Research

I am excited about tackling fundamental problems at the interface of stochastic modeling, network science, and inference, particularly in the context of complex socio-technical systems (like social media platforms) that have an increasing grip on society and our everyday lives. 

 

My doctoral research investigated how the network structure, specifically in the context of heterogeneous interactions, drives emergent properties in large-scale networked systems and how we can leverage this knowledge to improve system performance. My thesis contributed to i) balancing sparsity-connectivity trade-offs in network design for distributed systems and ii) modeling the spread of evolving contagions in high-stakes societal systems.

M. Sood, Structural Heterogeneity and Performance in Stochastic Networks: From Distributed Inference to Epidemics and Beyond, 

PhD Thesis, Carnegie Mellon University, Aug, 2024.


Selected Publications

[Balancing Sparsity-Connectivity Trade-offs in Distributed Network Design]

[Modeling the Spread of Evolving Contagions in Social Systems]