Djalel obtained his PhD in Machine Learning from the University Paris-Saclay, under the supervision of Balázs Kégl. During his PhD, in immersion within a particle physics laboratory, he explored Reinforcement Learning methods for budgeted learning and fast supervised prediction, typically to be applied in high-energy physics and trigger design. Djalel has various AI-related interests, such as hyperparameter optimisation, collaborative machine learning, and medical applications; however, his main interest remains data-efficient reinforcement learning.

Interests

• reinforcement learning
• model-based reinforcement learning
• meta-learning