CV Lattes
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Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Ricardo Cerri obtained his PhD in Computer Science and Computational Mathematics from the University of São Paulo (ICMC/USP/Brazil), working with Neural Networks and Genetic Algorithms for Hierarchical and Multi-label Problems. He has experience working mainly with the themes of Bioinformatics and Machine Learning, with a special focus on advanced methods for classification and regression of data with multiple outputs and structured outputs (multi-output learning / hierarchical / multi-label / multi-target). From 2015 to 2024 he held the position of Assistant Professor in the Department of Computing at the Federal University of São Carlos (UFSCar/Brazil), leading the Bioinformatics and Machine Learning group (BioMal - www.biomal.ufscar.br), supervising undergraduate and graduate students. He is also a CNPq Research Productivity Fellow - Level 2. He has several ongoing international collaborations, in addition to several national collaborations. He works as a reviewer for national and international journals and conferences, in addition to serving on the program committee of different conferences and workshops in Brazil and abroad. He is also a member of the editorial board of international journals. From 2019 to 2020, he carried out postdoctoral research at the Laboratory of Artificial Intelligence and Decision Support (LIAAD) of the University of Porto (Portugal), working with multi-label classification in data streams. He is currently an Assistant Professor at the Institute of Mathematics and Computer Science of the University of São Paulo. (Source: Lattes Curriculum)
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Automatic Machine Learning (AutoML) is an emerging research field that aims to find automatic Machine Learning (ML) solutions for various problems. Using limited computational resources, AutoML automates the construction of ML pipelines, including data preparation, feature engineering, model generation, and model evaluation tasks. AutoML can potentially reduce human errors when designing …
Data Streams (DS) are sequences of data of unlimited size, generated continuously, non-stationary, and in many cases, at high speed. Because this flow is potentially infinite, the data cannot be stored in memory, forcing an example to be processed only once and discarded. Several real-world applications generate large amounts of data in a continuous flow, and the trend is that with the ev…
The aim of this project is to provide a series of molecular markers and candidate genes, both associated with grain yield to assist in the development of new commercial rice strains and cultivars. For this, the project will use two databases from Embrapa's Nuclear Rice Collection, one phenotypic, generated from a series of nine field experiments where its 550 accessions were evaluated for…
In conventional classification, an instance is classified in just one among two or more classes. These problems are called single-label classification problems. However, there are more complex problems in which an instance can be classified in two or more classes simultaneously. These are known in the Machine Learning literature as multi-label classification problems. When the classes inv…
(Only some records are available in English at this moment)
Amyotrophic Lateral Sclerosis (ALS) is a progressive and fatal neurodegenerative disease that affects motor neurons responsible for controlling voluntary movements. Despite decades of intensive research and the identification of approximately 50 genes potentially associated with the disease, its etiology remains largely unknown and treatment options are limited for most patients. This pro…
Transposable elements (TEs) are DNA sequences capable of moving within the genome, influencing genetic evolution. piRNAs are a class of small non-coding RNAs that play a crucial role in silencing TEs, contributing to species' reproductive stability. Predicting interactions between piRNAs and TEs through laboratory experiments is time-consuming and costly, making the development of efficie…
A significant challenge in novelty detection for multi-label classification problems in continuous data streams is how to measure the performance of algorithms. Effectively evaluating novelty detection algorithms is crucial to ensure accuracy and reliability in results. Recent methodologies do not penalize the identification of many novelty patterns representing a class, do not weigh nove…
(Only some records are available in English at this moment)
PIWI-interacting RNAs (piRNAs) are a class of small non-coding RNAs that are abundantly present in the human body. They play a fundamental role in gene expression regulation, embryonic development, and cell differentiation. Furthermore, a large number of recent studies show the involvement of piRNAs in various diseases such as tumors, male infertility, Alzheimer's, and cardiovascular dise…
Long non-coding RNAs (lncRNAs) are RNAs longer than 200 nucleotides that are not translated into functional proteins. They play an important role in various life processes. In parallel, an increasing number of studies have revealed associations between abnormal expressions of these RNAs and human diseases. Many biotechnological approaches have been used to identify and detect these lncRNA…
Single nucleotide polymorphisms (SNPs) are variations at unique positions in the nucleotide sequence where the DNA is created. Due to the genetic alteration, SNPs are extremely important for human health studies. By them, it is possible to predict the individual response to some particular medications, for example. Furthermore, SNPs can be associated with more complex diseases, like cardi…
(Only some records are available in English at this moment)
PIWI-interacting RNAs (piRNAs) are small non-coding RNAs crucial for gene regulation, embryonic development, and cell differentiation. Recent studies highlight their involvement in diseases such as cancer, male infertility, Alzheimer's, and cardiovascular disorders. Despite their importance and the growing use of computational approaches in biology, predicting piRNA-associated diseases re…
Long non-coding RNAs (lncRNAs) are RNA sequences longer than 200 nucleotides that are not translated into functional proteins. LncRNAs play a crucial role in several vital activities; therefore, dysfunctions of lncRNAs are associated with a wide range of diseases. Thus, is important to identify and detect lncRNAs, essencials to disease diagnosis and therapy. Given the adversities involvin…
Single Nucleotide Polymorphism (SNP) is the variation at a single position of a nucleotide chain where the DNA is formed. The association of SNPs and phenotypes is pertinent to assess the genetic basis of human health and the investigation of the genomes. The information provided by SNPs enables predicting the responses of an individual to certain drugs, as well as for the search of genes…
Data streams (DS) are unlimited, continuously generated, non-stationary, and in many cases high-speed data. Many real-world applications generate large amounts of data in a continuous stream, and with the evolution of Information Technology, more data will be generated and collected constantly. This highlights the relevance and necessity for developing algorithms capable of extracting rel…
(Only some records are available in English at this moment)
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| 30 / 29 | All research grants and scholarships |
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