PhD Thesis

Between 2016 and 2023, I conducted my doctoral research on the topic of soft sensors for complex systems. My work was co-supervised by Professor Mohammed Lehsaini at the University of Tlemcen (Algeria) and Professor Hamid Bouchachia at Bournemouth University (UK).

Initially, the focus of my thesis was on the theoretical modeling of soft sensors—virtual constructs that infer unmeasurable or hard-to-measure parameters from observable data. As the work evolved, I was drawn toward smart energy systems, particularly in the context of residential buildings.

This shift in application led me to explore:

• Non-Intrusive Load Monitoring (NILM) techniques
• Machine learning algorithms for time-series energy data
• Deep learning architectures for event detection and appliance disaggregation
• The integration of contextual and behavioral features into predictive energy models

My thesis contributed to the development of intelligent systems capable of improving energy awareness and reducing consumption without relying on hardware-based sensors.

🧑‍🏫 Teaching & Supervision

Alongside my research, I had the opportunity to:

• Teach Advanced Operating Systems to third-year undergraduate students (L3)
• Co-supervise Master’s final projects (PFE) in topics related to systems, energy, and machine learning

This experience helped strengthen my academic communication, mentoring abilities, and curriculum development skills.

The thesis journey was both intellectually demanding and deeply rewarding, spanning multiple disciplines—from signal processing and machine learning to distributed systems and real-world sustainability use cases.