Assistant professor at the Institute of Mathematics and Computer Science of the University of São Paulo (ICMC-USP), graduated in Computer Science and has M.S. and Ph.D. degrees in Computer Science and Computational Mathematics, all from ICMC-USP. His central research theme is Data Mining and its applications, focusing on large volumes of continuous sequential data (such as time series and digital signals). Besides, he has experience with data preprocessing for Machine Learning applications, class imbalance, and classification of data streams. He is the coordinator of the research group on Data Mining and Applications (MIDAS, the acronym for the group's name in Portuguese), which includes undergrad and graduated students. (Source: Lattes Curriculum)
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Monitoring physiological signs, vital signs, and other parameters that can be collected over time from individuals are essential in several tasks in healthcare, such as heart rate estimation and the identification of abnormal heartbeats. However, these time series are obtained by very expensive and usually not portable equipment. On the other hand, with the improvement and miniaturization…
With the enhancement and miniaturization of sensors capable of obtaining and transmitting various types of data, the Internet of Things has been notably gaining space in both scientific research and industry. Sports analysis is among a multitude of applications of such a technology. Specifically, sensors have aided the statistical analysis of the athletes' performances. This type of devic…
With the growing interest in time series in recent decades, which has been intensifying in recent years, researchers have proposed dozens of specific algorithms for classifying and forecasting time series. However, there is still a great demand for techniques associated with the extrinsic regression of time series. By "extrinsic," it is understood that the target of the prediction is an e…
Monitoring physiological signs, vital signs, and other parameters that can be collected over time is essential in several tasks in Health, such as estimating heart rate and identifying abnormal heartbeats. However, obtaining annotated data, especially in the Health domain, can be costly. However, in some cases, obtaining labels for part of the data is possible. This scenario configures se…
Monitoring physiological signs, vital signs, and other parameters that can be collected over time from individuals are essential in several tasks in healthcare, such as heart rate estimation and the identification of abnormal heartbeats. However, these time series are obtained by very expensive and usually not portable equipment. On the other hand, with the improvement and miniaturization…
(Only some records are available in English at this moment)
With the growing ubiquity of smartphones, smartwatches, and other devices capable of collecting data across time, applications that use time series as input, such as cardiac monitoring and activity recognition, have become increasingly popular. Thus, various techniques have been developed for Machine Learning applied to time series. However, the majority of those techniques were created f…
With the growth of music content streaming platforms, the interest in automating tasks such as recommendation and information retrieval from musical data has been increasing. In this context, social tags have been considered important tools for organizing and retrieving musical data. Tags, or "labels", are data assigned to each music (or artist) to describe it at a high level. Some exampl…
Due to the increasing collection of overtime observed data, time series are becoming a ubiquitous type of data in human beings' daily lives. This fact has also caused a significant increase in the number of techniques for time series classification in recent decades. In this scenario, when a researcher or developer needs a solution based on a classification model, there is a wide range of…
(Only some records are available in English at this moment)
With the growing ubiquity of smartphones, smartwatches, and other devices capable of collecting data across time, applications that use time series as input, such as cardiac monitoring and activity recognition, have become increasingly popular. Several of these scenarios can be mapped naturally as tasks involving multivariate time series. Thus, various techniques for Machine Learning appl…
With the growing ubiquity of smartphones, smartwatches, and other devices capable of collecting data across time, applications that use time series as input, such as cardiac monitoring and activity recognition, have become increasingly popular. Several of these scenarios can be mapped naturally as tasks involving multivariate time series. Thus, various techniques for Machine Learning appl…
With the growing ubiquity of smartphones, smartwatches, and other devices capable of collecting data across time, applications that use time series as input, such as cardiac monitoring and activity recognition, have become increasingly popular. Thus, various techniques for Machine Learning applied to time series have been developed. However, most of those techniques were created for class…
Time series data is becoming ubiquitous in our everyday tasks. The increasing collection of data observed over time has also increased the number of techniques for classifying time series. In this scenario, when a researcher or practitioner needs a classification solution, there is a vast range of options of algorithms to apply. When only one algorithm is chosen, its performance may not a…
Music auto-tagging is a significant way to characterize recordings, with implications on music organization and retrieval. The state-of-the-art auto-taggers are based on deep learning. However, these techniques need a large volume of data to induce a suitable model. Besides, these models may underperform on least represented tags. While there are techniques to reduce this issue during the…
(Only some records are available in English at this moment)
| 1 / 1 | Ongoing research grants |
| 1 / 1 | Completed research grants |
| 5 / 5 | Ongoing scholarships in Brazil |
| 13 / 13 | Completed scholarships in Brazil |
| 2 / 2 | Ongoing scholarships abroad |
| 6 / 6 | Completed scholarships abroad |
| 28 / 28 | All research grants and scholarships |
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