AI Research

The AI group has a mission of building the next-gen RiskOps AI to safeguard businesses and people from fraud and financial crime that is responsible and explainable by design. The group aims to reimagine financial services, risk management and financial crime prevention through the lens of state-of-the-art Human-Centered AI and propose product solutions to significant problems, such as identity, detection, and automation, while mitigating bias and promoting transparency.

Research Focus:

  • AI in Financial Services
  • AutoML
  • AI safety, fairness, privacy, robustness
  • ML Monitoring, Explainability and Observability
  • Deep Learning & Network Science

Recent Publications

DiConStruct: Causal Concept-based Explanations through Black-Box Distillation

Ricardo Moreira, Jacopo Bono, Mário Cardoso, Pedro Saleiro, Mário A. T. Figueiredo, Pedro Bizarro

Published at CLeaR 2024 - Conference on Causal Learning and Reasoning

arXiv

On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods

Kasun Amarasinghe, Kit T. Rodolfa, Sérgio Jesus, Valerie Chen, Vladimir Balayan, Pedro Saleiro, Pedro Bizarro, Ameet Talwalkar, Rayid Ghani

Published at AAAI-24 - Annual AAAI Conference on Artificial Intelligence

arXiv

FiFAR: a fraud detection dataset for learning to defer

Jean V. Alves, Diogo Leitão, Sérgio Jesus, Marco O. P. Sampaio, Pedro Saleiro, Mário A. T. Figueiredo, Pedro Bizarro

Published at ICAIF23 - Synthetic Data for AI in Finance workshop

arXiv | Github

Adversarial training for tabular data with attack propagation

Tiago Leon Melo, João Bravo, Marco O. P. Sampaio, Paolo Romano, Hugo Ferreira, João Tiago Ascensão, Pedro Bizarro

Published at KDD Workshop on Machine Learning in Finance 2023

arXiv | Youtube

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