Alireza Fallah

Alireza is a PhD student in the Department of Electrical Engineering and Computer Science. His research is focused on developing new robust and accelerated optimization methods for machine learning applications. He uses MATLAB to tune algorithms to achieve the desired trade-off between convergence rate and robustness, making use of CVX to find the best set of parameters. With the Symbolic Math Toolbox, Alireza is also able to propose a specific parameterization by solving a set of matrix inequalities. He also works on characterizing the convergence properties of a class of meta-learning algorithms and its applications in other domains such as federated learning. In that regard, he uses MATLAB to certify the theoretical results through numerical experiments over both real and synthetic data sets. Alireza earned a BSc in electrical engineering and a BSc in mathematics from Sharif University of Technology, Iran.



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