Navid's research interests span a wide spectrum of topics in optimization, machine learning, networks, and markets. His work has focused on various problems at the intersection of these areas, including nonconvex optimization, deep learning theory, pricing, networked markets, distributed algorithms, and spreading processes in networks. The Role of Optimizers in Generalization of Deep Learning
Optimization and Pricing in Markets
Stochastic Optimization Algorithms in Estimation
Algorithms for Distributed Computation
Spreading Processes in Complex Networks
