Rémi Bourgerie

I’m a PhD student in Computer Science at KTH Royal Institute of Technology, in the Department of Network and System Engineering. My research explores how networked systems and machine learning intersect, with a particular interest in graph neural networks. I am particularly interested in how topological structure shape information flow and learning in networked systems, and how these insights can help design more robust and efficient distributed intelligence.

Prior to the Phd

I studied mathematics and physics in the Classe Préparatoire aux Grandes Écoles (MP*) at Lycée Fénelon Sainte-Marie in Paris, France. After three intense but formative years, I joined École Centrale de Lyon in 2019, where I studied General Engineering.

In 2021, I moved to Sweden for a double degree through the TIME between École Centrale de Lyon and KTH Royal Institute of Technology, specializing in Machine Learning. During this time, I conducted my master’s thesis in the industry at Ericsson Global AI Accelerator, where I worked on applied machine learning using Graph Neural Networks and Federated Learning for software anomaly detection. I graduated in 2023 with both an Engineering degree from ECL and an MSc in Machine Learning from KTH.

I have been living in Stockholm since 2021 where I have discovered the enjoyment of quiet balance, the benefits of shared fika, and the meaning of lagom. Between forest walks and long northern evenings, Sweden has become both a place to live and a way to think.