The Data Analytics Lab (DAL) is a research group at CEFET/RJ, registered with CNPq, dedicated to the development of innovative methods and tools in Data Analysis and Data Mining, with a special emphasis on time series analysis. Its activities range from the investigation of prediction techniques to event detection, including anomalies, change points, concept drifts, pattern discovery, and motif identification. DAL operates at the interface between basic and applied research, seeking robust solutions for problems involving multivariate, non-stationary data from complex scenarios such as real-time monitoring, big data, and critical systems.
The laboratory stands out for the development of integrated computational frameworks, such as Harbinger, DALToolbox, and TSPred, which are widely used by the scientific community and made available as packages on CRAN. These frameworks incorporate state-of-the-art methods in machine learning, deep learning, and preprocessing techniques, enabling everything from offline analysis to online detection and forecasting applications. DAL maintains a strong integration between research and practice, applying its solutions in areas such as finance, healthcare, urban mobility, environment, energy, and information security, always aiming to extract actionable knowledge from large volumes of data.
DAL’s work is characterized by national and international collaborations with research institutions, companies, and government agencies, fostering the transfer of knowledge and technology. Its projects have a direct impact on different sectors, contributing to scientific advances and data-driven decision-making. In addition, the group is dedicated to training highly qualified human resources, involving undergraduate and graduate students in its research, and to disseminating knowledge through publications, open-source software, scientific events, and science outreach activities.