Navid's research interests span a wide spectrum of topics in machine learning, optimization, control, and networks. His work has focused on various problems at the intersection of these areas, including deep learning theory, nonconvex optimization, distributed algorithms for machine learning, networked markets, rumor spread in social networks, and information processing in biological networks. Stochastic Optimization Algorithms
Distributed Learning/Optimization
Optimization and Pricing in Markets
Spreading Processes in Complex Networks
Biological Networks
