Scholar Profile
At the Hebrew University of Jerusalem, Dr. Sharir’s doctorate in computer science tried to understand why certain neural network architectures are better than others in terms of the complexity of the tasks they can perform versus their overall computational budget.
His postdoctoral research at Caltech’s Department of Computing + Mathematical Sciences deepened his exploration of efficiency-driven approaches to machine learning.
In his lab at Technion, Dr. Sharir works on building a robust theoretical foundation for evaluating the strengths and weaknesses of newly proposed architectures.
