{"id":1725,"date":"2025-04-17T22:36:21","date_gmt":"2025-04-18T01:36:21","guid":{"rendered":"https:\/\/sbbd.org.br\/2025\/?page_id=1725"},"modified":"2025-08-18T14:15:48","modified_gmt":"2025-08-18T17:15:48","slug":"ctdbd-en","status":"publish","type":"page","link":"https:\/\/sbbd.org.br\/2025\/en\/ctdbd-en\/","title":{"rendered":"CTDBD"},"content":{"rendered":"\t\t
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Thesis and Dissertation Contest on Databases (CTDBD)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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We are pleased to announce the works accepted for the second phase of the Thesis and Dissertation Contest on Databases \u2013 CTDBD of SBBD 2025. The works will be presented on the SBC channel (https:\/\/www.youtube.com\/@sbcoficial\/) on the dates and times defined below. Congratulations to the selected participants!<\/span><\/p>

DOCTORATE<\/b><\/span><\/h3>

Online session: 08\/12 (Tuesday), 6:00 PM
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Committee<\/strong>: Karin Becker (UFRGS), Ricardo Ciferri (UFSCar), Sergio Lifschitz (PUC-Rio)
<\/span>Link:<\/strong> To watch the Master’s dissertation presentations: https:\/\/www.youtube.com\/watch?v=JOUjBmXQKgA<\/p>

Title<\/strong>: A Comprehensive Exploitation of Instance Selection Methods for Automatic Text Classification \u2014 \u201cDoing More with Less\u201d
Author: Washington Cunha (DCC – UFMG)
Advisor: Marcos Andr\u00e9 Gon\u00e7alves (DCC – UFMG)
Co-advisor: Leonardo Chaves Dutra da Rocha (DCOMP – UFSJ)<\/p>

Title<\/strong>: Provenance Data as First-Class Citizens for Workflow Analysis in Deep Learning
Author: D\u00e9bora Pina (PESC\/COPPE – UFRJ)
Advisor: Marta L. de Queir\u00f3s Mattoso (PESC\/COPPE – UFRJ)
Co-advisor: Daniel Cardoso Moraes de Oliveira (IC – UFF)<\/p>

Title<\/strong>: Provenance Data as First-Class Citizens for Workflow Analysis in Deep Learning
Author: D\u00e9bora Pina (PESC\/COPPE – UFRJ)
Advisor: Marta L. de Queir\u00f3s Mattoso (PESC\/COPPE – UFRJ)
Co-advisor: Daniel Cardoso Moraes de Oliveira (IC – UFF)<\/p>

MASTER’S<\/b><\/span><\/h3>

Online session: 08\/14 (Thursday), 6:00 PM<\/strong><\/p>

Committee<\/strong>: \u00c2ngelo Brayner (UFC), F\u00e1bio Porto (LNCC), Marco Ant\u00f4nio Casanova (PUC-Rio)<\/span>
<\/b>Link:<\/strong> To watch the PhD thesis presentations: https:\/\/www.youtube.com\/live\/i3yD9Jp9QFw<\/p>

Title<\/strong>: CarboFarm: Data Integration and Knowledge Generation for Agricultural GHG Inventories
Author: Luiz Fernando Santos (DCC-UFJF)
Advisor: Regina Maria Maciel Braga (DCC-UFJF)
Co-advisor: Jos\u00e9 Maria N. David (DCC-UFJF)<\/p>

Title<\/strong>: Combining Ontology and Deep Learning for Sensor Data Integration and Critical Event Prediction
Author: Jefferson do Nascimento Amar\u00e1 (DCC-UFJF)
Advisor: Victor Str\u00f6ele de Andrade Menezes (DCC-UFJF)
Co-advisor: Regina Maria Maciel Braga (DCC-UFJF)<\/p>

Title<\/strong>: BioF4C-Frame: A Framework for Feature Preparation and Selection applied to Ecological Data Classification
Author: Luma Rios Delponte (INE \u2013 UFSC)
Advisor: Carina F. Dorneles (INE \u2013 UFSC)
Co-advisor: Simone S. Werner (INE \u2013 UFSC)<\/p>


CTDBD \u2013 Call for Submissions<\/span><\/strong><\/h1>

The Database Theses and Dissertations Competition (CTDBD) of the Brazilian Symposium on Databases (SBBD) aims to select and award the best PhD thesis and the best Master’s dissertation<\/strong> in the field of Databases in Brazil. The competition is open to works developed at Brazilian educational and research institutions, defended and approved between January 1, 2024, and April 30, 2025. Theses and dissertations must be related to the topics of interest of the SBBD.<\/p>

Theses and dissertations will be evaluated based on their scientific and technological contributions, as well as their potential impact on the state of the art and\/or their innovative nature in the field of Databases and data-centric applications.<\/p>

To promote high-quality research developed in Brazil and encourage broad participation from the community, CTDBD 2025 will follow the structure below: annual competition, simplified submission, online selection process, and awarding of the best dissertation and best thesis, to be presented in person at SBBD 2025.<\/p>

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IMPORTANT DATES<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Phase 1:<\/strong> Submission and ranking<\/em><\/p>