Florimond is a PhD student in the Computational Privacy Group at Imperial College. He graduated in 2017 with a Master of Engineering in applied mathematics at the Université catholique de Louvain, in Belgium, where he studied a range of topics from mathematics to computer science, with a particular focus on discrete math, algorithms, and statistical modelling. He first started working on privacy during an internship at MIT.
Research-wise, He's been interested in a range of questions in adversarial privacy, ranging from query obfuscation to protect privacy in Web search queries to large-scale network-based attacks. He interned at Google in 2019, where he worked on differential privacy. He's also been a teaching assistant in machine learning and privacy engineering at Imperial.
Contributions by Florimond Houssiau
Getting lost in the crowd: The limits of privacy in location data