Prof. Dr. Everaldo GUEDES | Econometrics and Finance | Best Researcher Award
Professor from FIOCRUZ, Brazil
Dr. Everaldo Freitas Guedes is a distinguished Brazilian statistician and data scientist with a robust academic and professional background. He earned his Ph.D. and Master’s degrees in Computational Modeling and Industrial Technology from SENAI CIMATEC, following a Bachelor’s degree in Statistical Sciences from the Higher School of Statistics of Bahia and a Licentiate in Mathematics from the Faculty of Educational Sciences. Dr. Guedes has held various academic positions, including roles as a substitute professor at the Federal University of Recôncavo da Bahia and as a visiting professor at UNIASSELVI. In the public sector, he serves as an Administrative Analyst specializing in statistics at the Brazilian Company of Hospital Services (EBSERH). His research interests encompass time series analysis, data mining, machine learning, and computational statistics, with applications across finance, climatology, and healthcare. Dr. Guedes has contributed to the development of statistical methodologies, such as the Detrended Multiple Cross-Correlation Analysis (DMC) and the GMZTests R package. His work has been published in reputable journals and presented at various conferences, reflecting his commitment to advancing statistical science and its practical applications.
Professional Profile
Education
Dr. Guedes’s educational journey reflects a strong foundation in statistics and mathematics. He completed his Bachelor’s degree in Statistical Sciences at the Higher School of Statistics of Bahia (2004–2007), providing him with essential skills in data analysis and interpretation. Pursuing his passion for mathematics, he obtained a Licentiate in Mathematics from the Faculty of Educational Sciences (2007–2009), equipping him with pedagogical skills for teaching complex mathematical concepts. His academic pursuits culminated in a Master’s (2011–2014) and a Ph.D. (2012–2020) in Computational Modeling and Industrial Technology at SENAI CIMATEC. His doctoral research focused on the behavior of industrial production, employing advanced time series analysis techniques. Throughout his academic career, Dr. Guedes has demonstrated a commitment to interdisciplinary learning, integrating statistical theory with practical applications in industrial and technological contexts.
Professional Experience
Dr. Guedes has amassed extensive professional experience in both academic and public sectors. In academia, he has served as a substitute professor at the Federal University of Recôncavo da Bahia, teaching courses such as Algebra, Calculus, and Mathematics for Biology. He has also been a visiting professor at UNIASSELVI, contributing to the education of future statisticians and data scientists. In the public sector, Dr. Guedes holds the position of Administrative Analyst specializing in statistics at the Brazilian Company of Hospital Services (EBSERH), where he develops dashboards using Power BI and compiles statistical reports for maternity services. His professional roles have allowed him to apply his statistical expertise to real-world problems, bridging the gap between theoretical research and practical implementation. Additionally, his involvement in various educational institutions underscores his dedication to knowledge dissemination and capacity building in statistical sciences.
Research Interests
Dr. Guedes’s research interests are centered on the application of statistical methods to complex systems. He specializes in time series analysis, focusing on techniques like Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA) to study long-range dependencies in data. His work extends to data mining and machine learning, where he explores patterns in large datasets to inform decision-making processes. Dr. Guedes has applied these methodologies across various domains, including financial markets, climatology, and healthcare. Notably, he has investigated the interdependence of stock market indices using advanced cross-correlation techniques and analyzed climatic variables to understand environmental changes. His interdisciplinary approach demonstrates the versatility of statistical tools in addressing diverse scientific questions.
Research Skills
Dr. Guedes possesses a comprehensive skill set in statistical analysis and computational modeling. He is proficient in programming languages such as R and Python, utilizing them for data analysis, visualization, and the development of statistical packages. His expertise includes the creation of the GMZTests R package, which offers a suite of statistical tests for time series analysis. Dr. Guedes is adept at employing machine learning algorithms for predictive modeling and has experience with big data tools like PySpark. His skills extend to the development of interactive dashboards using Power BI, facilitating data-driven decision-making in organizational settings. Through continuous professional development, including courses on deep learning and data science, Dr. Guedes stays abreast of emerging technologies and methodologies in the field.
Awards and Honors
Throughout his career, Dr. Guedes has been recognized for his contributions to statistical science. He received a doctoral scholarship from the Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB), supporting his research in computational modeling. His scholarly work has garnered citations in academic publications, reflecting the impact of his research on the scientific community. Dr. Guedes’s commitment to excellence is further evidenced by his participation in professional development programs and certifications, including Lean Six Sigma and data science courses. These accolades underscore his dedication to advancing statistical methodologies and their practical applications.
Conclusion
Dr. Everaldo Freitas Guedes exemplifies the integration of rigorous academic training with practical experience in statistical analysis and data science. His educational background lays a solid foundation for his multifaceted career, encompassing teaching, research, and public service. Dr. Guedes’s research endeavors demonstrate a commitment to applying statistical methods to real-world problems, contributing valuable insights across various domains. His proficiency in computational tools and continuous pursuit of professional development position him as a leader in the field. Recognitions such as the FAPESB scholarship and citations of his work attest to his impact on the scientific community. Dr. Guedes’s career trajectory reflects a dedication to the advancement of statistical science and its application for societal benefit.
Publications Top Notes
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Title: Quantifying the Influence of Climatic Variables on the Incidence of Diseases in Salvador-BA
Journal: Fluctuation and Noise Letters
Date: June 2025
DOI: 10.1142/S0219477525500294
Contributors: Everaldo Freitas Guedes, Cláudia Ferreira da Cruz, Florêncio Mendes Oliveira Filho -
Title: DETRENDED MULTIPLE CROSS-CORRELATION COEFFICIENT BASED ON ρDMCA
Journal: Fractals
Date: May 16, 2025
DOI: 10.1142/S0218348X25500434
Contributors: E. F. Guedes, R. M. T. S. Dias, A. M. da Silva Filho, G. F. Zebende -
Title: Caracterização da rede de internações por diabetes mellitus no estado da Bahia: teoria das redes
Journal: Revista Baiana de Saúde Pública
Date: December 31, 2022
DOI: 10.22278/2318-2660.2022.v46.n4.a3341
Contributors: Raiara dos Santos Pereira Dias, Aloísio Machado da Silva Filho, Edna Maria de Araújo, Everaldo Freitas Guedes, Florêncio Mendes Oliveira Filho -
Title: Statistical Approach to Study the Relationship Between Stock Market Indexes by Multiple DCCA Cross-Correlation Coefficient
Journal: Fluctuation and Noise Letters
Date: October 2022
DOI: 10.1142/S0219477522500456
Contributors: G. F. Zebende, L. C. Aguiar, Paulo Ferreira, E. F. Guedes -
Title: Efficiency and Long-Range Correlation in G-20 Stock Indexes: A Sliding Windows Approach
Journal: Fluctuation and Noise Letters
Date: August 2022
DOI: 10.1142/S021947752250033X
Contributors: E. F. Guedes, R. P. C. Santos, L. H. R. Figueredo, P. A. da Silva, R. M. T. S. Dias, G. F. Zebende -
Title: How Statistically Significant is the DMCA Coefficient?
Journal: Fluctuation and Noise Letters
Date: June 2022
DOI: 10.1142/S0219477522500213
Contributor: Everaldo Freitas Guedes -
Title: Detrended multiple cross-correlation coefficient with sliding windows approach
Journal: Physica A: Statistical Mechanics and its Applications
Date: July 2021
DOI: 10.1016/j.physa.2021.125990
Contributors: E. F. Guedes, A. M. da Silva Filho, G. F. Zebende -
Title: Analysis of intentional lethal violent crimes: A sliding windows approach
Journal: Physica A: Statistical Mechanics and its Applications
Date: April 2021
DOI: 10.1016/j.physa.2020.125653
Contributors: A. M. da Silva Filho, G. F. Zebende, E. F. Guedes -
Title: DCCA cross-correlation coefficient with sliding windows approach
Journal: Physica A: Statistical Mechanics and its Applications
Date: August 2019
DOI: 10.1016/j.physa.2019.121286
Contributor: Everaldo Guedes -
Title: An econophysics approach to study the effect of BREXIT referendum on European Union stock markets
Journal: Physica A: Statistical Mechanics and its Applications
Date: June 2019
DOI: 10.1016/j.physa.2019.04.132
Contributor: Everaldo Guedes