I am a second-year PhD student with research interests in Software Engineering, Machine Learning, and Green Software. My work initially focused on the variability and co-evolution of software systems, particularly through the use of Large Language Models (LLMs).

Over time, I started to see LLMs as configurable software systems. This perspective led me to apply variability modeling principles to study trade-offs between performance and accuracy in LLM inference. Through my research group, I was also introduced to energy-related challenges in software systems, which led me to develop an interest in Green Software. Since then, I have extended my work to include energy consumption as a key dimension, and I now focus on the intersection of configuration, LLM inference, and energy efficiency.

Prior to my PhD, I completed both my Bachelor’s and Master’s degrees at the University of Lille, where I specialized in Software Engineering.

News

• Mar 2026: Our paper “Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters” was accepted at EASE’26.
• Sep 2025: Presented our paper “LLM-based Co-Evolution of Configurable Software Systems” in SPLC’25 at A Coruña, Spain.
• Jun 2025: Presented our poster “LLM-based Co-Evolution of Configurable Software Systems” in GDR/GPL at Pau, France.
• May 2025: Our paper “LLM-based Co-Evolution of Configurable Software Systems” was accepted to SPLC’25.
• Nov 2024: Joined Inria Lille as a PhD student.