IA & Data for Industrial Engineering

Management

The Chair is led by the “Data Science for Complex Systems” team at the Co-Innovation Lab and the School’s Department of Industrial Engineering, in close collaboration with Scalian’s teams.

Governance: steering committee composed of Nicolas Viala, COO of Scalian France; Jean-Pierre Dupé, Managing Director of Scalian Consulting; Emmanuel Girard, Associate Director of Research at the School; and Fabien Liéval, Director of the Co-Innovation Lab.

Scientific Director: Mohamed Saâd El Harrab, Associate Professor at the School. 

Objective

The Chair aims to develop innovative operational solutions to address complex industrial challenges, particularly in the areas of systems modeling, process optimization, automation, uncertainty management, and consideration of the human factor, within the context of environmental and energy transitions, drawing on data science, algorithms, and artificial intelligence systems.

The program is structured around academic and applied research activities, including the supervision of engineering internships, doctoral theses, and postdoctoral work. The work will result in concrete outcomes, such as prototypes, demonstrators, or decision-support tools. The program promotes knowledge transfer and the development of innovative solutions that can be directly applied in industrial contexts.