CV Lattes
ORCID
Google Scholar Citations
Universidade Federal de São Carlos (UFSCAR). Centro de Ciências Exatas e de Tecnologia (CCET) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Computer Science Bachlor at Universidade Estadual Paulista Julio de Mesquita Filho - UNESP, Bauru campus. Master's degree (2014-2016) by "Instituto de Biociências" from UNESP, São José do Rio Preto campus, with the research work titled "Identificação Biométrica de Pessoas via Características dos Seios Paranasais Obtidas de Tomografias Computadorizadas" supervised by Prof. Dr. Aparecido Nilceu Marana. Member of Recogna group (UNESP-Bauru) and fellow member of ReMIC group from the Techinical University of Applied Sciences - Regensburg, Germany. Current PhD student by the "Universidade Federal de São Carlos (UFScar)", in the Computer Science Program, and supervised by Prof. Dr. João Paulo Papa and Prof. Dr. Christoph Palm in the project "Auxílio ao Diagnóstico Automático do Esôfago de Barrett Utilizando Aprendizado de Máquina". My PhD project has been financed by FAPESP grants #2017/04847-9 and #2019/08605-5 (abroad at OTH Regensburg, in Germany). Currently I am an Assistant Professor at the Federal University of Espírito Santo, where I conduct research on Artificial Intelligente, Machine Learning and Medical Imaging fields. (Source: Lattes Curriculum)
| News published in Agência FAPESP Newsletter about the researcher |
| More itemsLess items |
| TITULO |
| Articles published in other media outlets ( ): |
| More itemsLess items |
| VEICULO: TITULO (DATA) |
| VEICULO: TITULO (DATA) |
The Barrett's Esophagus is usually hard to detect at the early stages of the esophageal lesion, being not correctly observed in the cancerous tissue evaluation so often. The development of automatic evaluation systems of such illness may be very useful, thus assisting the experts in the neoplastic region detection. With the strong growth of the machine learning techniques aiming to improv…
Esophageal adenocarcinoma is an illness that is usually hard to detect at the early stages in the presence of Barrett's esohagus. The development of automatic evaluation systems of such illness may be very useful, thus assisting the experts in the neoplastic region detection. With the strong growth of machine learning techniques aiming to improve the effectivess of medical diagnosis, the …
| 2 / 2 | Completed scholarships in Brazil |
| 1 / 1 | Completed scholarships abroad |
| 3 / 3 | All Scholarships |
| Associated processes | |