This article outlines our point of view regarding the applicability, state-of-the-art, and potential
of quantum computing for problems in finance. We provide an introduction to quantum …

In this paper, we propose a novel, computational efficient, dynamic ridesharing algorithm.
The beneficial computational properties of the algorithm arise from casting the ridesharing …

This paper develops online algorithms to track solutions of time-varying constrained optimization
problems. Particularly, resembling workhorse Kalman filtering-based approaches for …

One of the cornerstones of the field of signal processing on graphs are graph filters, direct
analogs of classical filters, but intended for signals defined on graphs. This paper brings forth …

We propose a class of convex relaxations to solve the sensor network localization problem,
based on a maximum likelihood (ML) formulation. This class, as well as the tightness of the …

Dual decomposition has been successfully employed in a variety of distributed convex
optimization problems solved by a network of computing and communicating nodes. Often, when …

This paper considers distribution networks featuring inverter-interfaced distributed energy
resources, and develops distributed feedback controllers that continuously drive the inverter …

This paper develops a real-time algorithmic framework for aggregations of distributed energy
resources (DERs) in distribution networks to provide regulation services in response to …

Optimization underpins many of the challenges that science and technology face on a daily
basis. Recent years have witnessed a major shift from traditional optimization paradigms …

The determination of vehicle routes fulfilling connectivity, time, and operational constraints
is a well-studied combinatorial optimization problem. The NP-hard complexity of vehicle …