Mariana Recamonde Mendoza

Institute of Informatics - UFRGS

I supervise undergraduate and graduate students working with machine learning, bioinformatics, and computational biology, or in the intersection across these areas. Our research aims to advance machine learning methodologies while promoting their responsible application to healthcare and biomedical problems. Supervision emphasizes methodological rigor, interpretability, robustness, and trustworthy AI, particularly in projects involving clinical data and genomics. Most projects are developed within the Machine Learning & Applications in Biomedical Data Lab (MLAB) and, depending on the topic, may involve interdisciplinary collaboration with researchers in life sciences and related fields.

If you are interested in our research topics and would like to contribute to advancing knowledge on real-world challenges in Biology and Medicine, consider applying for research supervision at the undergraduate or graduate (MSc/PhD) level. Graduate students are enrolled in the Graduate Program in Computer Science (PPGC). I welcome motivated students interested in interdisciplinary research within my areas of expertise.

Ongoing supervisions:

PhD students

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

MSc Students

• Guilherme Brockhof Bueno de Oliveira Malta, PPGC/INF/UFRGS. Start Date: 2025.
• Luciano Luz Beyloni Farias, PPGC/INF/UFRGS. Start Date: 2025.
• Mateus Balda Mota, PPGC/INF/UFRGS. Start Date: 2025.
• 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.

Undergraduate students

• Caroline Bauman Bertti, Scientific initiation, CCA/EE/UFRGS
• Kamille Konarzewski, Scientific initiation, CIC/INF/UFRGS
• Maximus Borges da Rosa, Scientific initiation, CIC/INF/UFRGS
• Eduarda Tessari Pereira, Undergraduate thesis supervision, CIC/INF/UFRGS
• Lucca Dellazen Claus, Undergraduate thesis supervision, CIC/INF/UFRGS
• Luís Coelho, Undergraduate thesis supervision, CIC/INF/UFRGS
• Rafael Weber Becker, Undergraduate thesis supervision, CIC/INF/UFRGS

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

MSc Students

• Alice Vian, MSc Dissertation, PPGC/INF/UFRGS, 2025
• [Dissertation] Explorando aprendizado supervisionado para avaliar a influência de parâmetros de aquisição na qualidade de imagens de ressonância magnética: um estudo de caso com metadados DICOM reais
• 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

• Grace Feijó, Specialization in Software Engineering for Applications in Data Science, INF/UFRGS, 2026
• Guilherme Mafra Soares, Specialization in Software Engineering for Applications in Data Science, INF/UFRGS, 2026
• Vanessa Paula Resmini, Specialization in Software Engineering for Applications in Data Science, INF/UFRGS, 2026
• 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

• Ana Lumertz Schardosim, Undergraduate thesis supervision, CIC/INF/UFRGS, 2025
• Ana Carolina de Castilhos Ferreira, Undergraduate thesis supervision, ECP/INF/UFRGS, 2025
• Arthur Prochnow Baumgardt, Undergraduate thesis supervision, ECP/INF/UFRGS, 2025
• Vitor Caruso Rodrigues Ferrer, Undergraduate thesis supervision, CIC/INF/UFRGS, 2025
• Análise do impacto da COVID-19 no desenvolvimento do transtorno de estresse pós-traumático na população brasileira: um estudo com aprendizado de máquina
• Nikolas Tesche, Undergraduate thesis supervision, CIC/INF/UFRGS, 2025
• Desenvolvimento de modelo de aprendizado de máquina para classificar o motivo de compra de produtos a partir de notas fiscais eletrônicas
• 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

• Gabriel Leal, Scientific initiation, CIC/INF/UFRGS, 2025
• [Paper] Can Data Complexity Measures Detect Pre-Training Bias in Machine Learning? A Case-Study with Health Data, SBCAS, 2025
• Julia Kasali Lima, Scientific initiation, Biomedicine/UFCSPA, 2025
• 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