CV Lattes
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Universidade de São Paulo (USP). Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP) (Institutional affiliation from the last research proposal) Birthplace: Brazil
He has a degree in Electrical Engineering (1994) from the São Paulo State University Júlio de Mesquita Filho (UNESP), a master's degree (1999) and a doctorate (2003) in Electrical Engineering from the University of São Paulo (USP). Since 2004 he has been a professor at the Faculty of Philosophy, Sciences and Letters of Ribeirão Preto (FFCLRP) at USP. He is currently a full professor of the Department of Computing and Mathematics at FFCLRP / USP, where he was head of the department twice. He is affiliate to the graduate programs Applied Computing and Physics Applied to Medicine and Biology at FFCLRP / USP. He works in the area of Artificial Intelligence, with special interest in theoretical and practical aspects of Evolutionary Computation and Machine Learning. (Source: Lattes Curriculum)
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Health systems form a complex structure whose understanding and modeling involve multiple factors and their relationships. Brazil's demographic diversity makes Health Management an even more challenging scenario. On the other hand, overcoming them can produce significant advances for Health in Brazil and worldwide. Advanced Artificial Intelligence (AI) methods have generated significant d…
Accurate production management decisions for soybeans are crucial for increasing yield and improving harvest quality. However, the complex canopy structure of soybean plants, characterized by mutual shading, complicates the accurate acquisition of phenotypic data. Additionally, soybean growth is intricately linked to environmental factors, which are increasingly variable due to climate ch…
Information about the structure of the problem is available in many optimization applications. However, this information is neglected by the vast majority of Evolutionary Algorithms (EAs), making optimization a black-box process. In contrast, gray-box optimization takes advantage of the knowledge of the interaction between decision variables to guide the search. Recently, new operators an…
The recombination of solutions is important for evolutionary computation, particularly for genetic algorithms. Recombination is also interesting in other optimization strategies: it can be used to recombine solutions produced in different runs of an algorithm or to recombine solutions produced by different algorithms. The main objective of this project is the investigation of new operator…
(Only some records are available in English at this moment)
Obstructive Sleep Apnea is one of the most common sleep disorders, consisting of the cessation or reduction of airflow during sleep. The most common and accurate test to diagnose sleep disorders is polysomnography which, despite its effectiveness, is a complex and relatively expensive test. Recently, the use of Heart Rate Variability and Machine Learning (ML) to classify the severity of S…
We are interested in Explainable Artificial Intelligence to explain decisions of Machine Learning (ML) models in the problem of Sleep Apnea severity classification. (Obstructive) Sleep Apnea is one of the most common sleep disorders, consisting of the cessation or reduction of airflow during sleep. The most common and accurate test to diagnose sleep disorders is polysomnography which, des…
Osteosarcoma is the most common type of cancer in the bones. In this work, X-ray images will be classified using Machine Learning (ML) methods. The method should aid the detection of osteosarcoma at different levels of malignancy. Currently, there has been a great interest in using Convolutional Neural Networks for the classification of medical images. The main advantage of these neural n…
The identification of running patterns, especially those associated with fatigue, can assist in designing more efficient workouts and preventing injuries in high-performance sports. However, this task is not trivial due to the complexity of the patterns. An interesting alternative is to use Machine Learning methods, such as Artificial Neural Networks (ANNs), to classify running patterns. …
(Only some records are available in English at this moment)
The canonical genetic code is almost universal and is present in most complex organisms. A question that has intrigued researchers is why exactly this code was chosen instead of another one. Many researchers believe that the genetic code is a product of natural selection, what is supported when the canonical genetic code is compared with other hypothetical codes considering some evaluatio…
In this project, Genetic Algorithms (GAs) in dynamic optimization problems, which are characterized by changes in the surface of fitness occurring during the execution of the optimization algorithm, will be theoretically investigated. The area of evolutionary algorithms in dynamic environment has received great attention from researchers in recent years. Unfortunately, few studies have st…
| 2 / 2 | Ongoing grants |
| 8 / 5 | Completed research grants |
| 1 / 1 | Ongoing scholarships in Brazil |
| 23 / 15 | Completed scholarships in Brazil |
| 2 / 2 | Completed scholarships abroad |
| 36 / 25 | All research grants and scholarships |
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