87 citations · 233 across the 36 of their papers we have counts for
42 papers
Mechanism Design for Privacy-Preserving Information Sharing in Oligopoly Competition
Yuxin Liu, M. Amin Rahimian
Information sharing among competing suppliers can improve decisions under demand uncertainty, but it may also intensify strategic interaction by aligning firms' beliefs. We study a…
Socio-Spatial Patterns of Suicide Mortality in the United States
Kushagra Tiwari, M. Amin Rahimian, Marie-Laure Charpignon +2
Suicide causes more than 49,000 deaths annually in the United States, 55% involving firearms. Suicide mortality varies substantially across US counties, but the role of large-scale…
Privacy at Scale in Networked Healthcare
M. Amin Rahimian, Benjamin Panny, James Joshi
Digitized, networked healthcare promises earlier detection, precision therapeutics, and continuous care; yet, it also expands the surface for privacy loss and compliance risk. We a…
Extended Persistent Homology Distinguishes Simple and Complex Contagions with High Accuracy
Vahid Shamsaddini, M. Amin Rahimian
The social contagion literature makes a distinction between simple (independent cascade or bond percolation processes that pass infections through edges) and complex contagions (bo…
Structural Dynamics of Harmful Content Dissemination on WhatsApp
Yuxin Liu, M. Amin Rahimian, Kiran Garimella
WhatsApp, a platform with more than two billion global users, plays a crucial role in digital communication, but also serves as a vector for harmful content such as misinformation,…
Conformal-DP: A Density-Aware Mechanism for Differential Privacy over Riemannian Manifolds via Conformal Transformation
Peilin He, Liou Tang, M. Amin Rahimian +1
Differential Privacy (DP) is being increasingly adopted for non-Euclidean data that lie on complex, high-dimensional manifolds. Existing DP mechanisms for manifold data consider ge…
Privacy-Aware Sequential Learning
Yuxin Liu, M. Amin Rahimian
Sequential learning often relies on individuals reporting private information, with early reports shaping later beliefs and collective decisions. When such reports are sensitive, p…
Democratic Resilience and Sociotechnical Shocks
M. Amin Rahimian, Michael P. Colaresi
We focus on the potential fragility of democratic elections given modern information-communication technologies (ICT) in the Web 2.0 era. Our work provides an explanation for the c…
Measuring Network Dynamics of Opioid Overdose Deaths in the United States
Kushagra Tiwari, M. Amin Rahimian, Mark S. Roberts +2
The US opioid overdose epidemic has been a major public health concern in recent decades. There has been increasing recognition that its etiology is rooted in part in the social co…
Optimized Model Selection for Estimating Treatment Effects from Costly Simulations of the US Opioid Epidemic
Abdulrahman A. Ahmed, M. Amin Rahimian, Mark S. Roberts
Agent-based simulation with a synthetic population can help us compare different treatment conditions while keeping everything else constant within the same population (i.e., as di…
Differentially Private Distributed Inference for Multicenter Clinical Studies
Marios Papachristou, M. Amin Rahimian
Extracting reliable conclusions from data distributed across institutions is a core problem in healthcare: pooling patient records would improve inference, but privacy regulations…
Estimating Treatment Effects Using Costly Simulation Samples from a Population-Scale Model of Opioid Use Disorder
Abdulrahman A. Ahmed, M. Amin Rahimian, Mark S. Roberts
Large-scale models require substantial computational resources for analysis and studying treatment conditions. Specifically, estimating treatment effects using simulations may requ…
Inferring epidemic dynamics using Gaussian process emulation of agent-based simulations
Abdulrahman A. Ahmed, M. Amin Rahimian, Mark S. Roberts
Computational models help decision makers understand epidemic dynamics to optimize public health interventions. Agent-based simulation of disease spread in synthetic populations al…
Differentially Private Distributed Estimation and Learning
Marios Papachristou, M. Amin Rahimian
We study distributed estimation and learning problems in a networked environment where agents exchange information to estimate unknown statistical properties of random variables fr…
Structural Measures of Resilience for Supply Chains
Marios Papachristou, M. Amin Rahimian, Arash Azadegan
Modern production systems are increasingly defined by dense networks of multi-tier sourcing dependencies, where localized upstream disruptions can cascade into system-wide collapse…
Influence of Repetition through Limited Recall
Jad Sassine, M. Amin Rahimian, Dean Eckles
Decision makers who receive many signals are subject to imperfect recall. This is especially important when learning from feeds that aggregate messages from many senders on social…
When social influence promotes the wisdom of crowds
Abdullah Almaatouq, M. Amin Rahimian, Jason W. Burton +1
Whether, and under what conditions, groups exhibit "crowd wisdom" has been a major focus of research across the social and computational sciences. Much of this work has focused on…
Seeding with Costly Network Information
Dean Eckles, Hossein Esfandiari, Elchanan Mossel +1
We study the task of selecting nodes, in a social network of size , to seed a diffusion with maximum expected spread size, under the independent cascade model with cascade p…
Long ties accelerate noisy threshold-based contagions
Dean Eckles, Elchanan Mossel, M. Amin Rahimian +1
Network structure can affect when and how widely new ideas, products, and behaviors are adopted. In widely-used models of biological contagion, interventions that randomly rewire e…
Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard
Jan Hązła, Ali Jadbabaie, Elchanan Mossel +1
We study the Bayesian model of opinion exchange of fully rational agents arranged on a network. In this model, the agents receive private signals that are indicative of an unkown s…
Bayesian Decision Making in Groups is Hard
Jan Hązła, Ali Jadbabaie, Elchanan Mossel +1
We study the computations that Bayesian agents undertake when exchanging opinions over a network. The agents act repeatedly on their private information and take myopic actions tha…
Structural Controllability of Multi-Agent Networks: Robustness against Simultaneous Failures
M. Amin Rahimian, Amir G. Aghdam
In this paper, structural controllability of a leader-follower multi-agent system with multiple leaders is studied from a graph-theoretic point of view. The problem of preservation…
Digraphs with Distinguishable Dynamics under the Multi-Agent Agreement Protocol
M. Amin Rahimian, Amir Ajorlou, Amir G. Aghdam
In this work, the ability to distinguish digraphs from the output response of some observing agents in a multi-agent network under the agreement protocol has been studied. Given a…
Learning without recall in directed circles and rooted trees
M. Amin Rahimian, Ali Jadbabaie
This work investigates the case of a network of agents that attempt to learn some unknown state of the world amongst the finitely many possibilities. At each time step, agents all…