PhD in Agricultural Engineering from the University of Campinas (2022) with emphasis on crop modeling. Experiences include modeling using data-driven approaches, particularly machine learning techniques, and mechanistic approaches, as well as in the use of the DSSAT and APSIM platforms and in code implementation of tomato plant growth models based on their equations. I also have experience in areas related to modeling: calibration, sensitivity analysis, assessment strategies, data assimilation and assessment in climate change scenarios. (Source: Lattes Curriculum)
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Dynamic crop growth models combined with the vast body of available data have been seen as part of the response to the problem of a more resource efficient Agriculture. Although such models require calibration steps without which their predictive performance may be insufficient to aid in decision making, real-time monitoring may circumvent this need. Dynamic models and satellite images ha…
Sugarcane is one of the most relevant crops in Brazil and, therefore it is imperative that the decisions taken to reach the larger achievable production also contemplate social and environmental perspectives. Mechanized harvest system, applied as an alternative to traditional manual harvesting, support the constitution of a layer of cultural trash which protects the soil and that improves…
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CV Lattes
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