CV Lattes
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Universidade de São Paulo (USP). Instituto de Física de São Carlos (IFSC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
PhD in Applied Physics (Computational) from the São Carlos Institute of Physics (IFSC) of the University of São Paulo (USP), completed in 2023. Is currently a postodoctoral researcher at IFSC-USP (since 2023), working with Machine Learning. Between January 2022 and January 2023, he carried out a BEPE-FAPESP research internship at Ghent University, Belgium. He holds a Bachelor's degree in Computer Science (2015) from the Federal University of Mato Grosso do Sul (UFMS), and a Master's degree in Applied Physics (Computational) also from IFSC-USP (2018). He works in research involving Machine Learning, Computer Vision and scientific computing in general, addressing mainly the following topics: complex networks, texture analysis, neural networks and pattern recognition. (Source: Lattes Curriculum)
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Sensors and biosensors play a crucial role in various fields, such as early cancer diagnosis, detection of viruses, contamination in food, water, etc. Intending to develop cost-effective and accurate detection and diagnosis strategies, researchers have explored the use of machine learning techniques and computer vision. While these approaches have shown promising results in biological ima…
Artificial Neural Networks (ANN) and complex networks are gaining attention nowadays due to advances in artificial intelligence, computer hardware, and big data phenomena. Recent deep ANN architectures have been achieving outstanding performance on complex problems, however, due to the lack of knowledge of its internal functioning, these techniques are used as a "black box" approach. In t…
Sensors and biosensors play a crucial role in various fields, such as early cancer diagnosis, detection of viruses, contamination in food, water, etc. Intending to develop cost-effective and accurate detection and diagnosis strategies, researchers have explored the use of machine learning techniques and computer vision. Images obtained from these sources possess unique textural properties…
Computer Vision is one of the most diffused areas within Machine Learning and where most of the deep Artificial Neural Networks (ANNs) have emerged. Although these models achieve outstanding results on large vision tasks, their ever-increasing complexity hampers a better understanding of their internal functioning. Consequently, most methods for architecture design and optimization usuall…
| 2 / 2 | Completed scholarships in Brazil |
| 2 / 2 | Completed scholarships abroad |
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