About me
Hi! I’m Ana. I have been working in research and development projects in data science and machine learning, since 2020. Currently, I’m working with mathematical and statistical methods for classifying market segments, improving risk models for granting credit limits and validating the probability of default of the counterparties studied. My interests are focused on Mathematical Modelling, Applied and Computational Mathematics, Machine Learning Algorithms, Simulations and Mathematical Biology. But, in my free time, I have ventured into nature photography.
In my master’s degree studies at School of Electrical and Computer Engineering - FEEC), in University of Campinas (UNICAMP), Brazil. I have started to work on modelling a citrus disease, threatening the citriculture worldwide. This disease is known as Greening or HLB (Huanglongbing) and there is no cure for while. Essentially, I used cellular automaton to look at the spatial dispersion of HLB in a grove. Also, I investigated how the dispersion of inoculum affects the crop yield, as the yield per tree (in the model) depends on the disease severity and the age of the plant. As an evolution of this work, I utilized Individual-Based Model (IBM) - also known as Agent-Based Model out of biology - to analyse and understand the patterns of this vector dispersion due to different factors. In 2017 (for 11 months), I was guest scientist at the Forstliche Biometrie und Forstliche Systemanalyse (Forest Biometry and Forest Systems Analysis) research group, in TU Dresden, Germany. Financed by European Commission in the Erasmus Mundus Programme - Euro-Brazilian Windows +.
On my undergraduate studies (Bachelor in Applied and Computational Mathematics at IMECC), I worked at the LabMaC (Computational Mathematics Laboratory) on Embrapa Agricultural Informatics with a CNPq Scientific Initiation fellowship. There, I developed a deterministic compartmental model for the Equine Infectious Anemia (EIA) to analyze the behavior between the horses and the vector of EIA (mutuca).