Forward-Looking Process Mining - Automatic Construction of Simulation Environments from Process Data
| ABG-130334 | Thesis topic | |
| 2025-04-01 | Public funding alone (i.e. government, region, European, international organization research grant) |
- Computer science
- Engineering sciences
Topic description
This PhD seeks to revolutionize traditional methods of process mining and simulation model creation by developing a human-centered framework that extracts Discrete Event Simulation (DES) models directly from event logs. Current approaches are inefficient, heavily reliant on manual efforts, and lack evidence-based accuracy. This project aims to address key scientific challenges by integrating domain expertise with AI-driven algorithms to deliver accurate, automated, and FAIR (Findable, Accessible, Interoperable, Reusable) simulation models. The forward-looking perspective offered by this approach moves beyond analyzing historical data to combining predictive simulation for continuous process improvements.
Funding category
Funding further details
Presentation of host institution and host laboratory
Host Organization: Laboratoire Génie de Production (LGP) - ENIT, Université de Technologie de Tarbes (UTTOP), France Research Group: PICS (Planification, Interopérabilité, et Coordination pour les Systèmes Dynamiques) Supervisors: Dr. Sina Namaki Araghi (Lead Supervisor), Prof. Bernard Archimède (Co-Supervisor)
Candidate's profile
We are seeking a highly disciplined individual with the following qualifications:
Master's or Engineering degree in Computer Science, Applied Mathematics, or Industrial Engineering with a specialty in System Analysis.
