Laura O. Moraes

Biography

Laura O. Moraes is a professor at Universidade Federal do Estado do Rio de Janeiro (UNIRIO). She has a master's degree and a Ph.D. in Systems Engineering and Computer Science at COPPE / UFRJ in the artificial intelligence research field. She graduated in Electronic and Computer Engineering from the Universidade Federal do Rio de Janeiro, during which she acted as a software engineer in the UFRJ-CERN collaboration. From 2011 to 2021, she was a co-founding partner of the data science start-up Twist Systems. In 2018, she participated in the Data Science for Social Good program at the University of Chicago, developing a predictive model to identify individuals at high risk of long-term unemployment. In 2019, she was a finalist for the 2nd EPFL Engineering Ph.D. Summit and presented her doctoral research at École polytechnique fédérale de Lausanne (EPFL), Switzerland. She worked as a lecturer for the MBA in Big Data & Analytics at Fundação Getúlio Vargas in 2019 and 2020 and taught Computer Science classes at Colégio Pedro II.

Interests

Computer Science Education
Learning Analytics
Educational Data Mining
Student Performance Prediction

Education

PhD in Systems Engineering and Computer Science, 2021, Universidade Federal do Rio de Janeiro
MEng in Systems Engineering and Computer Science, 2016, Universidade Federal do Rio de Janeiro
BSc in Electronic and Computer Engineering, 2013, Universidade Federal do Rio de Janeiro

Contact

E-mail: laura@uniriotec.br

Github: lauramoraes and laura-moraes

LinkedIn: lofmoraes

CV

Publications

Google Scholar

Laura O. Moraes, Carlos Eduardo Pedreira, Carla Delgado, João Pedro Freire (2021). Machine Teaching: uma ferramenta didática e de análise de dados para suporte a cursos introdutórios de programação. Anais do II Simpósio Brasileiro de Educação em Computação, pp. 213-223, 24 a 29 de Abril, 2022, Virtual.
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Laura O. Moraes, Carlos Eduardo Pedreira, Carla Delgado, João Pedro Freire (2021). Supporting Decisions Using Educational Data Analysis. Anais Estendidos do XXVII Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia 2021), pp. 99-102, Novembro 2021, Virtual.
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Chunpai Wang, Shaghayegh Sahebi, Siqian Zhao, Peter Brusilovsky, Laura O. Moraes (2021). Knowledge Tracing for Complex Problem Solving: Granular Rank-Based Tensor Factorization. In Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (UMAP '21), pp. 179-188, June 21–25, 2021, Utrecht, Netherlands. ACM, New York, NY, USA.
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Laura O. Moraes, Carlos Eduardo Pedreira (2021). Unsupervised Concept Extraction in an Introduction to Programming Course. PhD Thesis in Systems Engineering and Computer Science - COPPE, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro.
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Laura O. Moraes, Carlos Eduardo Pedreira (2021). Clustering Introductory Computer Science Exercises Using Topic Modeling Methods. IEEE Transactions on Learning Technologies, vol. 14, no. 1, pp. 42-54, Feb. 2021.
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Laura O. Moraes, Carlos Eduardo Pedreira (2020). Designing an Intelligent Tutoring System Across Multiple Classes. 4th Educational Data Mining in Computer Science Education (CSEDM), 2020, Virtual Workshop.
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Laura O. Moraes, Carlos Eduardo Pedreira (2019). A Decision Tree Approach for the Differential Diagnosis of Chronic Lymphoid Leukemias and Peripheral B Cell Lymphomas. Computer Methods and Programs in Biomedicine, v. 178, pp. 85-90.
BIB Code DOI
Íñigo Martínez de Rituerto de Troya, Ruqian Chen, Laura O. Moraes, Pranjal Bajaj, Jordan Kupersmith, Rayid Ghani, Nuno B. Brás, Leid Zejnilovic (2018). Predicting Explaining and Understanding Risk of Long Term Unemployment. 32nd Annual Conference on Neural Information Processing Systems (NeurIPS) AI for Social Good Workshop, Canada.
PDF BIB
Laura O. Moraes, Carlos Eduardo Pedreira (2016). Classificação de Linfomas Utilizando uma Abordagem Baseada em Árvores De Decisão. Dissertação (Mestrado em Engenharia de Sistemas e Computação) - COPPE, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro.
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Louis-Martin Losier, Felipe Fink Grael, Etienne Desgagné, Fábio Hochleitner, Laura O. Moraes (2015). Cloud Based Alert System for Aggressive Natural Disasters. 15th Pan-American Conference on Soil Mechanics and Geotechnical Engineering, Argentina.
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Felipe Fink Grael, Carmen Maidantchik, Luiz Henrique Ramos de Azevedo Évora, Kaio Karam, Laura O. Moraes, Manuela Cirilli, Marzio Nessi, Kathy Pommès (2011). Glance Information System for Atlas Management. Journal of Physics: Conference Series, v. 331, n. 8, p. 082004.
PDF BIB DOI

Students

current STUDENTS

Gabriel Monteiro De Castro Xara Wanderley (2023--ongoing). Master student.
Henrique Soares Rodrigues (2023--ongoing). Master student.
Juliana Barros de Sousa (2023--ongoing). Construção de feedback automatizado para alunos em curso introdutório de programação. Undergraduate Final Course Project (CNPq).
Hugo Folloni Guarilha (2022--ongoing). Machine Teaching. Undergraduate student (Reditus e PIBIC). Co-advised with Carla Delgado.
Arthur Mendonça Sasse (2022--ongoing). Ferramenta para agrupamento de código. Undergraduate Final Course Project (CNPq). Co-advised with Carlos Eduardo Pedreira e Carla Delgado.
João Pedro Freire (2020--ongoing). Dropout and performance prediction. Undergraduate student (PIBIC). Co-advised with Carlos Eduardo Pedreira e Carla Delgado.

PAST STUDENTS

Gabriel Monteiro De Castro Xara Wanderley (2023). Arquitetura resiliente e escalável para um sistema de execução de código remoto. Undergraduate Final Course Project. Co-advised with Claudio Miceli.
Fernando Silva França e Bruno Hryniewicz Santos Cruz (2023). Biblioteca para exemplificação de álgebra linear EasyLinalg. Undergraduate Final Course Project. Co-advised with João Antonio Recio da Paixão.
Gabriel Matos Cardoso Leite (2017). Técnica de Redução de Comparações em Classificadores Multiclasse. Undergraduate Final Course Project. Co-advised with Carlos Eduardo Pedreira.

Projects

CURRENT PROJECTS

PAST PROJECTS

Machine Teaching

Ir para o projeto

At this project we aim at creating a personalized learning system in Introduction to Programming classes as a way to uncover students’ difficulties, to understand their knowledge and to provide timely feedback to keep students engaged.

Keywords:

Learning Analytics
Educational Data Mining
Computer Science Education
CSEDM

Predicting long-term unemployment in Portugal

Ir para o projeto

At this project we aim at better identifying individuals at high risk of long-term unemployment (LTU) and supporting more efficient allocation of IEFP’s resources to respond to the needs of unemployed individuals.

Keywords:

Data Science for Social Good
Long-term Unemployment
Regression

Lasso Tree

Ir para o projeto

At this project we propose a decision-tree approach for the differential diagnosis of B-cell chronic lymphoproliferative disorders using flow cytometry data.

Keywords: