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Practical and Theoretical Questions in Network Synchronization: Optimization and Control Collective behavior in large ensembles of network-coupled dynamical systems remains an active area of research in the nonlinear dynamics and networks

Feedback-based online algorithms for time-varying network optimizationThe talk focuses on the synthesis and analysis of online algorithmic solutions to control networked systems based on performance objectives and engineering constraints that may

Finite-Horizon Approximate Linear Programs for an Infinite-Horizon Revenue Management ProblemApproximate linear programs have been used extensively to approximately solve stochastic dynamic programs that suffer from the well-known curse of

Inference on Winners Many empirical questions can be cast as inference on a parameter selected through optimization.  For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the

Spectral Problems in Inverse Scattering for Inhomogeneous MediaThe inverse scattering problem for inhomogeneous (possibly anisotropic) media amounts to solving a nonlinear ill-posed equation, thus presenting difficulties in arriving at a solution.

Granular flow: Particle Size Segregation and New Constitutive LawsThe segregation of particles of different sizes can be achieved by vibration or by shear flow. I describe a nonlinear conservation law that captures the main features of segregation

Differential imaging of evolution in elastic backgrounds with unknown microstructureMajor components of nuclear power plants e.g., reactors, fuel cells and containment vessels are comprised of highly heterogeneous composites that (a) their topology

Fairest edge usage in spanning treesThis talk will explore several interesting and interrelated optimization problems involving the spanning trees of a graph.  Each problem will be connected to a single fundamental question: How should we

On the dynamics of coupled Morris-Lecar NeuronsIn recent years, the study of computational neuronal dynamics has made remarkable progress has been made by on the nonlinear study of artificial neural networks. This approach relies on using models of

Designing frustration and topologically constrained disorder in artificial spin iceWe are all familiar with classical states of matter as ordered or disordered; and yet some of the most relevant phenomena in nature, from the nano-machinery of life