Srinivasan Venkatramanan
Overview
Explore the profile of Srinivasan Venkatramanan including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
45
Citations
406
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
1.
Chen J, Hoops S, Mortveit H, Lewis B, Machi D, Bhattacharya P, et al.
PNAS Nexus
. 2024 Dec;
4(1):pgae557.
PMID: 39720202
This paper describes Epihiper, a state-of-the-art, high performance computational modeling framework for epidemic science. The Epihiper modeling framework supports custom disease models, and can simulate epidemics over dynamic, large-scale networks...
2.
Chen C, Wang Y, Kaur G, Adiga A, Espinoza B, Venkatramanan S, et al.
Epidemics
. 2024 Oct;
49:100793.
PMID: 39357172
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively...
3.
Loo S, Chinazzi M, Srivastava A, Venkatramanan S, Truelove S, Viboud C
Epidemics
. 2024 Aug;
48:100788.
PMID: 39209676
No abstract available.
4.
Mathis S, Webber A, Leon T, Murray E, Sun M, White L, et al.
Nat Commun
. 2024 Jul;
15(1):6289.
PMID: 39060259
Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of...
5.
Chen J, Bhattacharya P, Hoops S, Machi D, Adiga A, Mortveit H, et al.
Epidemics
. 2024 Jul;
48:100779.
PMID: 39024889
UVA-EpiHiper is a national scale agent-based model to support the US COVID-19 Scenario Modeling Hub (SMH). UVA-EpiHiper uses a detailed representation of the underlying social contact network along with data...
6.
Runge M, Shea K, Howerton E, Yan K, Hochheiser H, Rosenstrom E, et al.
Epidemics
. 2024 Jun;
47:100775.
PMID: 38838462
Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision...
7.
Bhattacharya P, Machi D, Chen J, Hoops S, Lewis B, Mortveit H, et al.
J Parallel Distrib Comput
. 2024 May;
191.
PMID: 38774820
We present MacKenzie, a HPC-driven multi-cluster workflow system that was used repeatedly to configure and execute fine-grained US national-scale epidemic simulation models during the COVID-19 pandemic. Mackenzie supported federal and...
8.
Lopez V, Cramer E, Pagano R, Drake J, ODea E, Adee M, et al.
PLoS Comput Biol
. 2024 May;
20(5):e1011200.
PMID: 38709852
During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by...
9.
Bhattacharya P, Chen J, Hoops S, Machi D, Lewis B, Venkatramanan S, et al.
Int J High Perform Comput Appl
. 2024 Apr;
37(1):4-27.
PMID: 38603425
This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning and response. The pipeline consists of () an automatic semantic-aware...
10.
Chen C, Wang Y, Kaur G, Adiga A, Espinoza B, Venkatramanan S, et al.
ArXiv
. 2024 Apr;
PMID: 38562450
The pandemic of COVID-19 has imposed tremendous pressure on public health systems and social economic ecosystems over the past years. To alleviate its social impact, it is important to proactively...