Massimiliano Ronzani — accepted AI-conference papers

2025

Generating Counterfactual Explanations Under Temporal Constraints

Andrei Buliga, Chiara Di Francescomarino, Chiara Ghidini, Marco Montali, Massimiliano Ronzani

AAAI 2025technical

Counterfactual explanations are one of the prominent eXplainable Artificial Intelligence (XAI) techniques, and suggest changes to input data that could alter predictions, leading to more favourable outcomes. Existing counterfactual methods do not readily apply to temporal domains, such as that of pr…

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2025

Proactive Data-driven Scheduling of Business Processes

Francesca Meneghello, Arik Senderovich, Massimiliano Ronzani, Chiara Di Francescomarino, Chiara Ghidini

IJCAI 2025

Proactive scheduling creates robust offline schedules that optimize resource utilization and minimize job flow times. This work addresses scheduling challenges in business processes, often encountered in service systems, which differ from traditional applications like manufacturing due to inherent u

Cited by 0 Source ↗PDF ↗Scholar ↗