[Archimedes Talks] Contagion in Large-Scale Networks: Frameworks for Resource Allocation and Model-Agnostic Simulation
Title: Contagion in Large-Scale Networks: Frameworks for Resource Allocation and Model-Agnostic Simulation
Speaker: Marios Papachristou (final-year PhD candidate, Cornell University)
Abstract: In this talk, I focus on resource allocation in dynamically changing complex environments that undergo contagion in the real world, such as peer-to-peer lending networks, viral marketing campaigns, ridesharing, and financial networks. In these systems, a planner needs to allocate resources subject to a budget to cause or prevent contagion. These environments are often very large-scale and dynamically changing and usually have missing links. The current presentation aims to provide insights on two problems:
First, I present a model for allocations that can be provably and efficiently solved in large-scale networks and is more flexible than existing contagion models.
Second, I briefly focus on the absence of data in such networks and the limitations of existing agent-based models. Given the recent successes of Large Language Models (LLMs), I show that collectives of LLMs exhibit several macroscopic characteristics that are similar to human dynamics, such as preferential attachment and long-tailed degree distributions, homophily, and triadic closure. Finally, I suggest several avenues of research based on this paradigm.
(The talk contains joint work with Jon Kleinberg, Sid Banerjee, Amin Rahimian, Yuan Yuan, Chin-Chia Hsu, and Longqi Yang)
Short Bio: Marios Papachristou is a final-year Ph.D. candidate in the Computer Science Department at Cornell University, advised by Prof. Jon Kleinberg, and is joining the Department of Information Systems at the W.P. Carey School of Business at Arizona State University as a tenure-track Assistant Professor in Fall 2025. Marios works on algorithms and networks, exploring their roles within large-scale social and information systems, and understanding their wider societal implications. His research has been supported by an Onassis Scholarship and a LinkedIn Ph.D. Fellowship, a Cornell Fellowship, as well as grants from the A.G. Leventis Foundation and the Gerondelis Foundation.
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