| 2025 | AIES | Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation. | Maria Eriksson, Erasmo Purificato, Arman Noroozian, Joo Vinagre, Guillaume Chaslot, Emilia Gmez, David Fernndez Llorca |
| 2025 | ICTAI | Fed-VFDT: Federated Very Fast Decision Trees with Coordinated Splitting Over Data Streams. | Paula Raissa Silva, Joo Vinagre, Joo Gama |
| 2025 | RecSys | Data Access for Recommender Systems Research: leveraging the EU's Digital Services Act. | Joo Vinagre, Lorenzo Porcaro, Silvia Merisio, Erasmo Purificato, Emilia Gmez |
| 2024 | ECAI | Federated Online Learning for Heavy Hitter Detection. | Paula Raissa Silva, Joo Vinagre, Joo Gama |
| 2024 | NDSS | Flow Correlation Attacks on Tor Onion Service Sessions with Sliding Subset Sum. | Daniela Lopes, Jin-Dong Dong, Pedro Medeiros, Daniel Castro, Diogo Barradas, Bernardo Portela, Joo Vinagre, Bernardo Ferreira, Nicolas Christin, Nuno Santos |
| 2023 | EPIA | Mining Causal Links Between TV Sports Content and Real-World Data. | Duarte Melo, Jessica C. Delmoral, Joo Vinagre |
| 2023 | EPIA | Hybrid SkipAwareRec: A Streaming Music Recommendation System. | Rui Ramos, Lino Oliveira, Joo Vinagre |
| 2023 | EPIA | Measuring Latency-Accuracy Trade-Offs in Convolutional Neural Networks. | Andr Tse, Lino Oliveira, Joo Vinagre |
| 2023 | RecSys | ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling. | Joo Vinagre, Marie Al-Ghossein, Ladislav Peska, Alpio Mrio Jorge, Albert Bifet |
| 2023 | SAC | A DTW Approach for Complex Data A Case Study with Network Data Streams. | Paula Raissa Silva, Joo Vinagre, Joo Gama |
| 2022 | CCS | Poster: User Sessions on Tor Onion Services: Can Colluding ISPs Deanonymize Them at Scale? | Daniela Lopes, Pedro Medeiros, Jin-Dong Dong, Diogo Barradas, Bernardo Portela, Joo Vinagre, Bernardo Ferreira, Nicolas Christin, Nuno Santos |
| 2022 | RecSys | ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling. | Joo Vinagre, Marie Al-Ghossein, Alpio Mrio Jorge, Albert Bifet, Ladislav Peska |
| 2021 | IDA | Partially Monotonic Learning for Neural Networks. | Joana Trindade, Joo Vinagre, Kelwin Fernandes, Nuno Paiva, Alpio Jorge |
| 2021 | RecSys | ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling. | Joo Vinagre, Alpio Mrio Jorge, Marie Al-Ghossein, Albert Bifet |
| 2020 | RecSys | ORSUM - Workshop on Online Recommender Systems and User Modeling. | Joo Vinagre, Alpio Mrio Jorge, Marie Al-Ghossein, Albert Bifet |
| 2019 | RecSys | Incremental Multi-Dimensional Recommender Systems: Co-Factorization vs Tensors. | Miguel Sozinho Ramalho, Joo Vinagre, Alpio Mrio Jorge, Rafaela Bastos |
| 2019 | RecSys | ORSUM 2019 2nd workshop on online recommender systems and user modeling. | Joo Vinagre, Alpio Mrio Jorge, Albert Bifet, Marie Al-Ghossein |
| 2018 | DIS | Online Gradient Boosting for Incremental Recommender Systems. | Joo Vinagre, Alpio Mrio Jorge, Joo Gama |
| 2018 | WWW | Incremental Matrix Co-factorization for Recommender Systems with Implicit Feedback. | Susan C. Anyosa, Joo Vinagre, Alpio M. Jorge |
| 2018 | WWW | ORSUM Chairs' Welcome & Organization. | Alpio Jorge, Joo Vinagre, Pawel Matuszyk, Myra Spiliopoulou |
| 2017 | EPIA | Improving Incremental Recommenders with Online Bagging. | Joo Vinagre, Alpio Mrio Jorge, Joo Gama |
| 2015 | SAC | Forgetting methods for incremental matrix factorization in recommender systems. | Pawel Matuszyk, Joo Vinagre, Myra Spiliopoulou, Alpio Mrio Jorge, Joo Gama |
| 2015 | SAC | Collaborative filtering with recency-based negative feedback. | Joo Vinagre, Alpio Mrio Jorge, Joo Gama |
| 2014 | ICCSA | Monitoring Recommender Systems: A Business Intelligence Approach. | Catarina Flix, Carlos Soares, Alpio Jorge, Joo Vinagre |
| 2012 | WWW | Combining usage and content in an online music recommendation system for music in the long-tail. | Marcos Aurlio Domingues, Fabien Gouyon, Alpio Mrio Jorge, Jos Paulo Leal, Joo Vinagre, Lus Lemos, Mohamed Sordo |