Ph. D. Project
The Human Digital Twin in the Cyber Physical Enterprise
2023/05/25 - 2026/05/24
Other supervisor(s):
NAUDET Yannick (
The Luxembourg Institute of Science and Technology (LIST) ( is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.
You 'd like to contribute as PhD student? Join our IT for Innovation Services department
The IT for Innovative Services (ITIS) department, with its 100 researchers and engineers, focuses on the digital transformation of operations in organizations with traditional environments and digital ecosystems, with the aim of improving their performance and innovation capacity. The common thread throughout ITIS is to develop the most efficient use of big data to ensure the most appropriate decision-making processes. The department relies on the Data Analytics Platform: a hybrid infrastructure covering the entire range of data analytics activities. The platform is based on three pillars: a high-performance computing (HPC) infrastructure, a cognitive analytics pillar and an interactive visualization wall (Viswall).
This PhD project is part of a bilateral research project between ITIS, the Research Center for Automatic Control (CRAN --University of Lorraine, CNRS) and the ORISUN enterprise, in France, dealing with applications of artificial intelligence for cognitive interoperability in cyber-physical enterprises: AI4C2PS. The candidate will be registered at the University of Lorraine (doctoral school IAEM Lorraine) as a PhD student and will be integrated in the HUMOD research group of ITIS and the ISET research department of CRAN. The main workplace will be in LIST offices in Esch/Alzette, Luxembourg, while some time will be spent in Nancy, France, in CRAN offices.

How will you contribute?
The introduction of Cyber-Physical Systems (CPS), together with advances in Information and Communication Technologies (ICT), has been the major driving force for the 4th industrial revolution. The 5th revolution calls now for a better integration of human and social / societal factors, transforming progressively CPS into Cyber-Physical-Social Systems (CPSS). A Cyber-Physical Enterprise (CPE) consists of autonomous and cooperative technical elements, humans and sub-organisations that are connected based on the context within and across all levels of the global organisation, from processes, through machines and up to enterprises and supply-chains networks. Today ontology-based solutions ensure that technological components (CPS) of a CPE share a common vocabulary and can reason on exchanged knowledge. However, this is not enough to build CPSS components, ensuring CPS and human agents understand each other enough to collaborate efficiently. The next generation of CPE must reach a satisfactory level of flexibility and efficiency that better integrates humans and give human-machine teams complete autonomy for some tasks including ad-hoc reconfigurations and non-predefined problem-solving.
In this context, you will address the research challenge of building a Human Digital Twin (HDT) based on ontological, neural and stochastic models, that is realistic enough to serve as a computational model for CPS adaptation to humans. The PhD objective is to build a theoretical framework for the HDT in industry and implement it as an intelligent software agent that can support human workers to collaborate with CPSS of an enterprise. Synchronous and asynchronous contexts will be both considered, where in the first the digital twin takes part of simulations for prediction objectives and in the latter the digital twin reflects the human state and behaviour. The work will focus on:
1- The cognitive aspects of human modelling and human-CPSS collaboration, exploring the theory of cognitive architectures.
2- Exploring HDT models combining Knowledge Reasoning and Representation with Artificial Neural Network -based Machine Learning, able to explain their state and behaviours (i.e., implementing explainable artificial intelligence).
• Participation to the AI4C2PS project as a full member, integrating the models, algorithms, and prototypes in collaboration with the project's team of researchers, participating to project's meeting and contributing to deliverables
• Presentation of papers at academic conferences
• Writing of research papers and publication of peer-reviewed journal articles
• Write a PhD thesis in the field of computer engineering
• Participation to outreach activities of LIST and CRAN
Human Digital Twin, Cyber-phisical Systems, Congnitive sciences
Modeling and Control of Industrial Systems