CV Lattes
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Universidade de São Paulo (USP). Instituto de Ciências Biomédicas (ICB) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Has Bachelor degree at Electrical Engineering from Universidade de São Paulo (2017) and Master's degree at Electrical Engineering from Universidade de São Paulo (2019), and is currently a PhD candidate in Electrical Engineering at University of São Paulo, with a period of research internship in Imperial College London (UK). Has experience on the following subjects: Epidemic Modeling, Bayesian Models, Machine Learning, Signal Processing, Compressive Sensing, Identification of Nonlinear Systems and Acoustic Emission. (Source: Lattes Curriculum)
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Numerous genetic and behavioral factors influence the risk of acquiring malaria. Evidence suggests that certain naturally acquired antibodies are linked to reduced clinical malaria risk in endemic areas. Conversely, specific work activities are known to increase the risk of malaria. In this context, we have demonstrated that components of vivax malaria transmission dynamics in the Amazon …
Inferring the fraction of the population infected by an infeccious agent (attack rate) in real time is essential for monitoring emerging infectious diseases and predicting the trajectory of future epidemics. Estimating the attack rate is hindered by the high cost of mass testing, the delay in reporting test results in hospitalised patients, and the large proportion of non-reported asympto…
There is nowadays a deep interest in the development of techniques that allow continuous monitoring of a mechanical structure (structural health monitoring - SHM). The method of acoustic emissions for detection of faults is one of the main techniques used for SHM. The method has great sensitivity, but there is room for improvement of the algorithms for detection of faults, for estimatio…
This project addresses the pattern recognition problem by extending recent techniques in graphs, which have been used successfully in the context of image processing, by the usage of non-smooth connectivity functions in the framework of the Image Foresting Transform (IFT). The intended techniques will allow a broader view than that currently supported by the recent works involving the cla…
The effective reproduction number (Rt) is a time-varying parameter used to monitor the evolution of an epidemic which can be inferred using serial interval and incidence data. The SARS-CoV-2 epidemic in Brazil was driven by multiple co-circulating lineages, which may present different serial interval distributions. Despite that, Rt is usually calculated using a fixed serial interval estim…
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