I am a final-year PhD student at King Abdullah University of Science and Technology (KAUST), advised by Peter Richtárik. My research focuses on optimization for distributed machine learning and private federated learning.
During my PhD, I spent time at Apple and Samsung AI Center (Cambridge, UK), where I worked on heterogeneous, efficient, and personalized federated learning.
I am currently on the job market.
Apart from research, I am also passionate about hiking/backpacking, alpine skiing, and rationality.
BSc in Applied Mathematics, Computer Science and Physics, 2019
Moscow Institute of Physics and Technology
We provide analysis of the inexact orthogonalized update at Muon’s core, revealing a fundamental coupling between LMO inexactness and optimal step size and momentum.
We propose a general yet simple theorem describing the convergence of SGD under the arbitrary sampling paradigm.