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Computational Complexity, Dynamical Systems, and Non-Convex OptimizationFor a given computational problem, computational complexity asks the question of the resources needed - such as time, space, energy - by anyalgorithm which solves the

Using Survival Information in Truncation by Death Problems Without the Monotonicity Assumption In some randomized clinical trials, patients may die before the measurements of their outcomes. Even though randomization generates comparable

Nancy Rodriguez, Department of Applied Mathematics, University of Colorado 51��ý"Mathematical Biology and Sociology: a Buff's Perspective"  Daniel Appelö, Department of Applied Mathematics, University of Colorado 51��ý“

ontrolling oscillations in high-order accurate methods through neural networksWhile discontinuous Galerkin methods have proven themselves to be powerful computational methods, capable of accurately solving a variety of PDE's, the combination of high

Neuroendocrine stress response and PTSDThe hypothalamic-pituitary-adrenal (HPA) axis is a neuroendocrine system that regulates numerous physiological processes. Disruptions are correlated with stress-related diseases such as PTSD and major

A touch of non-linearity in fluid fields: where spheres “think” collectively and swim togetherFrom crawling cells to orca whales, swimming in nature occurs at different scales. The study of swimming across length scales can shed light onto

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