Projects

In research, the work he has done so far is multidisciplinary and concerns the theme of the "engineering of complex systems". The theses he has supervised or is currently supervising deal with approaches that mainly concern the engineering of complex systems and fall within the specialty of industrial engineering at the Pays de la Loire (France) doctoral school of Engineering and Systems Sciences (ED SIS).

• The ANR DIA-SOLAIRE project, which he currently coordinates as scientific director, aims to develop artificial intelligence-based tools to extend the life of operational photovoltaic power plants, using hybrid approaches based on physical models and qualitative and quantitative field data. This project enables a consortium of academic laboratories (working in engineering sciences or humanities and social sciences) to develop appropriate tools to support the solar industry in France and mitigate the uncertainties and loss of energy performance in the face of various environmental, technological, economic, organizational, and human risks.
• Developing methods for system modeling, multi-perspective behavioral simulation, and verification and evaluation of non-functional properties (e.g., safety, reliability, security, and resilience) while taking into account the risks and their effects offers promising prospects that are closely related to what he has been able to do so far.
• The ANR DIA-SOLAIRE project (funded by the French National Research Agency) that he is currently leading includes several work packages, one of which specifically concerns the collection, analysis, fusion, and processing of data, and another which consists of developing deep learning techniques with augmented data.
• Focusing on data and knowledge management and quality is essential for evaluating, diagnosing, and predicting the functioning of a complex system or organization using AI. In line with what he is currently doing, he would like to conduct research on this issue and set up several research projects.
• Evaluating the performance of a complex system for smart advanced manufacturing and industrial engineering is an area of research to which he can contribute. Taking into account data related to the traceability of requirements (from design to production) and the principle of "quality assurance" is also part of what he is developing in the subjects he currently teaches.
• Integrating AI tools to try to improve the evaluation of multi-scale and multi-criteria prediction of the behavior of a complex system, taking into account hazards and uncertainties, is a promising area of research.
• Access to data, information, and knowledge generated throughout a project, from the design to the operation of a complex system (or organization), is often difficult. Depending on the context and subject studied, this lack of accessibility leads to complexity and disparities in terms of volume, variety, variability, and data reliability. He is tackling this difficulty in the ANR DIA-SOLAIRE project that he is currently coordinating.
• Model-based systems and software engineering have vulnerabilities that can compromise their operation and integrity. The operational safety of systems and software, confidentiality, and data integrity are also essential topics to be developed. A multidisciplinary engineering approach using digital twins is also an interesting research prospect. The recent development of Digital Twins offers many opportunities in complex systems engineering.