Physics graduate from UFMT and M.Sc. student in Environmental Physics, working at the intersection of machine learning, atmospheric science, and climate data analysis in Brazil.
I study how data-driven methods can support the analysis of lightning, climate variability, and environmental risk in Brazil. My current work combines atmospheric datasets, statistical analysis, and machine learning to investigate patterns linked to lightning-related impacts.
My background is in computational physics, with experience in numerical modeling, scientific programming, and interdisciplinary research across environmental and physical systems.
- Machine learning applied to lightning and climate data in Brazil
- Analysis of lightning-related fatalities and their environmental drivers
- Atmospheric datasets, seasonality, and geophysical pattern detection
- Scientific workflows for reproducible data processing and modeling
