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
Dr. Barros received his BSc degree in Computer Science from UFPel (2007), his MSc degree in Computer Science from PUCRS (2009), and his PhD degree in Computer Science and Computational Mathematics from USP (2013). He was a visiting research assistant at the University of Kent, UK, between 2012 and 2013. Dr. Barros received the "Best Thesis in Computer Science Award" from both the Brazilian Computer Society (SBC) and CAPES, due to his outstanding PhD dissertation entitled "On the automatic design of decision-tree induction algorithms". Currently he is a member of PPGCC, where he leads the Machine Learning Theory and Applications research group (MALTA). He has published over 100 refereed papers in premier journals and conferences such as IEEE Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision (ICCV), International Conference on Machine Learning (ICML), AAAI, IEEE Transactions on Evolutionary Computation, ACM Computing Surveys, among others. He received the best paper award in numerous occasions in conferences such as ACM GECCO, IEEE CEC, IJCNN, FLAIRS, and BRACIS. His research project received the Google Research Awards for Latin America in three consecutive editions. He supervises MSc and PhD students in topics related to Machine Learning and Evolutionary Computation, with applications to computer vision, natural language processing, audio processing, and bioinformatics. He is co-founder and Research Director of Teia Labs, the first Artificial Intelligence startup of Rio Grande do Sul. (Source: Lattes Curriculum)
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Decision-tree induction is one of the most employed methods to extract knowledge from data, since the representation of knowledge is very intuitive and easily understandable by humans. There are several distinct strategies for decision-tree induction, each one presenting advantages and disadvantages according to its corresponding inductive bias. These strategies have been continuously imp…
In this project, we present a summary of the research activities which will be performed between August 2012 and June 2013 as a part of the research projectentitled Automatically Designing Decision Tree Induction Algorithms (in portuguese, Um meta-learner para indução de árvores modelo por meio de programação genética). During this period, the student will be staying at the University of …
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