Henri Arno

Henri Arno

PhD candidate @ Ghent University
FWO Fellow

Research Projects

My current research focuses on causal machine learning for data-driven decision support. In particular, I study how observational data can be used not only to predict outcomes, but also to estimate causal effects and learn effective decision policies. For a complete and up-to-date publication list, see my Google Scholar.

Causal Machine Learning for Data-Driven Decision Support

This research direction focuses on using causal machine learning for downstream decision-making from observational data. Rather than only predicting what is likely to happen, causal methods aim to model how outcomes would change under different actions and which actions are most effective for whom. Within this broader area, I study treatment effect estimation, ranking, and policy learning, with a particular interest in adapting these methods to realistic data settings. This includes learning directly for downstream objectives such as prioritization, working with complex multimodal data, and accounting for limitations in the available data.

Selected outputs

Business Failure Prediction and Judicial Decision Support

This research project focused on the development of machine learning systems for the early detection of financially distressed firms in collaboration with Belgian commercial courts. The work combined financial and textual corporate disclosures and examined how AI could support real-world judicial decision-making. My research addressed predictive performance, interpretability, and the added value of textual information, while the broader interdisciplinary project also considered the integration of AI-based decision support into the workflow of the commercial courts.

Selected outputs