Alexandre Personnic

I'm an AI researcher currently pursuing a PhD at KU Leuven in Belgium, where I focus on gaze estimation and visual attention modeling. My work blends deep learning, computer vision, and multimodal data processing to understand how humans visually interact with screens.

I graduated with a dual Master's degree in Applied Mathematics and Computer Science from ENSEEIHT and INSA Toulouse, specializing in artificial intelligence. During my studies, I balanced coursework with a research-oriented apprenticeship at Capgemini Engineering, where I worked, amongst other things, on real-time Speech-to-Text systems, quantum machine learning, and sustainable AI.

My master's thesis addressed the environmental impact of AI, where I built a Python library and AWS-based workflows to measure and reduce energy consumption in deep learning models. This work received top marks and contributed to internal tools still used at Capgemini today.

I'm passionate about making AI both smarter and more responsible, and I enjoy working at the intersection of research and engineering.