activity
20172020
most citedExploring Algorithmic Fairness in Robust Graph Covering Problems

33 citations · 36 across the 5 of their papers we have counts for

collaborators

6 papers

cs.SI2020

Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness

Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi +5

Youth experiencing homelessness (YEH) are subject to substantially greater risk of HIV infection, compounded both by their lack of access to stable housing and the disproportionate…

cs.SI20201 cited

Preliminary Results from a Peer-Led, Social Network Intervention, Augmented by Artificial Intelligence to Prevent HIV among Youth Experiencing Homelessness

Eric Rice, Laura Onasch-Vera, Graham T. DiGuiseppi +5

Each year, there are nearly 4 million youth experiencing homelessness (YEH) in the United States with HIV prevalence ranging from 3 to 11.5%. Peer change agent (PCA) models for HIV…

math.OC202033 cited

Exploring Algorithmic Fairness in Robust Graph Covering Problems

Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti +4

Fueled by algorithmic advances, AI algorithms are increasingly being deployed in settings subject to unanticipated challenges with complex social effects. Motivated by real-world d…

cs.SI2019

Influence Maximization for Social Good: Use of Social Networks in Low Resource Communities

Amulya Yadav

This thesis proposal makes the following technical contributions: (i) we provide a definition of the Dynamic Influence Maximization Under Uncertainty (or DIME) problem, which model…

cs.AI20191 cited

Artificial Intelligence for Low-Resource Communities: Influence Maximization in an Uncertain World

Amulya Yadav

The potential of Artificial Intelligence (AI) to tackle challenging problems that afflict society is enormous, particularly in the areas of healthcare, conservation and public safe…

cs.SI20171 cited

Activating the "Breakfast Club": Modeling Influence Spread in Natural-World Social Networks

Lily Hu, Bryan Wilder, Amulya Yadav +2

While reigning models of diffusion have privileged the structure of a given social network as the key to informational exchange, real human interactions do not appear to take place…