State-of-the-Art Innovations
to Prevent Financial Risk

The Feedzai Research department invests in applied research to improve our products and help users have a better experience. We work closely with Product and Customer Success to develop and transfer innovations. We focus on long-term, disruptive, state-of-the-art research, produce and protect our IP, publish peer reviewed work, contribute to open-source, partner with external researchers, and sponsor scholarships.

Recent Publications

Aequitas Flow: Streamlining Fair ML Experimentation

Sérgio Jesus, Pedro Saleiro, Inês Oliveira e Silva, Beatriz M. Jorge, Rita P. Ribeiro, João Gama, Pedro Bizarro, Rayid Ghani

Published at Journal of Machine Learning Research

arXiv

Fair-OBNC: Correcting Label Noise for Fairer Datasets

Inês Oliveira e Silva, Sérgio Jesus, Hugo Ferreira, Pedro Saleiro, Inês Sousa, Pedro Bizarro, Carlos Soares

Published at ECAI 2024

arXiv | YouTube

RIFF: Inducing Rules for Fraud Detection from Decision Trees

João Lucas Martins, João Bravo, Ana Sofia Gomes, Carlos Soares, Pedro Bizarro

Published at RuleML+RR 2024

arXiv | YouTube

Show Me What’s Wrong!: Combining Charts and Text to Guide Data Analysis

Beatriz Feliciano, Rita Costa, Jean Alves, Javier Liebana, Diogo Duarte, Pedro Bizarro

Published at NLVIZ, a workshop at IEEE VIS 2024

PDF | arXiv | YouTube

Aequitas Flow: Streamlining Fair ML Experimentation

Sérgio Jesus, Pedro Saleiro, Inês Oliveira e Silva, Beatriz M. Jorge, Rita P. Ribeiro, João Gama, Pedro Bizarro, Rayid Ghani

Published at Journal of Machine Learning Research

arXiv

Fair-OBNC: Correcting Label Noise for Fairer Datasets

Inês Oliveira e Silva, Sérgio Jesus, Hugo Ferreira, Pedro Saleiro, Inês Sousa, Pedro Bizarro, Carlos Soares

Published at ECAI 2024

arXiv | YouTube

RIFF: Inducing Rules for Fraud Detection from Decision Trees

João Lucas Martins, João Bravo, Ana Sofia Gomes, Carlos Soares, Pedro Bizarro

Published at RuleML+RR 2024

arXiv | YouTube

Show Me What’s Wrong!: Combining Charts and Text to Guide Data Analysis

Beatriz Feliciano, Rita Costa, Jean Alves, Javier Liebana, Diogo Duarte, Pedro Bizarro

Published at NLVIZ, a workshop at IEEE VIS 2024

PDF | arXiv | YouTube

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