Negatively reinforced balanced urn schemes. - Gursharn Kaur (Adv. Appl. Math., 2019)

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)

Reconstructing an Epidemic Outbreak Using Steiner Connectivity. - Ritwick Mishra; Jack Heavey; Gursharn Kaur; Abhijin Adiga; Anil Vullikanti (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)

Interacting urns on a finite directed graph. - Gursharn Kaur; Neeraja Sahasrabudhe (J. Appl. Probab., 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)

Interacting urns on directed networks with node-dependent sampling and reinforcement. - Gursharn Kaur; Neeraja Sahasrabudhe (J. Appl. Probab., 2025)