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)

Informing University Covid-19 Decisions Using Simple Compartmental Models. - Benjamin Hurt; Aniruddha Adiga; Madhav V. Marathe; Christopher L. Barrett (WSC, 2021)

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)

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)

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)