(Meta 3) Yuri Dimitre Dias de Faria, Leandro A. Villas, Allan M. de Souza. Exploring Communication Efficient Methods for Homomorphic Encryption Federated Learning. IEEE Symposium on Computers and Communications (ISCC). 2025. [qualis A2]
(Meta 7) Juliano Soares; Marcelo Reis. Grafos causais e de Conhecimentos em Sistemas de Recomendação. Learning on Graphs Conference (LOG) 2025. 2025.
(Meta 3) Ekler Mattos, Augusto Domingues, Fabrício Silva, Heitor Filho and Antonio Loureiro. A Dynamic Privacy Tuning Mechanism in Mix-zones. The 21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). 2025. [qualis A4]
(Meta 3) Rafael Veiga, Lucas Bastos, Denis Rosário, Antonio Loureiro and Eduardo Cerqueira. A Resilient and Lightweight Layer Client Selection in Federated Learning. The 21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). 2025. [qualis A4]
(Meta 1 e 2) Letícia Berto, Mehdi Hellou, Alessandra Sciutti, Ricardo Gudwin, Esther Colombini, Angelo Cangelosi. A Theory of Mind Motivational Framework for Social Interaction with Autonomous Cognitive Robots. IEEE RO-MAN 2025. 2025. [qualis A2]
(Meta 2) GHEDINI, C.; SILVA, A. A.; COLOMBINI, E. Advancing Human Activity Recognition with Meta-Learning for Continual Learning. IEEE International Conference on Acoustics, Speech and Signal Processing. 2025. [qualis A1]
(Meta 3) Rafael Veiga, Renan Morais, Lucas Bastos, Denis Rosário, Daniel Guidoni and Eduardo Cerqueira. Bio-signal Multistream Architecture Classification for Federated Learning. The 21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). 2025. [qualis A4]
(Meta 6) Giovana Kerche Bonas, Marcos M. Raimundo, Marcelo Reis. Combinatorial U-Curve Optimization for Multi-Task Learning: A Task Selection Approach. International Joint Conference on Neural Networks (IJCNN 2025). 2025. [qualis A1]
(Meta 3) Cláudio Capanema, Fabricio Silva, Antonio Loureiro and Leandro Villas. Data Shift Under Delayed Labeling in Multi-Model Federated Learning. The 21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). 2025. [qualis A4]
(Meta 1 e 2) Leonardo L. Rossi, Paula D. P. Costa, Alexandre Simões, Esther L. Colombini, Ricardo Gudwin. Dribble in the Mind: Exploring Causality with Cognitive Soccer Agents. XXVIII RoboCup International Symposium. 2025. [qualis A3]
(Meta 1 e 2 – SUBMETIDO) Cleveston, I; Santana, A.; Gwdwin, R. R.; Costa, P. D. P.; Simões, A.; Colombini, E. L. InstructRobot: A Model-Free Framework for Mapping Natural Language Instructions into Robot Motion. IEEE International Conference on Robotics and Automation. 2025. [qualis A1]
(Meta 6) Jansen Silva de Brito Pereira, Giovani Valdrighi, Marcos Medeiros Raimundo. M²FGB: A Min-Max Gradient Boosting Framework for Subgroup Fairness. 2025 ACM Conference on Fairness, Accountability, and Transparency (FAccT) in Athens. 2025. [qualis A1]
(Meta 6) Sujoy Chatterjee, Everton Romanzini Colombo, Marcos Medeiros Raimundo. Multi-criteria Rank-based Aggregation for Explainable AI. International Joint Conference on Neural Networks (IJCNN 2025). 2025. [qualis A1]
(Meta 1) Eduardo Camargo, Leonardo L. Rossi, Paula D. P. Costa, Ricardo Gudwin, Esther L. Colombini. Programming a BabyBot: Cognitive Architectures Foundations for a Newborn Robot. IEEE International Conference on Development and Learning (ICDL). 2025. [qualis B4]
(Meta 7) Fillipe Santos, Julio Cesar dos Reis, Marcelo S. Reis. Segment, Recommend, and Explain: Advancing Conversational Recommender Systems with Large Language Model Agents. Conferência UMAP (ACM International Conference on User Modeling, Adaptation and Personalization). 2025.
(Meta 3) João Augusto dos Santos; Felipe Domingos da Cunha. A Data-Driven Approach to Air Quality Forecasting in Congonhas-MG. Workshop Urban Computing 2025 (DCOSS-IoT). 2025. [qualis A4]
(Meta 5) Carlos Caetano, Gabriel O. dos Santos, Caio Petrucci, Artur Barros, Camila Laranjeira, Leo S. F. Ribeiro, Júlia F. de Mendonça, Jefersson A. dos Santos, Sandra Avila. Neglected Risks: The Disturbing Reality of Children’s Images in Datasets and the Urgent Call for Accountability. ACM Conference on Fairness, Accountability, and Transparency (FAccT), Atenas, Grécia. 2025. [qualis A1] [LINK]
(Metas 1 e 2) BERTO, L. M. ; COSTA, P. D. P. ; GUDWIN, R. R. ; SIMOES, A. S. ; COLOMBINI, E. L. . A motivational-based learning model for mobile robots, Journal paper poster track, ICDL, Prague, 2025. [qualis B4]
(Meta 2) GHEDINI, C.G.; ANJOS da S., A.; COLOMBINI, E.L.; Advancing Human Activity Recognition with Meta-Learning for Continual Learning. IEEE System, Man and Cybernetics 2025. Viena, 2025. [qualis A2]
(Meta 6) Pereira, Jansen Silva de Brito, Giovani Valdrighi, and Marcos Medeiros Raimundo. “M²FGB: A Min-Max Gradient Boosting Framework for Subgroup Fairness.” ACM Conference on Fairness, Accountability, and Transparency (FAccT), Atenas, Grécia. 2025. [qualis A1]
(Metas 1 e 2) Eduardo Y. Sakabe, Eduardo Camargo, Alexandre Simões, Esther Colombini, Paula Costa, Ricardo Gudwin. An Episode Encoding Mechanism for Cognitive Architectures. 2025 Annual International Conference on Biologically Inspired Cognitive Architectures, the 16th Annual Meeting of the BICA Society (BICA 2025).
(Metas 1 e 2) BERTO, L. M.; GUDWIN, R. R; COLOMBINI, E. L. An Incremental, Intrinsically Motivated Approach for Cognitive Robots. IMOL 2025.
(Meta 3) Weld Lucas Cunha, Luis F. G. Gonzalez, Daniel L. Guidoni and Leandro A. Villas. Client-Aware Model Aggregation for \ Non-IID Data in Federated Learning. FLTA Main Track. 2025.
(Meta 3) Aissa Hadj Mohamed, Daniel Guidoni, Luis Gonzalez, Leandro Villas and Allan Souza. FedEcoSelect: A Communication-Efficient Client Selection Strategy via Predictive Similarity Estimation in Federated Learning. FLTA Main Track. 2025.
(Meta 3) Luiz Fernando Rodrigues Fonseca e Luiz Fernando Bittencourt. HVCFL: Hybrid Centralized-Decentralized Federated Learning for VANETs. FLTA. 2025.
(Meta 3) Gabriel Talasso, Allan Souza, Luis Gonzalez, Eduardo Cerqueira, Antonio Loureiro and Leandro Villas. Leveraging Federated Learning for Multilingual and Private Language Models via Model Clustering. FLTA Main Track. 2025.
(Metas 1 e 2) Bruno G. Silva, Eduardo Camargo, Alexandre Simões, Esther L. Colombini, Paula D. P. Costa, Ricardo R. Gudwin. Representing Episodes: Space-Time Experiences for Cognitive Architectures. 2025 Annual International Conference on Biologically Inspired Cognitive Architectures, the 16th Annual Meeting of the BICA Society (BICA 2025). 2025.
(Meta 3) Felipe Souza, Pedro Alves, Miliene Rodrigues, Filipe Maciel, Allan Souza, Leandro Villas e Luiz F. Bittencourt. Tackling the effect of local model updates heterogeneity on adaptive fit fraction. FLTA. 2025.
(Meta 1) Maria Gabriela Lustosa Oliveira, Paula Dornhofer Paro Costa. Evaluating Simulation Platforms for Visual Affordance Understanding in Computer Vision. Workshop of Undergraduate Works do SIBGRAPI. 2025.
(Meta 4) Otávio Oliveira Napoli, Edson Borin. On domain generalization for human activity recognition with mix-based methods. In: The 33th European Symposium on Artificial Neural Networks, Bélgica. 2025. [LINK] [qualis A3]
(Meta 3) Rafael Veiga and Renan Morais; Rómulo Bustincio; Lucas de Lima Bastos; Denis Lima Rosário; Susana Sargento; Eduardo Cerqueira. OPALA: Optimized Pruning Adaptive Learning Approach for Federated Learning Scenarios. The 30th IEEE Symposium on Computers and Communications (ISCC 2025). 2025.
(Meta 3) Rafael Veiga, Renan Morais, Augusto Neto, Lucas Bastos, Denis do Rosário, Eduardo Cerqueira. Federated Learning for User Identification Method from Biosignals in Wearable Devices. IEEE International Wireless Communications & Mobile Computing Conference (IWCMC 2025). 2025.
2024
Veiga, R. ; Morais, R.; Bastos, L; Villas, L. ; Rosario, D. ; Cerqueira, E.C. Resilience-aware Quarantine Selection Mechanism for Federated Learning Environments. In: IEEE 13th International Conference on Cloud Networking (CloudNet), 2024, Rio de Janeiro. 2024. [LINK]
Veiga, R. ; Morais, R. ; Seruffo, M ; Rosario, D. ; Cerqueira, E.C. RiCAM: An Efficient Multicriteria Client Selection Mechanism for Federated Learning. In: IEEE 13th International Conference on Cloud Networking (CloudNet), 2024, Rio de Janeiro. 2024. [LINK]
Sanchez, J. I. G.; Inofuente-Colque, K.; Marques, L. B. M. M.; Costa, P. D. P.; Tonoli, R. L. 2024. Benchmarking Speech-Driven Gesture Generation Models for Generalization to Unseen Voices and Noisy Environments. In Proceedings of the GENEA: Generation and Evaluation of Non-verbal Behaviour for Embodied Agents Workshop 2024. [LINK]
Filho WFS, Haddadi SJ, Reis MS, Reis JC. Maeve: An Agnostic Dataset Generator Framework for Predicting Customer Behavior in Digital Marketing. In KDIR 2024, Porto, Portugal. [LINK]
Panicachi DD, Cohen ED. Study of the ethical limits of the use of Artificial Intelligence for Marketing in the Brazilian context. LAAI Ethics 2024. Niterói, Brasil. 1ª Edição da Conferência Latino-Americana de Ética em Inteligência Artificial (LAAI-ethics 2024). [LINK]
Silva, J. V. S., Ferreira, A. I. S., Moreira, D. A. B., Santos, G. O., Bonil G., Gondim, J. M., Pereira, L. F. M., Maia, H. A., Silva, N. F. F., Hashiguti, S. T., Avila, S., Pedrini, H., Avaliação de Ferramentas de Ética no Levantamento de Considerações Éticas de Modelos de Linguagem em Português. 1ª Edição da Conferência Latino-Americana de Ética em Inteligência Artificial (LAAI-ethics) 2024. [LINK]
Moreira, D. A. B., Ferreira, A. I. S., Silva, J. V. S., Santos, G. O., Pereira, L. F. M., Gondim, J. M., Bonil, G., Maia, H. de A., Silva, N. F. F., Hashiguti, S. T., Santos, J. A., Pedrini, H., Avila S. FairPIVARA: Reducing and Assessing Biases in CLIP-Based Multimodal Models. 35th British Machine Vision Conference (BMVC 2024) Workshop Privacy, Fairness, Accountability and Transparency in Computer Vision (PFATCV), 2024. [LINK]
Araújo, P.; Haddadi; S.; Reis, Marcelo S.; dos Reis, J.C. Topic Modeling Influence in Sentiment Analysis from User-generated Product Reviews. 32nd International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE 2024). Reggio Emilia, Italy, 2024.
Santos, Fillipe; dos Reis, J.C.; Reis, Marcelo S. SERIEMA: A Framework to Enhance Clustering Stability, Compactness, and Separation by Fusing Multimodal Data. 29th International Conference on Natural Language & Information Systems (NLDB 2024), Turin, Italy, 2024. [LINK]
Carnot Braun, Joahannes B D da Costa, Leandro A Villas, Allan M de Souza. EcoPredict: Assessing Distributed Machine Learning Methods for Predicting Urban Emissions. IEEE 100th Vehicular Technology Conference (VTC-Fall), 2024.
Rafael O. Jarczewski, Eduardo Cerqueira, Luiz F. Bittencourt, Antonio A. F. Loureiro, Leandro A. Villas, Allan M. de Souza. Let’s Federate – Effective Communication Strategy for Dynamic Client Participation. IEEE International Conference on Machine Learning and Applications (ICMLA), 2024.
Wellington Lobato, Joahannes B D da Costa, Luis F G Gonzales, Eduardo Cerqueira, Denis Rosário, Christoph Sommer, Leandro A Villas. Entropy and Mobility-based Model Assignment for Multi-model Vehicular Federated Learning. IEEE International Symposium on Federated Learning Technologies and Applications (FLTA), 2024. [LINK]
Silva, F. S., Dos Reis, J. C., & Reis, M., SERIEMA: A Framework to Enhance Clustering Stability, Compactness, and Separation by Fusing Multimodal Data. International Conference on Natural Language & Information Systems (NLDB) 2024. [LINK]
Osorio, A., Grassiotto, F., Moraes, S., Munoz, A., Neto, S. F. & Gibaut, W. Transfer Learning for Human Activity Recognition in Federated Learning on Android Smartphones with Highly Imbalanced Datasets. In IEEE DistInSys 2024: The 4th IEEE International Workshop on Distributed Intelligent Systems. Paris, França. 2024. [LINK]
Rossi, L. L.; Rohmer, E.; Costa, P. D. P.; Gudwin, R. R., Da Silva Simões, A., Colombini, E. L. Drives And Impulses: Shaping Motivation And Procedural Learning For Humanoid Robots, ICDL, Austin, US, 2024. [LINK]
Berto, L. M., Tanevska, A. Costa, P. P Simoes, A. S, Gudwin, R., Colombini, E., Real, F., Sciutti, A. Curiosity and Affect-Driven Cognitive Architecture for HRI, ICDL,Austin, US, 2024. [LINK]
Berto, L. M.; Rossi, L. L.; Rohmer, E.; Costa, P. D. P.; Gudwin, R. R.; Simoes, A. S.; Colombini, E. L. Piagetian experiments to DevRobotics, Journal paper poster track, ICDL, Austin, US, 2024. [LINK]
Claudio Capanema, Joahannes B D da Costa, Fabricio A Silva, Leandro Villas, Antonio A Loureiro. A Modular Plugin for Concept Drift in Federated Learning. 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (IEEE DCOSS-IoT 2024). Abu Dhabi, UAE. 2024. [LINK]
Talasso, G., de Souza, A. M., Bittencourt, L., Cerqueira, E., Loureiro, A,, & Villas, L. FedSCCS: Hierarchical Clustering with Multiple Models for Federated Learning. IEEE International Conference on Communications (ICC) 2024. IEEE. [LINK]
Filipe Maciel, Joahannes B D, Luis F G Gonzalez, Allan M de Souza, Leandro A Villas, Luiz F Bittencourt. Adaptive Fit Fraction Based on Model Performance Evolution in Federated Learning. 11th International Conference on Future Internet of Things and Cloud (FiCloud). Viena, Áustria. 2024. [LINK]
Aissa H Mohamed, Joahannes B D da Costa, Allan M de Souza, Leandro A Villas, Julio C dos Reis. Combining Client Selection Strategy with Knowledge Distillation for Federated Learning in Non-IID Data. 29th IEEE Symposium on Computers and Communications (ISCC). Paris, França. 2024. [LINK]
Rafael O. Jarczewski, Eduardo Cerqueira, Luiz F. Bittencourt, Antonio A. F. Loureiro, Leandro A. Villas, Allan M. de Souza. Let’s Federate – Effective Communication Strategy for Dynamic Client Participation. IEEE International Conference on Machine Learning and Applications (ICMLA), 2024. [LINK]
Bruno S Martins, Leandro A Villas. Partial Training Mechanism to Handle the Impact of Stragglers in Federated Learning with Heterogeneous Clients. 29th IEEE Symposium on Computers and Communications (ISCC). Paris, França. 2024. [LINK]
Nicolas Assumpção, Leandro Villas. Fast, Private, and Protected: Safeguarding Data Privacy and Defending Against Model Poisoning Attacks in Federated Learning. 29th IEEE Symposium on Computers and Communications (ISCC). Paris, França. 2024. [LINK]
2023
Santos, G. O. D., Moreia, D. A., Ferreira, A. I., Silva, J., Pereira, L., Bueno, P., & Avila, S. (2023). CAPIVARA: Cost-Efficient Approach for Improving Multilingual CLIP Performance on Low-Resource Languages. Proceedings of the 3rd Workshop on Multi-lingual Representation Learning (MRL). [LINK]
Miranda Filho, D.; Veronese, T. B.; Raimundo, M. M. Measuring fairness of synthetic minority oversampling on credit datasets. NeurIPS 2023 Workshop Algorithmic Fairness through the Lens of Time (AFT 2023), 2023. [LINK]
Sakabe, E. Y., da Silva, A. A., Coletta, L. F., da Silva Simões, A., Colombini, E. L., Costa, P. D. P., & Gudwin, R. R. (2023, October). An Episode Tracker for Cognitive Architectures. In Biologically Inspired Cognitive Architectures Meeting (pp. 750-758). Cham: Springer Nature Switzerland. [LINK]
Mohamed, A. H., de Souza, A. M., Da Costa, J. B., Villas, L. A., & Dos Reis, J. C. (2023, December). CCSF: Clustered Client Selection Framework for Federated Learning in non-IID Data. In Proceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing. [LINK]
Condori Bustincio, R. W., de Souza, A. M., Da Costa, J. B., & Bittencourt, L. (2023, December). EntropicFL: Efficient Federated Learning via Data Entropy and Model Divergence. In Proceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing. [LINK]
Veiga, R., Flexa, R., Bastos, L., Medeiros, I., Rosário, D., Cerqueira, E., & Villas, L. (2023, October). A Federated Learning Approach for Continuous User Identification. In 2023 IEEE 9th World Forum on Internet of Things (WF-IoT). IEEE. [LINK]
Capanema, C. G., de Souza, A. M., Silva, F. A., Villas, L. A., & Loureiro, A. A. (2023, June). FedPredict: Combining Global and Local Parameters in the Prediction Step of Federated Learning. In 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE. [LINK]
Maciel, F., De Souza, A. M., Bittencourt, L. F., & Villas, L. A. (2023, June). Resource aware client selection for federated learning in IoT scenarios. In 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE. [LINK]
Mohamed, A. H., Assumpçáo, N. R., Astudillo, C. A., de Souza, A. M., Bittencourt, L. F., & Villas, L. A. (2023, January). Compressed client selection for efficient communication in federated learning. In 2023 IEEE 20th Consumer Communications & Networking Conference (CCNC). IEEE. [LINK]
2022
Grassiotto, F., Colombini, E. L., da Silva Simões, A., Gudwin, R. R., & Costa, P. D. P. (2022, January). CogToM-CST: An implementation of the Theory of Mind for the Cognitive Systems Toolkit. In ICAART (3). [LINK]
Marques, Á., Coletta, L., Silva, A., Paraense, A., Berto, L., Costa, P., & Gudwin, R. (2022). Visualization Tools for Monitoring and Debugging a Cognitive Architecture using CST. Procedia Computer Science. [LINK]
Lobato, W., Da Costa, J. B., de Souza, A. M., Rosário, D., Sommer, C., & Villas, L. A. (2022, September). Flexe: Investigating federated learning in connected autonomous vehicle simulations. In 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall). IEEE. [LINK]
2021
Berto, L. M., Costa, P. D., Simoes, A. S., Gudwin, R. R., & Colombini, E. L. (2021, August). An iowa gambling task-based experiment applied to robots: A study on long-term decision making. In 2021 IEEE International Conference on Development and Learning (ICDL). IEEE. [LINK]
