M
Madhav V. Marathe
Researcher at University of Virginia
Publications - 356
Citations - 15017
Madhav V. Marathe is an academic researcher from University of Virginia. The author has contributed to research in topics: Approximation algorithm & Computer science. The author has an hindex of 53, co-authored 315 publications receiving 13493 citations. Previous affiliations of Madhav V. Marathe include University at Albany, SUNY & Los Alamos National Laboratory.
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Impact of weeknight and weekend curfews using mobility data: a case study of bengaluru urban
Aravind Adiga,Srinivas Prasanna Kumar Athreya,Madhav V. Marathe,J. Midthala,Nihesh Rathod,Rajesh Sundaresan,Sharadha Venkataramanan,Sarath Yasodharan +7 more
TL;DR: In this paper , the authors assess the impact of curfew using community mobility reports published by Google and quantitatively quantify the impact on the spread of the Omicron variant of SARS-CoV-2.
Journal ArticleDOI
Contextualized Behavior Recommendation from Complex Agent-Based Simulations of Disasters
TL;DR: In this article, the authors present an approach for generating contextualized behavior recommendations from a large, data-driven, complex agent-based simulation by decomposing the output of a simulation into a tree of causally-relevant states and show how behavior recommendations can be generated by ranking these causally relevant states in terms of their impact on an outcome of interest.
Journal ArticleDOI
Enhancing COVID-19 Ensemble Forecasting Model Performance Using Auxiliary Data Sources
Aniruddha Adiga,Gursharn Kaur,Benjamin Hurt,Lijing Wang,Przemyslaw J. Porebski,Srinivasan Venkatramanan,Bryan Lewis,Madhav V. Marathe +7 more
TL;DR: In this paper , a Bayesian model averaging ensemble technique consisting of statistical, deep learning, and compartmental models for forecasting epidemiological signals, specifically, COVID-19 signals, is presented.
Posted Content
Pandemic Informatics: Preparation, Robustness, and Resilience
TL;DR: An effective strategy to reduce the national and global burden of pandemics must: detect timing and location of occurrence, taking into account the many interdependent driving factors; anticipate public reaction to an outbreak, including panic behaviors that obstruct responders and spread contagion.