Short bio
Post-doctoral researcher in Business Analytics at the University of Padova. I earned my Ph.D. in Brain, Mind and Computer Science (process analytics track) at the same university.
Research interests
- Process mining
- Artificial intelligence
- Fairness
- Predictive & prescriptive analytics
- Event-log augmentation
- Resource allocation
- Explainability
Timeline
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Born in Tavernelle (Perugia)
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Bachelor’s degree in Mathematics @ UniPG
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Moved to Padova
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Master’s degree in Data Science @ UNIPD
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Ph.D. in Brain, Mind and Computer Science (process analytics) @ UNIPD
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Guest researcher at TU/e Eindhoven
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Post-doctoral researcher in process analytics @ UNIPD
Awards
Best BPM Dissertation Award — runner-up
2025 · International Conference on Business Process Management (BPM)
Publications
Selected work; the full list lives on DBLP.
Highlights below. For the complete bibliography see my dblp page or download my CV.
2026
2025
- Alessandro Padella: Process and Resource-Aware Responsible Recommender Systems (Extended Abstract). Best Dissertation Award / Doctoral Consortium & Demo at BPM 2025, CEUR Vol. 4032: 6–10
- Alessandro Padella, Paolo Frazzetto, Nicolò Navarin, Massimiliano de Leoni: Enhancing Predictive Process Monitoring on Small-Scale Event Logs Using LLMs. BPM Forum 2025: 274–290
- Ngoc-Diem Le, Alessandro Padella, Francesco Vinci, Massimiliano de Leoni: Leveraging Counterfactuals for Prescriptive Process Analytics. BPM 2025 RBPM Forum: 200–215
- Sjoerd van Straten, Alessandro Padella, Marwan Hassani: Leveraging Data Augmentation and Siamese Learning for Predictive Process Monitoring. CoopIS 2025: 70–87
- Alessandro Padella, Francesco Vinci, Massimiliano de Leoni: An Experimental Comparison of Alternative Techniques for Event-Log Augmentation. arXiv:2511.01896 (2025)
2024
- Alessandro Padella, Felix Mannhardt, Francesco Vinci, Massimiliano de Leoni, Irene Vanderfeesten: Experience-Based Resource Allocation for Remaining Time Optimization. BPM 2024: 345–362
- Massimiliano de Leoni, Alessandro Padella: Achieving Fairness in Predictive Process Analytics via Adversarial Learning. CoopIS 2024: 346–354
2023
2022
Teaching
Courses
- Teaching assistant — Database and Modeling, Bachelor in Computer Science, 2021–2025
- Professor — Fundamentals of Computer Science, Psychology Faculty, University of Padova, 2025–present
Thesis supervision
- Ongoing: Otto Wantland (Erasmus Mundus) — “Explainable OCEL Process Predictive Monitoring”
- 2025: Letizia Cimbro (MSc Data Science) — “Constrained Event-Log Augmentation”
- 2023: Jiani Wu (Data Science M.Sc.) — “Techniques for Discovering Event-Log Generative Models”
- 2023: Mohammed Ismail Tirmizi (Erasmus Mundus) — “Prescriptive Process Analytics using Counterfacts”
- 2022: Michele Gatto (Computer Science) — “Design and Development of a Graphical Interface for a Business Process Instance Recommendation System”
Curious about a thesis on processes, logs, or AI? Write me.