEE-SAPEVO-M1 method. Procedia Computer Science, 221, 177-184.

Profile Details

WoS ResearcherID: C-6034-2016

https://bv.fapesp.br/en/pesquisador/678391/luiz-paulo-lopes-favero/

https://scholar.google.com/citations?user=bKujhe8AAAAJ&hl=en

https://www.researchgate.net/profile/Luiz-Favero