Massimiliano de Leoni

Professor in the Department of Mathematics at Università degli Studi di Padova, Italy. Active in the process-mining and predictive-process-monitoring research community since the late 2000s; collaborator with entities/wil-van-der-aalst (former post-doc at TU/e), entities/marlon-dumas, and the next-generation Padova group including entities/alessandro-padella.

Affiliation

Università degli Studi di Padova — Department of Mathematics. Contact: deleoni@math.unipd.it.

Work in this wiki

sources/2026-padella-llm-features-ppm — Exploring LLM Features in Predictive Process Monitoring for Small-Scale Event-Logs (with Padella & Dumas, arXiv 2601.11468). Second author / supervisor of the Padova LLM-PPM line.

Research themes

Process mining (conformance, performance, data-aware variants).
Predictive process monitoring — long-standing contributor, often via interpretable / data-aware methods.
LLM-based PPM in data-scarce settings (current line).
Fairness in predictive process analytics — cited as a referenced collaborator with Padella in earlier work (Berti et al. 2025 [3] in the 2026 paper).

Network

Co-authors with entities/marlon-dumas across the 2026 PPM line.
Cited as a discussant / collaborator on process modeling with LLMs (Berti, de Leoni, Kourani, van der Aalst 2025 — ref [3] of sources/2026-padella-llm-features-ppm).
Cited on reinforcement-learning-driven LLM process model specialisation (Berti, Wang, Kourani, van der Aalst 2025 — ref [3] of the same paper). (Disambiguation: two separate Berti papers in 2025.)

entities/marlon-dumas · entities/alessandro-padella · entities/wil-van-der-aalst · concepts/llm-based-ppm · concepts/predictive-process-monitoring