Doctoral student, Polytech Annecy-Chambéry.
Contact
E-mail: fatema.el-husseini@ univ-smb.fr
Telephone: +33 759368753
Mobile:+33 759368753,+961 3 065260
Office: A103
Address: LISTIC, 5 chemin de bellevue, CS80439, 74 944 Annecy Cedex, France
Thesis
Theme: ReGard
Subject:Efficient and robust machine learning solutions for Industry 4.0
Abstract:Recently, the fourth industrial revolution, or Industry 4.0, has been defined by the integration of advanced technologies such as automation, data analytics and the Internet of Things (IoT) into industrial and production processes. Artificial intelligence, in particular machine learning, enables us to build solutions that learn from experience and progress without explicit programming. By enabling the analysis and interpretation of massive volumes of data generated by industry-connected devices and powering cutting-edge automation and control systems, machine learning (ML) plays a key role in Industry 4.0. It enables the sector to reduce costs and downtime, predict maintenance, improve product quality and optimize the performance of industrial operations. This thesis will analyze the benefits, limitations and future directions of machine learning for Industry 4.0. Then, we will focus on the design of efficient and robust machine learning and deep learning solutions for Industry 4.0, with an emphasis on predictive maintenance, predictive quality control and inspection.
Keywords :
Publications :
- Advanced Machine Learning Approaches for Zero-Day Attack Detection: A Review
- Security and Privacy-Preserving for Machine Learning Models: Attacks, Countermeasures, and Future Directions
- Machine-Learning-Based Smart Energy Management Systems: A Review
Linkedin:http://linkedin.com/in/fatema-el-husseini-40a86081
Supervisor : Prof.Flavien Vernier.
Co-supervisor :Prof.Hassan N. Noura.
Start of thesis :1/09/2023
Ecole doctorale : SIE Sciences, Ingénierie, Environnement