Thiago Nóbrega is a student in the Department of Computing Systems of the Federal University of Campina Grande (DSC/UFCG) and a member of the Data Quality Research Group. DQRG is a research group that investigates and develops novel techniques, approaches, processes, and tools for evaluating and improving the quality of data sets, taking into account critical aspects of contemporary data analysis: reliability and performance.
The main focus of the group is to facilitate and improve the effectiveness of key tasks that rely on the quality of the data, such as: data integration, schema integration, data mining and decision making. The group is formed by students, faculty, and staff from the Department of Computing Systems of the Federal University of Campina Grande (DSC/UFCG).
Data Quality Research Group Homepage
Ming Zeng is a Ph.D. student at Carnegie Mellon University. His research interests include machine learning, deep learning, human behavior modeling, and natural language processing. His work is primarily focused on deep neural networks (DNNs) for human activity recognition. The deep learning models used in his work mainly include convolutional neural networks (CNNs) and Long Short Term Memory (LSTM) with different architectures according to different applications. In addition, instead of treating the deep neural network as a black box, he is trying to interpret the features extracted from DNNs.
Ming will explore the CrowdSignals.io data in the human activity recognition related areas. Deep neural networks can take advantage of the large dataset to train a good model. In addition, because the CrowSignals.io dataset involves a number of sensors, it is worth trying neural networks with a sensor fusion approach.
Homepage: Homepage at CMU
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