The literature addressing bias and fairness in AI models (fair-AI) is growing at a fast pace,
making it difficult for novel researchers and practitioners to have a bird's-eye view picture of …

In this paper, we investigate the practical relevance of explainable artificial intelligence (XAI)
with a special focus on the producing industries and relate them to the current state of …

Monitoring machine learning systems and efficiently recovering their reliability after
performance degradation are two of the most critical issues in real-world applications …

Liberalism-oriented political philosophy reasons that all individuals should be treated
equally independently of their protected characteristics. Related work in machine learning …

This paper presents a novel application of explainable AI (XAI) for root-causing performance
degradation in machine learning models that learn continuously from user engagement …

I am a Principal Investigator and an Applied Skills Support Advisor at the Alan Turing
Institute. I am passionate about predictive modelling and its impact on society. I have worked …