Matching, capturing allocation of items to unit-demand buyers, or tasks to workers, or pairs of
collaborators, is a central problem in economics. Indeed, the growing prevalence of …

We provide prophet inequality algorithms for online weighted matching in general (non-
bipartite) graphs, under two well-studied arrival models, namely edge arrival and vertex …

Rideshare platforms, when assigning requests to drivers, tend to maximize profit for the
system and/or minimize waiting time for riders. Such platforms can exacerbate biases that …

Online bipartite matching is one of the most fundamental problems in the online algorithms
literature. Karp, Vazirani, and Vazirani (STOC 1990) gave an elegant algorithm for …

Motivated by centralized matching markets, we study an online stochastic matching problem
on edge-weighted graphs, where the agents' arrivals and abandonments are stochastic and …

Many patients in need of a kidney transplant have a willing but incompatible (or poorly
matched) living donor. Kidney exchange programs arrange exchanges among such patient …

Motivated by online labor markets, we consider the online assortment optimization problem
faced by a two-sided matching platform that hosts a set of suppliers waiting to match with a …

Nonprofit crowdsourcing platforms such as food recovery organizations rely on volunteers to
perform time-sensitive tasks. Thus, their success crucially depends on efficient volunteer …

In response to mass casualty incidents, medical aid must be provided to numerous victims
synchronously under challenging circumstances including uncertainty about the condition of …

Three decades ago, Karp, Vazirani, and Vazirani (STOC 1990) defined the online matching
problem and gave an optimal (1-1/e)-competitive (about 0.632) algorithm. Fifteen years later …