Ali Ramezani-Kebrya

Ali Ramezani-Kebrya is currently an Associate Professor (with tenure) in Computer Science at the University of Oslo. Previously, he was a postdoctoral fellow at the Laboratory for Information and Inference Systems (LIONS) at EPFL and the Vector Institute in Canada. His research focuses on large-scale and distributed machine learning, optimization, privacy/security, reinforcement learning, and communication/networking aspects of machine learning algorithms. He holds a Ph.D. from the University of Toronto.

Key research interests include developing robust federated learning frameworks, addressing label shift in distributed systems, and improving the generalization capabilities of stochastic gradient descent methods. His work bridges theoretical foundations with practical applications in distributed optimization and privacy-preserving machine learning.

• Recipient of the NSERC Postdoctoral Fellowship (equivalent to NSF fellowship in the US)

His publications emphasize advancements in distributed learning systems, robust optimization techniques, and theoretical guarantees for federated learning under covariate shifts. Current research trends explore Nash equilibrium-based approaches for robustness and communication-efficient algorithms in distributed settings.