Some glimpses of my research profile…

Below is a list of my published projects (in descending order of publication year) and upcoming conference presentations. Please refer to my CV, Researchgate profile or Google Scholar page to get a complete list of my preprints, ongoing projects, past presentations and accolades. My CV also contains the most updated list of my administrative and peer review activities.

Published Works

• Kundu, R., Datta, J., Ray, D., Mishra, S., Bhattacharyya, R., Zimmermann, L, & Mukherjee, B. (2023). Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021. PLOS Global Public Health, 3(12), e0002063.

• Bhattacharyya, R., Henderson, N., & Baladandayuthapani, V. (2023, January). BaySyn: Bayesian evidence synthesis for multi-system multiomic integration. In Pacific Symposium on Biocomputing (Vol. 28, No. 2023, pp. 275-286).

• Bhattacharyya, R., Burman, A., Singh, K., Banerjee, S., Maity, S., Auddy, A., … & Baladandayuthapani, V. (2022). Role of multi-resolution vulnerability indices in COVID-19 spread in India: A Bayesian model-based analysis. BMJ Open, 12(11), e056292.

• Salvatore, M., Purkayastha, S., Ganapathi, L., Bhattacharyya, R., Kundu, R., Zimmermann, L., … & Mukherjee, B. (2022). Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience. Science Advances, 8(24), eabp8621.

• Bhattacharyya, R., Banerjee, S., Mohammed, S., & Baladandayuthapani, V. (2023). Network-based modeling of COVID-19 dynamics: early pandemic spread in India. Journal of the Indian Statistical Association, 59 (2), 1-43.

• Purkayastha, S., Bhattacharyya, R., Bhaduri, R., Kundu, R., Gu, X., Salvatore, M., … & Mukherjee, B. (2021). A comparison of five epidemiological models for transmission of SARS-CoV-2 in India. BMC Infectious Diseases, 21(1), 1-23.

• Bhattacharyya, R., Kundu, R., Bhaduri, R., Ray, D., Beesley, L. J., Salvatore, M., & Mukherjee, B. (2021). Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates. Scientific Reports, 11(1), 1-14.

• Ray, D., Bhattacharyya, R., & Mukherjee, B. (2021). Discussion on “The timing and effectiveness of implementing mild interventions of COVID-19 in large industrial regions via a synthetic control method” by Tian et al. Statistics and Its Interface, 14(1), 25-28.

• Salvatore, M., Basu, D., Ray, D., Kleinsasser, M., Purkayastha, S., Bhattacharyya, R., & Mukherjee, B. (2020). Comprehensive public health evaluation of lockdown as a non-pharmaceutical intervention on COVID-19 spread in India: national trends masking state-level variations. BMJ Open, 10(12), e041778.

• Ray, D., Salvatore, M., Bhattacharyya, R., Wang, L., Du, J., Mohammed, S., … & Mukherjee, B. (2020). Predictions, role of interventions and effects of a historic national lockdown in India’s response to the COVID-19 pandemic: data science call to arms. Harvard Data Science Review, 2020(Suppl 1).

• Bhattacharyya, R., Ha, M. J., Liu, Q., Akbani, R., Liang, H., & Baladandayuthapani, V. (2020). Personalized network modeling of the pan-cancer patient and cell line interactome. JCO Clinical Cancer Informatics, 4, 399-411.

• Liu, Q., Ha, M. J., Bhattacharyya, R., Garmire, L., & Baladandayuthapani, V. (2020, January). Network-based matching of patients and targeted therapies for precision oncology. In Pacific Symposium on Biocomputing (Vol. 25, No. 2020, pp. 623-634).

Upcoming Presentations

• Coming soon!