João Correia

Pontifical Catholic University of Rio de Janeiro — Brazil

Computer Science · Physical Sciences

7h-index305citations21works1.12yr avg
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Research Topics

Computational Drug Discovery Methods(7), Machine Learning in Materials Science(4), Software Engineering Research(3), Analytical Chemistry and Chromatography(3), Software Reliability and Analysis Research(3)

Publications21 total

Case Study: Applying Fuzzing to REST APIs in a Large-Scale Industrial Setting
2025
FeatureRef: Towards Effective Refactoring of Features
SSRN Electronic Journal·2025Open Access
Analysis of Automated Document Relevance Annotation for Information Retrieval in Oil and Gas Industry
2025Open Access
Slithering Through Exception Handling Bugs in Python Understanding Root Causes, Symptoms, and Fixes
SSRN Electronic Journal·2025Open Access
Designing Data Architecture for Industry 4.0 Applications: Lessons Learned from a Brazilian Multinational Industry
SSRN Electronic Journal·2025Open Access
Explainability of Models Applied to Obstetric Medical Imaging
SSRN Electronic Journal·2025Open Access
On the Investigation of Exception Pull Request Characteristics: Exploring the Apache Ecosystem
2024
Ensemble learning for fetal ultrasound and maternal–fetal data to predict mode of delivery after labor induction
Scientific Reports·2024· 9 citedOpen Access
Combining Evolutionary Algorithms with Reaction Rules Towards Focused Molecular Design
Proceedings of the Genetic and Evolutionary Computation Conference·2023Open Access
Don’t Forget the Exception! : Considering Robustness Changes to Identify Design Problems
2023· 4 cited
Evaluating molecular representations in machine learning models for drug response prediction and interpretability
Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics·2022· 39 citedOpen Access
Development of Deep Learning approaches to predict relationships between chemical structures and sweetness
2022 International Joint Conference on Neural Networks (IJCNN)·2022· 6 citedOpen Access
Predicting the number of biochemical transformations needed to synthesize a compound
2022 International Joint Conference on Neural Networks (IJCNN)·2022· 1 citedOpen Access
Generative Deep Learning for Targeted Compound Design
Journal of Chemical Information and Modeling·2021· 179 cited
A Comparison of Different Compound Representations for Drug Sensitivity Prediction
Lecture notes in networks and systems·2021· 3 cited
Combining Multi-objective Evolutionary Algorithms with Deep Generative Models Towards Focused Molecular Design
Lecture notes in computer science·2021· 7 cited
Brazilian Data Scientists: Revealing their Challenges and Practices on Machine Learning Model Development
2020· 8 cited
How Does Incomplete Composite Refactoring Affect Internal Quality Attributes?
2020· 27 cited
Artificial Intelligence in Music, Sound, Art and Design
Lecture notes in computer science·2020· 3 cited
Artificial Intelligence in Biological Activity Prediction
Advances in intelligent systems and computing·2019· 5 citedOpen Access
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Frequent Co-authors

Miguel Rocha(8), Alessandro Garcia(6), Vítor Pereira(5), Baldoíno Fonseca(4), Caio Barbosa(4), Rafael de Mello(4), Delora Baptista(3), Ana Carla Bibiano(3), Daniel Coutinho(3), Anderson Uchôa(3), Juliana Alves Pereira(3), Wesley K. G. Assunção(3), T. Ferra de Sousa(2), Bruno Pereira(2), Eduardo Fernandes(2), Rohit Gheyi(2), Márcio Ribeiro(2), Iolanda Ferreira(2), Ana Luísa Areia(2), Anderson Oliveira(2)