collaborators

7 papers

cs.AI2026

Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text

Anton Antonov, Humam Kourani, Alessandro Berti +1

Process modeling is a sub-domain of Business Process Management (BPM) focused on the translation of process artifacts into formal models. This task traditionally requires extensive…

cs.LG2026

Neuro-Symbolic Process Anomaly Detection

Devashish Gaikwad, Wil M. P. van der Aalst, Gyunam Park

Process anomaly detection is an important application of process mining for identifying deviations from the normal behavior of a process. Neural network-based methods have recently…

cs.AI2026

Compliance-Aware Predictive Process Monitoring: A Neuro-Symbolic Approach

Fabrizio De Santis, Gyunam Park, Wil M. P. van der Aalst +1

Existing approaches for predictive process monitoring are sub-symbolic, meaning that they learn correlations between descriptive features and a target feature fully based on data,…

cs.AI2026

Neuro-Symbolic Learning for Predictive Process Monitoring via Two-Stage Logic Tensor Networks with Rule Pruning

Fabrizio De Santis, Gyunam Park, Francesco Zanichelli

Predictive modeling on sequential event data is critical for fraud detection and healthcare monitoring. Existing data-driven approaches learn correlations from historical data but…

cs.AI2026

PMAx: An Agentic Framework for AI-Driven Process Mining

Anton Antonov, Humam Kourani, Alessandro Berti +2

Process mining provides powerful insights into organizational workflows, but extracting these insights typically requires expertise in specialized query languages and data science…

cs.SE2025

Online Discovery of Simulation Models for Evolving Business Processes (Extended Version)

Francesco Vinci, Gyunam Park, Wil van der Aalst +1

Business Process Simulation (BPS) refers to techniques designed to replicate the dynamic behavior of a business process. Many approaches have been proposed to automatically discove…