Hei hei,
My name is Ali. I am from Toronto, Canada and lived in Switzerland and Denmark before moving to Norway. Before joining UiO, I have been a senior scientific collaborator at EPFL, working in Laboratory for Information and Inference Systems (LIONS). Before joining LIONS, I was a postdoctoral fellow at the Vector Institute in Toronto. I finished my Ph.D. at the University of Toronto. My Ph.D. research was focused on developing theory and practices for next generation large-scale distributed and heterogeneous networks.
I work in machine learning and study scalability, robustness, privacy, generalization, and stability aspects of machine learning algorithms. In particular, I am developing highly scalable, privacy-preserving, and robust algorithms to train very large models in a distributed manner. Our algorithms can be used in so-called ‘‘federated learning’’ settings, where a deep model is trained on data distributed among multiple owners who cannot necessarily share their data, e.g., due to privacy concerns, competition, or by law. I also study the design of the underlying architecture over which a learning algorithm is applied, in particular, the fundamental question of ‘‘How much should we overparameterize a neural network?’’
I enjoy hiking, playing volleyball, board games, and learning Norsk!