JWarp: A Java Library for Parallel Discrete-Event Simulations. - Pedro Bizarro; Luís Moura Silva; João Gabriel Silva (Concurr. Pract. Exp., 1998)

The Dimension-Join: A New Index for Data Warehouses. - Pedro Bizarro; Henrique Madeira (SBBD, 2001)

Adding a Performance-Oriented Perspective to Data Warehouse Design. - Pedro Bizarro; Henrique Madeira (DaWaK, 2002)

Adaptive Query Processing in the Looking Glass. - Shivnath Babu; Pedro Bizarro (CIDR, 2005)

Proactive Re-optimization. - Shivnath Babu; Pedro Bizarro; David J. DeWitt (SIGMOD Conference, 2005)

Proactive re-optimization with Rio. - Shivnath Babu; Pedro Bizarro; David J. DeWitt (SIGMOD Conference, 2005)

Content-Based Routing: Different Plans for Different Data. - Pedro Bizarro; Shivnath Babu; David J. DeWitt; Jennifer Widom (VLDB, 2005)

BiCEP - Benchmarking Complex Event Processing Systems. - Pedro Bizarro (Event Processing, 2007)

A framework for performance evaluation of complex event processing systems. - Marcelo R. N. Mendes; Pedro Bizarro; Paulo Marques (DEBS, 2008)

A Training Process for Faculty Members in Collaborative Degree Programs: Design, Implementation and Feedback. - Gil Taran; Mário Zenha Rela; Paulo Marques; Pedro Bizarro (CSEE&T, 2009)

An integrated data management approach to manage health care data. - Diogo Guerra; Ute Gawlick; Pedro Bizarro (DEBS, 2009)

A Performance Study of Event Processing Systems. - Marcelo R. N. Mendes; Pedro Bizarro; Paulo Marques (TPCTC, 2009)

Progressive Parametric Query Optimization. - Pedro Bizarro; Nicolas Bruno; David J. DeWitt (IEEE Trans. Knowl. Data Eng., 2009)

Flood: elastic streaming MapReduce. - David Alves; Pedro Bizarro; Paulo Marques (DEBS, 2010)

Events, Neural Systems and Time Series. - Leslie S. Smith; Daniel Metz; Jungpen Bao; Pedro Bizarro (ServiceWave Workshops, 2010)

Assessing and Optimizing Microarchitectural Performance of Event Processing Systems. - Marcelo R. N. Mendes; Pedro Bizarro; Paulo Marques (TPCTC, 2010)

Benchmarking event processing systems: current state and future directions. - Marcelo R. N. Mendes; Pedro Bizarro; Paulo Marques (WOSP/SIPEW, 2010)

Deadline Queries: Leveraging the Cloud to Produce On-Time Results. - David Alves; Pedro Bizarro; Paulo Marques (IEEE CLOUD, 2011)

An Integrated Data Management Approach to Manage Health Care Data. - Diogo Guerra; Ute Gawlick; Pedro Bizarro; Dieter Gawlick (BTW, 2011)

Event processing grand challenges. - Pedro Bizarro; K. Mani Chandy; Nenad Stojanovic (DEBS, 2011)

Towards a standard event processing benchmark. - Marcelo R. N. Mendes; Pedro Bizarro; Paulo Marques (ICPE, 2013)

Overcoming memory limitations in high-throughput event-based applications. - Marcelo R. N. Mendes; Pedro Bizarro; Paulo Marques (ICPE, 2013)

FINCoS: benchmark tools for event processing systems. - Marcelo R. N. Mendes; Pedro Bizarro; Paulo Marques (ICPE, 2013)

Scalable Proactive Event-Driven Decision Making. - Alexander Artikis; Chris Baber; Pedro Bizarro; Carlos Canudas-de-Wit; Opher Etzion; Fabiana Fournier; Paul Goulart; Andrew Howes 001; John Lygeros; Georgios Paliouras; Assaf Schuster; Izchak Sharfman (IEEE Technol. Soc. Mag., 2014)

BreachRadar: Automatic Detection of Points-of-Compromise. - Miguel Araujo; Miguel Almeida; Jaime Ferreira; Luís Moura Silva; Pedro Bizarro (SDM, 2017)

Automatic Model Monitoring for Data Streams. - Fábio Pinto; Marco O. P. Sampaio; Pedro Bizarro (CoRR, 2019)

Machine learning methods to detect money laundering in the bitcoin blockchain in the presence of label scarcity. - Joana Lorenz; Maria Inês Silva; David Aparício; João Tiago Ascensão; Pedro Bizarro (ICAIF, 2020)

Interleaved Sequence RNNs for Fraud Detection. - Bernardo Branco; Pedro Abreu; Ana Sofia Gomes; Mariana S. C. Almeida; João Tiago Ascensão; Pedro Bizarro (KDD, 2020)

ARMS: Automated rules management system for fraud detection. - David Aparício; Ricardo Barata; João Bravo; João Tiago Ascensão; Pedro Bizarro (CoRR, 2020)

Railgun: streaming windows for mission critical systems. - João Oliveirinha; Ana Sofia Gomes; Pedro Cardoso; Pedro Bizarro (CoRR, 2020)

A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization. - André Ferreira Cruz; Pedro Saleiro; Catarina G. Belém; Carlos Soares; Pedro Bizarro (CoRR, 2020)

Teaching the Machine to Explain Itself using Domain Knowledge. - Vladimir Balayan; Pedro Saleiro; Catarina G. Belém; Ludwig Krippahl; Pedro Bizarro (CoRR, 2020)

How can I choose an explainer?: An Application-grounded Evaluation of Post-hoc Explanations. - Sérgio M. Jesus; Catarina G. Belém; Vladimir Balayan; João Bento 002; Pedro Saleiro; Pedro Bizarro; João Gama 001 (FAccT, 2021)

Active learning for imbalanced data under cold start. - Ricardo Barata; Miguel Leite; Ricardo Pacheco; Marco O. P. Sampaio; João Tiago Ascensão; Pedro Bizarro (ICAIF, 2021)

Promoting Fairness through Hyperparameter Optimization. - André Ferreira Cruz; Pedro Saleiro; Catarina G. Belém; Carlos Soares; Pedro Bizarro (ICDM, 2021)

TimeSHAP: Explaining Recurrent Models through Sequence Perturbations. - João Bento 002; Pedro Saleiro; André Ferreira Cruz; Mário A. T. Figueiredo; Pedro Bizarro (KDD, 2021)

Finding NeMo: Fishing in Banking Networks Using Network Motifs. - Xavier Fontes; David Aparício; Maria Inês Silva; Beatriz Malveiro; João Tiago Ascensão; Pedro Bizarro (SEA-Data@VLDB, 2021)

GuiltyWalker: Distance to illicit nodes in the Bitcoin network. - Catarina Oliveira; João Torres; Maria Inês Silva; David Aparício; João Tiago Ascensão; Pedro Bizarro (CoRR, 2021)

Weakly Supervised Multi-task Learning for Concept-based Explainability. - Catarina G. Belém; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro (CoRR, 2021)

Active learning for online training in imbalanced data streams under cold start. - Ricardo Barata; Miguel Leite; Ricardo Pacheco; Marco O. P. Sampaio; João Tiago Ascensão; Pedro Bizarro (CoRR, 2021)

GUDIE: a flexible, user-defined method to extract subgraphs of interest from large graphs. - Maria Inês Silva; David Aparício; Beatriz Malveiro; João Tiago Ascensão; Pedro Bizarro (CoRR, 2021)

Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs. - Ahmad Naser Eddin; Jacopo Bono; David Aparício; David Polido; João Tiago Ascensão; Pedro Bizarro; Pedro Ribeiro 004 (CoRR, 2021)

Railgun: managing large streaming windows under MAD requirements. - Ana Sofia Gomes; João Oliveirinha; Pedro Cardoso; Pedro Bizarro (Proc. VLDB Endow., 2021)

LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering. - Mário Cardoso; Pedro Saleiro; Pedro Bizarro (ICAIF, 2022)

Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation. - Sérgio M. Jesus; José Pombal; Duarte M. Alves; André Ferreira Cruz; Pedro Saleiro; Rita P. Ribeiro; João Gama 001; Pedro Bizarro (NeurIPS, 2022)

A Case Study on Implementing Screen Reader Accessibility in Dynamic Visualizations. - Rita Costa; Beatriz Malveiro; João Palmeiro; Pedro Bizarro (EuroVis (Posters), 2022)

Data+Shift: Supporting Visual Investigation of Data Distribution Shifts by Data Scientists. - João Palmeiro; Beatriz Malveiro; Rita Costa; David Polido; Ricardo Moreira; Pedro Bizarro (EuroVis (Short Papers), 2022)

ConceptDistil: Model-Agnostic Distillation of Concept Explanations. - João Bento Sousa; Ricardo Moreira; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro (CoRR, 2022)

Prisoners of Their Own Devices: How Models Induce Data Bias in Performative Prediction. - José Pombal; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2022)

Human-AI Collaboration in Decision-Making: Beyond Learning to Defer. - Diogo Leitão; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2022)

Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions. - José Pombal; André Ferreira Cruz; João Bravo; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2022)

Lightweight Automated Feature Monitoring for Data Streams. - João Conde; Ricardo Moreira; João Torres; Pedro Cardoso; Hugo R. C. Ferreira; Marco O. P. Sampaio; João Tiago Ascensão; Pedro Bizarro (CoRR, 2022)

From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs. - Jacopo Bono; Ahmad Naser Eddin; David Aparício; Hugo Ferreira 006; João Tiago Ascensão; Pedro Ribeiro 004; Pedro Bizarro (ICAIF, 2023)

The GANfather: Controllable generation of malicious activity to improve defence systems. - Ricardo Ribeiro Pereira; Jacopo Bono; João Tiago Ascensão; David Aparício; Pedro Ribeiro 004; Pedro Bizarro (ICAIF, 2023)

FairGBM: Gradient Boosting with Fairness Constraints. - André Ferreira Cruz; Catarina G. Belém; João Bravo; Pedro Saleiro; Pedro Bizarro (ICLR, 2023)

Fairness-Aware Data Valuation for Supervised Learning. - José Pombal; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2023)

Adversarial training for tabular data with attack propagation. - Tiago Leon Melo; João Bravo; Marco O. P. Sampaio; Paolo Romano 002; Hugo Ferreira 006; João Tiago Ascensão; Pedro Bizarro (CoRR, 2023)

FiFAR: A Fraud Detection Dataset for Learning to Defer. - Jean V. Alves; Diogo Leitão; Sérgio M. Jesus; Marco O. P. Sampaio; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CoRR, 2023)

On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods. - Kasun Amarasinghe; Kit T. Rodolfa; Sérgio M. Jesus; Valerie Chen; Vladimir Balayan; Pedro Saleiro; Pedro Bizarro; Ameet Talwalkar; Rayid Ghani (AAAI, 2024)

DiConStruct: Causal Concept-based Explanations through Black-Box Distillation. - Ricardo Miguel de Oliveira Moreira; Jacopo Bono; Mário Cardoso; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (CLeaR, 2024)

Fair-OBNC: Correcting Label Noise for Fairer Datasets. - Inês Oliveira e Silva; Sérgio M. Jesus; Hugo M. Ferreira; Pedro Saleiro; Inês Sousa; Pedro Bizarro; Carlos Soares (ECAI, 2024)

Lessons Learned while Running ML Models in Harsh Environments. - Pedro Bizarro (KDD, 2024)

RIFF: Inducing Rules for Fraud Detection from Decision Trees. - Lucas Martins; João Bravo; Ana Sofia Gomes; Carlos Soares; Pedro Bizarro (RuleML+RR, 2024)

AutoVizuA11y: A Tool to Automate Screen Reader Accessibility in Charts. - Diogo Duarte; Rita Costa; Pedro Bizarro; Carlos Duarte (Comput. Graph. Forum, 2024)

Aequitas Flow: Streamlining Fair ML Experimentation. - Sérgio M. Jesus; Pedro Saleiro; Inês Oliveira e Silva; Beatriz M. Jorge; Rita P. Ribeiro; João Gama 001; Pedro Bizarro; Rayid Ghani (CoRR, 2024)

RIFF: Inducing Rules for Fraud Detection from Decision Trees. - João Lucas Martins; João Bravo; Ana Sofia Gomes; Carlos Soares; Pedro Bizarro (CoRR, 2024)

"Show Me What's Wrong!": Combining Charts and Text to Guide Data Analysis. - Beatriz Feliciano; Rita Costa; Jean V. Alves; Javier Liébana; Diogo Duarte; Pedro Bizarro (CoRR, 2024)

Mind the truncation gap: challenges of learning on dynamic graphs with recurrent architectures. - João Bravo; Jacopo Bono; Pedro Saleiro; Hugo M. Ferreira; Pedro Bizarro (CoRR, 2024)

Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints. - Jean V. Alves; Diogo Leitão; Sérgio M. Jesus; Marco O. P. Sampaio; Javier Liébana; Pedro Saleiro; Mário A. T. Figueiredo; Pedro Bizarro (Trans. Mach. Learn. Res., 2024)

Mind the truncation gap: challenges of learning on dynamic graphs with recurrent architectures. - João Bravo; Jacopo Bono; Hugo Ferreira 006; Pedro Saleiro; Pedro Bizarro (Trans. Mach. Learn. Res., 2024)

Deep-Graph-Sprints: Accelerated Representation Learning in Continuous-Time Dynamic Graphs. - Ahmad Naser Eddin; Jacopo Bono; David Oliveira Aparício; Hugo Ferreira 006; Pedro Manuel Pinto Ribeiro; Pedro Bizarro (Trans. Mach. Learn. Res., 2024)

High Probability Risk Control Under Covariate Shift. - Duarte C. Almeida; João Bravo; Jacopo Bono; Pedro Bizarro; Mário A. T. Figueiredo (COPA, 2025)