CV Lattes
ResearcherID
ORCID
Universidade Estadual Paulista (UNESP). Campus de Bauru. Faculdade de Ciências (FC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
He is currently a Full Professor in the Department of Computer Science at the São Paulo State University, Unesp-Bauru. He holds a Bachelor's degree in Information Systems from the São Paulo State University (2002), a Master's degree in Computer Science from the Federal University of São Carlos (2005), a PhD in Computer Science from the State University of Campinas (2008), and post-doctorates in Computer Science from the State University of Campinas (2009), Harvard University (2015), and the Massachusetts Institute of Technology (MIT) (2025). He is a senior editor of the IEEE Signal Processing Letters journal, as well as a member of the editorial boards of the journals Computer Methods in Biomechanics and Biomedical Engineering, Journal of Next Generation Information Technology, and International Journal of Bio-Inspired Computation. He is co-editor of a book on metaheuristic optimization, and has collaborations with several international institutions. He was a visiting professor at the Ostbayerische Technische Hochschule (Germany) and Coordinator of the Postgraduate Program in Computer Science at Unesp. He is a Fellow of the International Association for Pattern Recognition (IAPR), the Asia-Pacific Artificial Intelligence Association (AAIA), and the Alexander von Humboldt Foundation (AvH), as well as a Brazilian representative to the International Association for Pattern Recognition (IAPR) and a senior IEEE member. He was a full member of the Special Committee on Computer Graphics and Image Processing (CEGRAPI) from 2015 to 2018. He has experience in Computer Science, with an emphasis on Computer Systems, working mainly on the following topics: image processing, machine learning, and pattern recognition. He also participates in projects in the area of #8203;#8203;Petroleum Engineering with the Center for Applied Geosciences in Petroleum (UNESPETRO) - Unesp/Rio Claro, and Recogna - Unesp/Bauru. He is currently chair of the IEEE Task Force on Business Intelligence and Knowledge Management, member of CA-CC/CNPq and Coordinator of the eScience and Data Science Program at FAPESP. (Source: Lattes Curriculum)
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The Data Science Center for Smart Industry acts as an advanced data analytics hub for industry, aiming to improve operational efficiency, product quality, innovation and sustainability through the application of data science and analytics techniques of data in industrial processes. Contact with industries will be mediated by SENAI and operationalized through workshops and thematic meeting…
The São Paulo State University (UNESP) is one of the largest and most important Brazilian universities, with outstanding performance in teaching, research, and extension of services to the community. Maintained by the state of São Paulo government, it is one of the three public universities with free education, along with USP (University of São Paulo) and Unicamp (State University of Camp…
Tribology stands for a research area that studies the process of friction in mechanical components. Since friction demands more energy, exploring the elements' behavior when interacting with each other is crucial to minimize such losses. Despite their usage in many areas, machine learning techniques have also been considered to deal with tribological studies, ranging from condition monito…
(Only some records are available in English at this moment)
Barrett's esophagus (BE) comprises a very severe and growing disease in the last decades, and since BE is often not identified properly at the early stages, it may evolve to a more aggressive version, and even to cancer. However, the early diagnosis of dysplastic tissue in BE-diagnosed patients may provide very high rates of remission after the treatment. In the past few years, deep learn…
Undiagnosed diabetic retinopathy (DR) leads to vision impairment and blindness, and its early detection can significantly reduce severe vision impairment by 50%. The presence of exudates in fundus images is one of the first signs of such a disease, but their manual detection is examiner-dependent and time-consuming. In this proposal, we aim at coping with the lack of data concerning compu…
Several machine learning techniques have relied on large labeled data sets to construct predictive models and solving supervised learning tasks. The use of deep learning techniques can be highlighted, since it have been broadly and successfully used in various domains. On the other hand, in many circumstances, the labeled sets are unavailable or insufficient to train effective supervised …
(Only some records are available in English at this moment)
This project aims to develop an application that promotes communication accessibility for people who are deaf or hard of hearing. The proposal is to use artificial intelligence (AI) technology to convert texts typed by users into a visual translation into Brazilian Sign Language (Libras). The application will include an interactive digital avatar, capable of clearly reproducing the signs …
Assisted disease diagnosis through medical imaging, clinical data, and text description has been paramount in recent years. Allied with the astonishing and promising results machine learning delivers, one may achieve even more accurate performance when using all available data sources. On the other hand, we face the problem of combining different data modalities. How to ensure one modalit…
Genetic evaluations of 305 milk yield (MY305) in Gir cattle uses the animal model to estimate the genomic genetic value (GEBV), solved by the ssGBLUP method considering genomic relationship information, calculated from genetic single nucleotide polymorphisms (SNP), additive genetic relationship, combined in matrix H, and the productive performance of the entire population. Due to the high…
(Only some records are available in English at this moment)
Amyotrophic Lateral Sclerosis (ALS) is an incurable and progressive neurodegenerative disease impacting motor neurons, leading to bulbar dysfunction in over 80% of cases. Survival rates after diagnosis vary from 20 to 48 months, with only 5 to 10% of patients living beyond 10 years, underscoring the critical need for early detection. However, the absence of reliable clinicopathological ma…
Chest X-ray images play a crucial role in modern medicine, being an accessible and easy-to-use tool for radiologists to identify diseases and assess the proper positioning of medical devices. Ensuring the correct positioning of these devices is vital for the patient's health, especially in high-risk cases where X-ray examinations are frequent. With the advance of deep learning techniques …
In this research project, we will explore the application of machine learning methods focused on the implementation of the Optimum-Path Forest (OPF) in the context of quantum computing. We will study how quantum computing tools and methods can be used to solve the Traveling Salesman problem, integrating this solution to the OPF. In particular, we will investigate how the implementation of…
(Only some records are available in English at this moment)
Brazil is the world's largest sugarcane producer and sugar supplier, an important economic activity. Weed control must be adequate, for herbicides are likely to damage the culture. The problem worsens on perennial plants, e.g., sugarcane, since not cleaning the soil after a harvest is a widespread practice. Plants and weeds often get mixed, making their automatic differentiation a severe …
Over the years, supervised image classification has made some noble advances. The classification models, in turn, developed a stronger need for larger datasets. However, in many situations, images are scarce. In this context, few-shot learning stands out as it allows models to learn from a few labeled samples. In particular, a promising model known as Prototypical Networks was introduced.…
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 …
(Only some records are available in English at this moment)
| 6 / 6 | Ongoing grants |
| 16 / 16 | Completed research grants |
| 7 / 7 | Ongoing scholarships in Brazil |
| 43 / 31 | Completed scholarships in Brazil |
| 6 / 6 | Completed scholarships abroad |
| 78 / 66 | All research grants and scholarships |
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