Mariana Recamonde Mendoza

Institute of Informatics - UFRGS

If you are an enthusiastic of Machine Learning, Bioinformatics or Computational Biology, and would like to work for advancing our knowledge on real-world challenging problems in Biology or Medicine, consider applying for research supervision either at undergraduate or graduate (MSc/PhD) levels. Graduate students are enrolled in the Graduate Program in Computer Science (PPGC). I'm always looking for motivated and hard-working students, interested in interdisciplinary projects within my research fields.

I had the pleasure to work with talented students pursuing degrees (at undergraduate or graduate levels) in computer sciences and life sciences courses. Below I list current and past supervisions (ordered by degree type and completion year).

Ongoing supervisions:

PhD students

• Bianca Matos de Barros, PPGC/INF/UFRGS. Start Date: 2023.
• Renan Soares de Andrade, PPGC/INF/UFRGS. Start Date: 2024.

Master's Degree students

• Edmar Junyor Bevilaqua, PPGC/INF/UFRGS. Start Date: 2025.
• Laura Galant Speggiorin, PPGC/INF/UFRGS. Start Date: 2025.
• Silmara Barnabé, PPGC/INF/UFRGS. Start Date: 2024.
• Felipe André Bach Alves, PPGC/INF/UFRGS. Start Date: 2024.
• Augusto Exenberger Becker, PPGC/INF/UFRGS. Start Date: 2024.
• Diego Dimer Rodrigues, PPGC/INF/UFRGS. Start Date: 2023.
• Gabriela Oliveira, PPGC/INF/UFRGS. Start Date: 2023.
• Gabriel Martini, PPGC/INF/UFRGS. Start Date: 2023.
• Alice Vian, PPGC/INF/UFRGS. Start Date: 2022.

Undergraduate students

• Ana Lumertz Schardosim, Undergraduate thesis supervision, CIC/INF/UFRGS
• Ana Carolina de Castilhos Ferreira, Undergraduate thesis supervision, ECP/INF/UFRGS
• Arthur Prochnow Baumgardt, Undergraduate thesis supervision, ECP/INF/UFRGS
• Rafael Weber Becker, Undergraduate thesis supervision, CIC/INF/UFRGS
• Vitor Caruso Rodrigues Ferrer, Undergraduate thesis supervision, CIC/INF/UFRGS
• Gabriel Leal, Scientific initiation, CIC/INF/UFRGS
• Julia Kasali Lima, Scientific initiation, Biomedicine/UFCSPA

Completed supervisions:

PostDocs

• Giovanna Câmara Giudicelli, PostDoc, NBioinfo/HCPA, 2023

PhD students

• Ivaine Tais Sauthier Sartor, PhD Thesis, PPGBM/UFRGS, 2019 (co-supervision with Prof. Patricia Ashton-Prolla)
• [Thesis] Análise do papel de Tubby-like protein 3 (TULP3) como biomarcador de diagnóstico e prognóstico, avaliação de seu papel na carcinogênese e implicações para terapia do adenocarcinoma ductal pancreático
• [Paper] TULP3: A potential biomarker in colorectal cancer?, PLoS One, 2019
• Graziela Hünning Pinto, PhD Thesis, PPGCardio/UFRGS, 2018 (co-supervision with Prof. Andréia Biolo)
• [Thesis] Análise do perfil de miRNAs e vias de sinalização relacionadas em modelo animal de hipertrofia cardíaca fisiológica induzida por natação

Master's Degree students

• Heloísa Oss Boll, MSc Dissertation, PPGC/INF/UFRGS, 2024
• [Dissertation] Graph Neural Networks for Clinical Risk Prediction Based on Patient Similarity Graphs
• [Paper] Graph neural networks for clinical risk prediction based on electronic health records: A survey, Journal of Biomedical Informatics, 2024

• Thomas Vaitses Fontanari, MSc Dissertation, PPGC/INF/UFRGS, 2023
• [Dissertation] Investigating Pooling in Graph Neural Networks for Cancer Genomics Classification and the Generalizability of Pan-cancer Models to Cancer-Specific Predictions
• [Paper] Cross-validation Strategies for Balanced and Imbalanced Datasets, Brazilian Conference on Intelligent Systems (BRACIS), 2022
• [Paper] Evaluating the Generalization of Neural Network-Based Pan-Cancer Classification Models for Cohort-Specific Predictionss, Brazilian Symposium on Bioinformatics (BSB), 2024
• Emanoel Vianna, MSc Dissertation, PPGC/INF/UFRGS, 2023
• [Dissertation] Explorando redes neurais de grafos para predição de interações miRNA-alvo associadas a câncer em grafos heterogêneos
• [Paper] Prediction of cancer-related miRNA targets using an integrative heterogeneous Graph Neural Network-based method, Brazilian Conference on Intelligent Systems (BRACIS), 2023
• Renan Soares de Andrades, MSc Dissertation, PPGC/INF/UFRGS, 2023
• [Dissertation] Prediction of Cancer Driver Genes with Graph Neural Networks: A Comparative Analysis and a Graph Convolutional Network-based Model
• [Paper] Machine learning methods for prediction of cancer driver genes: a survey paper, Briefings in Bioinformatics, 2022
• [Paper] Predicting Cancer Driver Genes: Leveraging Graph Convolutional Networks and Ensemble Learning, IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2024
• Hortênsia Costa de Barcelos, MSc Dissertation, PPGC/INF/UFRGS, 2020 (co-supervision with Profa. Viviane Moreira)
• [Dissertation] Detecção e Fusão de Atributos Duplicados para Mineração de Dados
• [Paper] Identifying and Fusing Duplicate Features for Data Mining, Simpósio Brasileiro de Bancos de Dados (SBBD), 2020
• Sheyla Velasques Paladini, MSc Dissertation, PPGCardio/UFRGS, 2019
• [Dissertation] Identificação de candidatos a biomarcadores de rejeição em transplante cardíaco a partir de transcriptomas: revisão sistemática e meta-análise
• [Paper] Identification of Candidate Biomarkers for Transplant Rejection from Transcriptome Data: A Systematic Review, Molecular Diagnosis & Therapy, 2019
• Laura Amaya Torres, MSc Dissertation, PPGC/INF/UFRGS, 2019 (co-supervision with Prof. Anderson Maciel)
• [Dissertation] Automatic Generation of Patient-Specific 3D Models of Organs Using an Unified Deep Learning Approach
• Eduardo Soares de Abreu, MSc Dissertation, PPGCOMP/C3/FURG, 2019 (co-supervision with Prof. Adriano Werhli)
• [Dissertation] Descoberta de possíveis biomarcadores utilizando análise topológica de redes de co-expressão gênica
• João Pedro Hartmann Salomão, MSc Dissertation, PPGCOMP/C3/FURG, 2019 (co-supervision with Prof. Karina Machado)
• [Dissertation] Modelos de classificação baseados em painel de genes e gene-especifico para a predição da patogenicidade de variantes genômicas
• Jorge Cristhian Chamby Diaz, MSc Dissertation, PPGC/INF/UFRGS, 2018 (co-supervision with Prof. Ana L. C. Bazzan)
• [Dissertation] An Incremental Gaussian Mixture Network for Data Stream Classification in Non-Stationary Environments.
• [Paper] Dynamic Correlation-Based Feature Selection for Feature Drifts in Data Streams, Brazilian Conference on Intelligent Systems (BRACIS), 2019
• [Paper] Adaptive Incremental Gaussian Mixture Network for Non-Stationary Data Stream Classification, International Joint Conference on Neural Networks (IJCNN), 2018

Specialization students

• Robertson Novellino Ferraz, Specialization in Data Science, INF/UFRGS, 2025
• Flavio Melo Gondim, Specialization in Data Science, INF/UFRGS, 2024
• Ronaldo Silva Virgínio Filho, Specialization in Data Science, INF/UFRGS, 2024
• André Pereira Viveiros., Specialization in Data Science, INF/UFRGS, 2023
• Júlio César Pereira Antunes, Specialization in Data Science, INF/UFRGS, 2023
• Ruchelli França de Lima, Specialization in Big Data & Data Science, INF/UFRGS, 2019

Undergraduate students - Thesis Supervision

• Afonso Martini Spezia, Undergraduate thesis supervision, ECP/INF/UFRGS, 2024
• Estudo de estratégias de validação cruzada baseadas em clusters
• Laura Galant Speggiorin, Undergraduate thesis supervision, CIC/INF/UFRGS, 2024
• Development of a machine learning model for molecular signature identification and early diagnostic support of Autism Spectrum Disorder
• Lucas Lima de Melo, Undergraduate thesis supervision, CIC/INF/UFRGS, 2024
• A study on graph neural networks for classification tasks and model interpretability on genomic datasets
• João Maieron Martins, Undergraduate thesis supervision, CIC/INF/UFRGS, 2024.
• Explorando dados climáticos e do Google Trends na predição de casos de dengue no Brasil: uma abordagem com aprendizado de máquina
• Augusto Exenberger Becker, Undergraduate thesis supervision, ECP/INF/UFRGS, 2023
• Assessing Data Leakage Effects on the Performance Estimates of Machine Learning Classifiers
• Daniel Matos de Castro, Undergraduate thesis supervision, CIC/INF/UFRGS, 2023
• Viés racial ou pequeno tamanho amostral? Investigando o impacto de disparidade racial em dados genômicos na análise de sobrevida em câncer
• Diego Dimer Rodrigues, Undergraduate thesis supervision, CIC/INF/UFRGS, 2023
• Assessing pre-training bias in Health data and estimating its impact on machine learning algorithms
• Gabriel Beretta, Undergraduate thesis supervision, CIC/INF/UFRGS, 2023
• Comparação de estratégias computacionais para integração de dados ômicos na classificação de subtipos de tumores
• Taiane de Oliveira Peixoto, Undergraduate thesis supervision, CIC/INF/UFRGS, 2023
• Comparação de estratégias para lidar com o desbalanceamento de classes: um estudo de caso com dados de mortalidade neonatal no Rio Grande do Sul
• Carlos Daniel Andrade, Undergraduate thesis supervision, CIC/INF/UFRGS, 2022
• Estudo sobre a complexidade de dados ômicos: uma análise para a predição de sobrevida em diferentes tipos de câncer
• [Paper] Study on the Complexity of Omics Data: An Analysis for Cancer Survival Prediction, Brazilian Symposium on Bioinformatics (BSB), 2022
• Felipe Colombelli, Undergraduate thesis supervision, CIC/INF/UFRGS, 2022
• Assessing the Applicability of Graph Neural Networks for Cancer Staging Using Sample Similarity Networks
• Guilherme Brockhof Bueno de Oliveira Malta, Undergraduate thesis supervision, CIC/INF/UFRGS, 2022
• An interpretable machine learning approach for predicting sleep quality in three temporal waves throughout the COVID-19 pandemic
• Iron Prando da Silva, Undergraduate thesis supervision, CIC/INF/UFRGS, 2022 (co-supervision with Prof. João Comba)
• Normalizing Flows: A Study On Models’ Coherence
• Ricardo Lampert, Undergraduate thesis supervision, ECP/INF/UFRGS, 2022 (co-supervision by Profa. Viviane Moreira)
• Stability and Performance of Machine Learning Feature Selection Methods: a Case Study on COVID-19 Diagnosis Datasets
• Ana Paula Carolino de Oliveira Mello, Undergraduate thesis supervision, CIC/INF/UFRGS, 2021
• Use of embedding concatenation and ensemble to improve node classification on graphs
• Bernardo Trevizan, Undergraduate thesis supervision, CIC/INF/UFRGS, 2021
• Homogeneous ensemble feature selection for breast cancer biomarker identification from microarray data
• [Paper] Ensemble Feature Selection Compares to Meta-analysis for Breast Cancer Biomarker Identification from Microarray Data, International Conference on Computational Science and Its Applications (ICCSA), 2021
• Gabriel Henrique da Silva Stepien, Undergraduate thesis supervision, CIC/INF/UFRGS, 2021 (co-supervision with Prof. Weverton Cordeiro)
• Uma Aplicação para o Monitoramento da Disseminação do Mosquito Aedes aegypti
• Lauren Silva Rolan Sampaio, Undergraduate thesis supervision, ECP/INF/UFRGS, 2021
• An Overview of AI-enabled Attacks: concepts, state-of-the-art, and evaluation of prototypes
• Luís Augusto Weber Mercado, Undergraduate thesis supervision, ECP/INF/UFRGS, 2021
• Detection of Infant Guinea pig Vocalizations using Machine Learning
• Pedro Durayski Saccilotto, Undergraduate thesis supervision, ECP/INF/UFRGS, 2021
• Desenvolvimento de modelos de aprendizado de máquina para detecção de fenótipos humanos com base em assinaturas do microbioma
• Flávia de Ávila Pereira, Undergraduate thesis supervision, CIC/INF/UFRGS, 2020
• Analisando padrões no consumo de álcool entre estudantes de Medicina brasileiros: uma abordagem de aprendizado de máquina
• [Paper] Patterns of high-risk drinking among medical students: a web-based survey with machine learninga, Computers in Biology and Medicine, 2021
• Gabriel de Souza Seibel, Undergraduate thesis supervision, ECP/INF/UFRGS, 2020
• Classification of suicidality in a large occupational cohort: an analysis of machine learning algorithms applied to the ELSA-Brasil study
• [Paper] Suicide risk classification with machine learning techniques in a large Brazilian community sample, Psychiatry Research, 2023
• Lucas Nunes Ronchetti, Undergraduate thesis supervision, CIC/INF/UFRGS, 2020 (co-supervision with Prof. Weverton Cordeiro)
• Aplicativo móvel para Mapeamento Colaborativo de Focos de Aedes aegypti Utilizando Técnicas de Machine Learning.
• Rodrigo Haas Bueno, Undergraduate thesis supervision, Biomedicine/ICBS/UFRGS, 2019
• Metanálise de dados de transcriptoma revela módulos patofisiológicos envolvidos com a fibrilação atrial
• [Paper] Meta‑analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation, Molecular Diagnosis & Therapy, 2020
• Andre Kenji Kagawa Nunes, Undergraduate thesis supervision, CIC/INF/UFRGS, 2019
• Análise do impacto de feature selection e detecção de concept drift na classificação de fluxos de dados em evolução
• Vinícius Fraga de Castro, Undergraduate thesis supervision, CIC/INF/UFRGS, 2019
• Auditoria em questionário de estudo epidemiológico utilizando os algoritmos K-Means e FindCBLOF
• Henrique Vargas Dambros, Undergraduate thesis supervision, CIC/INF/UFRGS, 2019
• Predição de alvos de microRNAs utilizando aprendizado semi-supervisionado e classificação baseada em uma única classe
• Gabriel Marangoni Moita, Undergraduate thesis supervision, ECP/INF/UFRGS, 2019
• Combining Performance and Diversity Measures for Optimizing Classification Ensembles via a Genetic Algorithm in the miRNA-Target Prediction Problem
• Itamar José Guimarães Nunes, Undergraduate thesis supervision, Biotechnology/CBiot/UFRGS, 2018
• Gene Expression Analysis Plataform (GEAP): uma plataforma flexível e intuitiva para análises de transcriptoma
• [Paper] Gene Expression Analysis Platform (GEAP): A highly customizable, fast, versatile and ready-to-use microarray analysis platform, Genetics and Molecular Biology, 2022
• Check GEAP, developed by Itamar: a free, portable, and user friendly software to analyze microarray data!
• Lucas Hennemann Perin, Undergraduate thesis supervision, ECP/INF/UFRGS, 2018
• Machine learning approaches for predicting diabetes and determining risk factors from epidemiological data
• Marcelo Schreiber Fernandes, Undergraduate thesis supervision, ENGELE/DELET/UFRGS, 2018
• Identificação do mosquito Aedes aegypti através de áudio utilizando técnicas de machine learning
• [Paper] Detecting Aedes aegypti Mosquitoes through Audio Classification with Convolutional Neural Networks, Computers in Biology and Medicine, 2021
• Luis Pedro Silvestrin, Undergraduate thesis supervision, ECP/INF/UFRGS, 2018
• MR Spectroscopy Signal Quantification Using Deep Learninga
• Cristian Felipe Schneider, Undergraduate thesis supervision, ENGELE/DELET/UFRGS, 2017
• Machine Learning Aplicado na Previsão de Resultados de Partidas de Futebol: Um Estudo de Caso para Comparação de Diferentes Classificadores
• Rodrigo Augusto Scheller Boos, Undergraduate thesis supervision, ECP/INF/UFRGS, 2017
• Funções de Escolha Social para Elaboração de Consenso em Aprendizado de Máquina Descentralizado: um Estudo em Problemas de Classificação Multiclasse

Undergraduate students - Scientific Initiation

• Julia Mombach, Scientific initiation, CIC/INF/UFRGS, 2024
• João Gabriel Zandoná, Scientific initiation, CIC/INF/UFRGS, 2023
• Laura Galant Speggiorin, Scientific initiation, CIC/INF/UFRGS, 2022
• Tiago Froes, Scientific initiation, ECP/INF/UFRGS, 2022
• Vitoria Colonetti Benedet, Scientific initiation, CIC/INF/UFRGS, 2022
• Lucas Lima de Melo, Scientific initiation, CIC/INF/UFRGS,2022
• Felipe Colombelli, Scientific initiation, CIC/INF/UFRGS, 2021
• [Paper] A hybrid ensemble feature selection design for candidate biomarkers discovery from transcriptome profiles, Knowledge-Based Systems, 2022
• Bruno Guilhem, Scientific initiation, CIC/INF/UFRGS, 2020
• João Schapke, Scientific initiation, CIC/INF/UFRGS, 2020
• [Paper] EPGAT: Gene Essentiality Prediction With Graph Attention Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022
• Bernardo Trevizan, Scientific initiation, CIC/INF/UFRGS, 2019
• [Paper] A comparative evaluation of aggregation methods for machine learning over vertically partitioned data, Expert Systems with Applications, 2020
• Guilherme Brockhof Bueno de Oliveira Malta, Scientific initiation, CIC/INF/UFRGS, 2018
• Rodrigo Haas Bueno, Scientific initiation, Biomedicine/ICBS/UFRGS, 2018
• Itamar José Guimarães Nunes, Scientific initiation supervision, Biotechnology/CBiot/UFRGS, 2018