New Insights from an Analysis of Social Influence Networks under the Linear Threshold Model - Srinivasan Venkatramanan; Anurag Kumar 001 (CoRR, 2010)

Co-evolution of content popularity and delivery in mobile P2P networks. - Srinivasan Venkatramanan; Anurag Kumar 001 (INFOCOM, 2012)

Spread of Influence and Content in Mobile Opportunistic Networks - Srinivasan Venkatramanan; Anurag Kumar 001 (CoRR, 2012)

Competition over timeline in social networks. - Eitan Altman; Parmod Kumar; Srinivasan Venkatramanan; Anurag Kumar 001 (ASONAM, 2013)

Competition for content spread over multiple social networks. - Srinivasan Venkatramanan; Anurag Kumar 001 (COMSNETS, 2014)

Influence Spread in Social Networks: A Study via a Fluid Limit of the Linear Threshold Model. - Srinivasan Venkatramanan; Anurag Kumar 001 (CoRR, 2014)

Co-Evolution of Content Spread and Popularityin Mobile Opportunistic Networks. - Srinivasan Venkatramanan; Anurag Kumar 001 (IEEE Trans. Mob. Comput., 2014)

Research Collaboration and Topic Trends in Computer Science: An Analysis Based on UCP Authors. - Yan Wu 016; Srinivasan Venkatramanan; Dah-Ming Chiu (WWW (Companion Volume), 2015)

Modeling and Analysis of Scholar Mobility on Scientific Landscape. - Qiufang Ying; Srinivasan Venkatramanan; Dah-Ming Chiu (WWW (Companion Volume), 2015)

A Population Model for the Academic Ecosystem. - Yan Wu 016; Srinivasan Venkatramanan; Dah Ming Chiu (CoRR, 2015)

To delay or not: Temporal vaccination games on networks. - Abhijin Adiga; Srini Venkat; Anil Vullikanti (INFOCOM, 2016)

Get To the Top and Stay There: A Study of Citation Rank Dynamics in Academia. - Yan Wu 016; Srini Venkat; Dah-Ming Chiu (WWW (Companion Volume), 2016)

Research collaboration and topic trends in Computer Science based on top active authors. - Yan Wu 016; Srinivasan Venkatramanan; Dah Ming Chiu (PeerJ Comput. Sci., 2016)

Towards robust models of food flows and their role in invasive species spread. - Srinivasan Venkatramanan; Sichao Wu; Bowen Shi; Achla Marathe; Madhav V. Marathe; Stephen G. Eubank; Lalit P. Sah; A. P. Giri; Luke A. Colavito; K. S. Nitin; V. Sridhar; R. Asokan; et al. (IEEE BigData, 2017)

Epidemic Forecasting Framework Combining Agent-Based Models and Smart Beam Particle Filtering. - Farzaneh Tabataba; Bryan L. Lewis; Milad Hosseinipour; Foroogh S. Tabataba; Srinivasan Venkatramanan; Jiangzhuo Chen; Dave Higdon; Madhav V. Marathe (ICDM, 2017)

Spatio-Temporal Optimization of Seasonal Vaccination Using a Metapopulation Model of Influenza. - Srinivasan Venkatramanan; Jiangzhuo Chen; Sandeep Gupta 004; Bryan L. Lewis; Madhav V. Marathe; Henning S. Mortveit; Anil Vullikanti (ICHI, 2017)

A Framework for Evaluating Epidemic Forecasts. - Farzaneh Sadat Tabataba; Prithwish Chakraborty; Naren Ramakrishnan; Srinivasan Venkatramanan; Jiangzhuo Chen; Bryan L. Lewis; Madhav V. Marathe (CoRR, 2017)

Using Network Reliability to Understand International Food Trade Dynamics. - Madhurima Nath; Srinivasan Venkatramanan; Bryan Kaperick; Stephen G. Eubank; Madhav V. Marathe; Achla Marathe; Abhijin Adiga (COMPLEX NETWORKS (1), 2018)

Profiling OSN Users Based on Temporal Posting Patterns. - Qiufang Ying; Dah Ming Chiu; Srinivasan Venkatramanan; Xiaopeng Zhang (WWW (Companion Volume), 2018)

Calibrating a Stochastic, Agent-Based Model Using Quantile-Based Emulation. - Arindam Fadikar; Dave Higdon; Jiangzhuo Chen; Bryan L. Lewis; Srinivasan Venkatramanan; Madhav V. Marathe (SIAM/ASA J. Uncertain. Quantification, 2018)

User modeling and usage profiling based on temporal posting behavior in OSNs. - Qiufang Ying; Dah Ming Chiu; Srinivasan Venkatramanan; Xiaopeng Zhang (Online Soc. Networks Media, 2018)

Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints. - Srinivasan Venkatramanan; Jiangzhuo Chen; Arindam Fadikar; Sandeep Gupta 004; Dave Higdon; Bryan L. Lewis; Madhav V. Marathe; Henning S. Mortveit; Anil Vullikanti (PLoS Comput. Biol., 2019)

Designing Effective and Practical Interventions to Contain Epidemics. - Prathyush Sambaturu; Bijaya Adhikari; B. Aditya Prakash; Srinivasan Venkatramanan; Anil Vullikanti (AAMAS, 2020)

Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting. - Lijing Wang 001; Aniruddha Adiga; Srinivasan Venkatramanan; Jiangzhuo Chen; Bryan L. Lewis; Madhav V. Marathe (IEEE BigData, 2020)

From 5Vs to 6Cs: Operationalizing Epidemic Data Management with COVID-19 Surveillance. - Akhil Sai Peddireddy; Dawen Xie; Pramod Patil; Mandy L. Wilson; Dustin Machi; Srinivasan Venkatramanan; Brian Klahn; Przemyslaw J. Porebski; Parantapa Bhattacharya; Shirish Dumbre; Erin Raymond; Madhav V. Marathe (IEEE BigData, 2020)

Models for COVID-19 Pandemic: A Comparative Analysis. - Aniruddha Adiga; Devdatt P. Dubhashi; Bryan L. Lewis; Madhav V. Marathe; Srinivasan Venkatramanan; Anil Vullikanti (CoRR, 2020)

Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway. - Alok Talekar; Sharad Shriram; Nidhin K. Vaidhiyan; Gaurav Aggarwal; Jiangzhuo Chen; Srinivasan Venkatramanan; Lijing Wang 001; Aniruddha Adiga; Adam Sadilek; Ashish Tendulkar; Madhav V. Marathe; Rajesh Sundaresan; et al. (AAMAS, 2021)

AI-Driven Agent-Based Models to Study the Role of Vaccine Acceptance in Controlling COVID-19 Spread in the US. - Parantapa Bhattacharya; Dustin Machi; Jiangzhuo Chen; Stefan Hoops; Bryan L. Lewis; Henning S. Mortveit; Srinivasan Venkatramanan; Mandy L. Wilson; Achla Marathe; Przemyslaw J. Porebski; Brian Klahn; Joseph Outten; et al. (IEEE BigData, 2021)

Scalable Epidemiological Workflows to Support COVID-19 Planning and Response. - Dustin Machi; Parantapa Bhattacharya; Stefan Hoops; Jiangzhuo Chen; Henning S. Mortveit; Srinivasan Venkatramanan; Bryan L. Lewis; Mandy L. Wilson; Arindam Fadikar; Tom Maiden; Christopher L. Barrett; Madhav V. Marathe (IPDPS, 2021)

All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting. - Aniruddha Adiga; Lijing Wang 001; Benjamin Hurt; Akhil Sai Peddireddy; Przemyslaw J. Porebski; Srinivasan Venkatramanan; Bryan Leroy Lewis; Madhav V. Marathe (KDD, 2021)

High Performance Agent-Based Modeling to Study Realistic Contact Tracing Protocols. - Stefan Hoops; Jiangzhuo Chen; Abhijin Adiga; Bryan L. Lewis; Henning S. Mortveit; Hannah Baek; Mandy L. Wilson; Dawen Xie; Samarth Swarup; Srinivasan Venkatramanan; Justin Crow; Elena Diskin; et al. (WSC, 2021)

A Population Model for Academia: Case Study of the Computer Science Community Using DBLP Bibliography 1960-2016. - Yan Wu 016; Srinivasan Venkatramanan; Dah Ming Chiu (IEEE Trans. Emerg. Top. Comput., 2021)

CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting. - Lijing Wang 001; Aniruddha Adiga; Jiangzhuo Chen; Adam Sadilek; Srinivasan Venkatramanan; Madhav V. Marathe (AAAI, 2022)

Enhancing COVID-19 Ensemble Forecasting Model Performance Using Auxiliary Data Sources. - Aniruddha Adiga; Gursharn Kaur; Benjamin Hurt; Lijing Wang 001; Przemyslaw J. Porebski; Srinivasan Venkatramanan; Bryan L. Lewis; Madhav V. Marathe (IEEE Big Data, 2022)

Effective Social Network-Based Allocation of COVID-19 Vaccines. - Jiangzhuo Chen; Stefan Hoops; Achla Marathe; Henning S. Mortveit; Bryan L. Lewis; Srinivasan Venkatramanan; Arash Haddadan; Parantapa Bhattacharya; Abhijin Adiga; Anil Vullikanti; Aravind Srinivasan; Mandy L. Wilson; et al. (KDD, 2022)

Evaluating the Utility of High-Resolution Proximity Metrics in Predicting the Spread of COVID-19. - Zakaria Mehrab; Aniruddha Adiga; Madhav V. Marathe; Srinivasan Venkatramanan; Samarth Swarup (ACM Trans. Spatial Algorithms Syst., 2022)

Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts. - Aniruddha Adiga; Gursharn Kaur; Lijing Wang 001; Benjamin Hurt; Przemyslaw J. Porebski; Srinivasan Venkatramanan; Bryan L. Lewis; Madhav V. Marathe (AAAI, 2023)

A Multi-Team Multi-Model Collaborative Covid-19 Forecasting Hub for India. - Aniruddha Adiga; Benjamin Hurt; Gursharn Kaur; Bryan Lewis 001; Madhav V. Marathe; Przemyslaw J. Porebski; Srinivasan Venkatramanan; Ambedkar Dukkipati; Tony Gracious; Shubham Gupta; Nihesh Rathod; Rajesh Sundaresan; et al. (WSC, 2023)

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support. - Parantapa Bhattacharya; Jiangzhuo Chen; Stefan Hoops; Dustin Machi; Bryan L. Lewis; Srinivasan Venkatramanan; Mandy L. Wilson; Brian Klahn; Aniruddha Adiga; Benjamin Hurt; Joseph Outten; Abhijin Adiga; et al. (Int. J. High Perform. Comput. Appl., 2023)

A Generalizable Theory-Driven Agent-Based Framework to Study Conflict-Induced Forced Migration. - Zakaria Mehrab; Logan Stundal; Srinivasan Venkatramanan; Samarth Swarup; Bryan Leroy Lewis; Henning S. Mortveit; Christopher L. Barrett; Abhishek Pandey; Chad R. Wells; Alison P. Galvani; Burton H. Singer; Seyed M. Moghadas; et al. (AAAI, 2024)

Network Agency: An Agent-based Model of Forced Migration from Ukraine. - Zakaria Mehrab; Logan Stundal; Samarth Swarup; Srinivasan Venkatramanan; Bryan Lewis 001; Henning S. Mortveit; Christopher L. Barrett; Abhishek Pandey; Chad R. Wells; Alison P. Galvani; Burton H. Singer; David Leblang; et al. (AAMAS, 2024)

Agent-Based Simulation Framework for Multi-Variant Surveillance. - Sifat Afroj Moon; Jiangzhuo Chen; Baltazar Espinoza; Bryan Lewis 001; Madhav V. Marathe; Joseph Outten; Srinivasan Venkatramanan; Anil Vullikanti; Andrew S. Warren (WSC, 2024)

Novel multi-cluster workflow system to support real-time HPC-enabled epidemic science: Investigating the impact of vaccine acceptance on COVID-19 spread. - Parantapa Bhattacharya; Dustin Machi; Jiangzhuo Chen; Stefan Hoops; Bryan Lewis 001; Henning S. Mortveit; Srinivasan Venkatramanan; Mandy L. Wilson; Achla Marathe; Przemyslaw J. Porebski; Brian Klahn; Joseph Outten; et al. (J. Parallel Distributed Comput., 2024)

Challenges of COVID-19 Case Forecasting in the US, 2020-2021. - Velma K. Lopez; Estee Y. Cramer; Robert Pagano; John M. Drake; Eamon B. O'Dea; Madeline Adee; Turgay Ayer; Jagpreet Chhatwal; Ozden O. Dalgic; Mary A. Ladd; Benjamin P. Linas; Peter P. Mueller; et al. (PLoS Comput. Biol., 2024)