Assistant Professor

Faculty of Computing - Federal University of Mato Grosso do Sul

Short Bio

I am an Assistant Professor (in Portuguese, Professor Adjunto) at the Faculty of Computing of the Federal University of Mato Grosso do Sul in Brazil. My main research areas are Machine Learning, Data Mining and Text Mining. I am currently working on Semi-Supervised Clustering, Deep Embedding Clustering, One Class Classification, Fake News Detection and Educational Data Mining.

Interests

  • Artificial Intelligence
  • Data and Text Mining
  • Machine Learning
  • Semi-supervised Clustering
  • Educational Data Mining

Education

  • PhD in Computer Science, 2013

    Institute of Mathematics and Computer Science - University of Sao Paulo

  • PhD in Computer Science (Double Degree), 2013

    University of Porto

  • MSc in Computer Science, 2009

    Institute of Mathematics and Computer Science - University of Sao Paulo

  • BSc in Computer Science, 2006

    Pontifical Catholic University of Minas Gerais

Recent Publications

(2020). TextCSN: a Semi-Supervised Approach for Text Clustering Using Pairwise Constraints and Convolutional Siamese Network. ACM SAC 2020.

Video DOI

(2020). Machine learning for suicidal ideation identification on Twitter for the Portuguese language. BRACIS 2020.

DOI

(2017). Learning a Fast Bipartite Ranker for Text Documents using Lexicographical Rankers and ROC Curves. ICDAR 2017.

DOI

(2017). Constrained Hierarchical Clustering for News Events. IDEAS 2017.

DOI

(2017). Integrating distance metric learning and cluster-level constraints in semi-supervised clustering. IJCNN 2017.

Video DOI

(2017). Save the Data! An Intelligent Approach to Avoid Data Loss. ENIAC 2017.

PDF

(2017). Websensors Analytics: Learning to sense the real world using web news events. WEBMEDIA 2017.

PDF

(2016). A multidimensional data model for the analysis of learning management systems under different perspectives. FIE 2016.

DOI

(2013). Comparing Relational and Non-relational Algorithms for Clustering Propositional Data. ACM SAC 2013.

DOI

Research Projects

Aprendizado de Máquina Baseado em Uma Única Classe: Algoritmos e Aplicações
Aprendizado de Websensors para Agronegócios
Aplicação de algoritmos de aprendizado de máquina semissupervisionado para a descoberta e gestão de conhecimento em bases de dados

Research Lab

Lia Logo

I'm a member of LIA (Artificial Intelligence Laboratory) at FACOM / UFMS. LIA currently has 9 faculty members as main researchers, working with more than 30 students and other associated researchers. Our projects are focused in Machine Learning, Data and Text Mining, Natural Language Processing, Robotics, among other related areas.

Teaching

Semesters Course (U)ndergraduate / (G)raduate
2019 / 2, 2018 / 2, 2017 / 2 Algorithms and Object-Oriented Programming II U
2019 / 1, 2018 / 1, 2016 / 1, 2015 / 2, 2015 / 1 Algorithms and Object-Oriented Programming I U
2020 / 1, 2019 / 1, 2017 / 2, 2016 / 2, 2015 / 1, 2014 / 2 Artificial Intelligence U
2016 / 2, 2021 / 1 Artificial Intelligence G
2017 / 1 Database Systems U
2020 / 1, 2021 / 1 Decision Support Systems U
2019 / 2 Topics in Artificial Intelligence U

Students

Masters Students

Name Work title Start year
Shih Ting Ju One-class classification using semi-supervised clustering 2019

Undergraduate Students

Name Work title Start year
Alison Iuri Oghino de Moura One-class classification for fake news detection 2019

Former Students

Masters Students

Name Work title Period
Leonardo Fuchs Alves Generating search strings for secondary studies using text mining 2018 - 2020
Lucas Akayama Vilhagra TextCSN: A semisupervised approach for text clustering thorugh paired constraints and convolutional siamese networks 2017 - 2019
Yuri Karan Benevides Tomas Metric learning for semi-supervised clustering 2015 - 2017
João Domingos Ferreira Mundim (co-advisor) Miltiview event learning for websensor construction 2015 - 2018
Lucas de Souza Rodrigues (co-advisor) FlexRank: a fast lexicographic ranker 2014 - 2016
Ronaldo de Oliveira Florence (co-advisor) Semi-supervised clustering for websensors generation 2015 - 2018

Undergraduate Students

Name Work title Period
Bruno Nazário Rodrigues Student profile mining in educational environments 2015 - 2016
Caíque de Paula Figueiredo Coelho Effort prediction in software development through Machine Learning 2017
Doglas Wendll Sorgatto Student profile mining in educational environments 2015 - 2016
Isabella Bicalho Frazetto Clustering of MicroRNAs in Carcinomas through Latent Dirichlet Allocation 2019
Jorge Luís Melgarejo Fake news detection through transductive learning 2018
Jordan Butkenicius Malheiros Analysing Brazilian laws using Text Mining 2017
Lucas Akayama Vilhagra Sentiment analysis in social networks using semi-supervised clustering 2017
Mateus Vieira Fidelis Sentiment analysis in publications about FIFA 2018 World Cup in social networks 2018
Matheus dos Santos Silva Using BERT for question answering 2020
Pedro Henrique da Silva Souza Semi-supervised clustering for market segmentation 2016 - 2017
Sandys de Castro Nunes Recommending automobile parts using Machine Learning 2019
Silas Augusto Fernandes do Carmo Recommending specialists for public positions using text mining 2019
Victoria Serra de Lima Moraes Semi-supervised document clustering through distance metric learning 2014 - 2016
Vinícios Faustino Carvalho Aplying HCAC-ML in document clustering 2018 - 2019
Vinícios Faustino Carvalho Machine learning for suicidal ideation identification on Twitter for the Portuguese language 2020
Vitor Hugo Pereira Ribeiro Exploring Machine Learning algorithms for students dropout prediction in higher education 2017 - 2018

Contact

  • bruno@facom.ufms.br
  • +55 67 33457851
  • Faculty of Computing, Federal University of Mato Grosso do Sul, Av. Costa e Silva, s/nº, Bairro Universitário, Campo Grande, MS 79070-900