Summary
Houssam Zenati is a machine learning researcher and Research Fellow at UCL with nine years of experience bridging academic and industry research in computational neuroscience, causal learning, and deep reinforcement learning. Trained at École Centrale Paris and ENS Paris-Saclay, he progressed from research internships to PhD and postdoctoral roles at Inria and industry research at Criteo and IBM, applying rigorous applied mathematics to real-world ML systems. His work spans causal inference, generative models and embodied RL, and he has a track record of moving ideas from internships into long-term research positions. Based in London and connected to the Gatsby Computational Neuroscience Unit, he blends theoretical depth with practical experimentation—an asset for teams seeking interpretable, scientifically grounded ML solutions.
9 years of coding experience
6 years of employment as a software developer
Master of Engineering (M.Eng), Executive Engineering Field Of Study : Applied Mathematics, Master of Engineering (M.Eng), Executive Engineering Field Of Study : Applied Mathematics at Ecole Centrale Paris
Master of Science - MS, Computational and Applied Mathematics, Master of Science - MS, Computational and Applied Mathematics at École normale supérieure Paris-Saclay
Mathematics, Physics, Engineering Sciences, Computer Science, Mathematics, Physics, Engineering Sciences, Computer Science at Lycée Louis-le-Grand
Shanghai JiaoTong University Summer School, Chinese politics and global governance, Shanghai JiaoTong University Summer School, Chinese politics and global governance at 上海交通大学
French, English, Arabic, Chinese