Shariq Mohammed, PhD
Assistant Professor
Boston University School of Public Health

PhD, University of Connecticut
MS, University of Connecticut
MSc, Chennai Mathematical Institute
BA, Indian Statistical Institute

I am an Assistant Professor in the Department of Biostatistics at Boston University (BU) School of Public Health. I am also a Rafik B. Hariri Junior Faculty Fellow at the Rafik B. Hariri Institute for Computing and Computational Science & Engineering at BU.

I was a postdoctoral research fellow in the Departments of Biostatistics, and Computational Medicine and Bioinformatics, and a Precision Health Scholar at The University of Michigan-Ann Arbor. I obtained my PhD in Statistics from University of Connecticut.

My research interests include Bayesian modeling, variable selection, geometric functional data analysis, spatial statistics and applications to complex-structured biomedical data. My current research is focused on building statistical methods to address relevant questions in different disease contexts, by integrating complex-structured data (imaging, spatial-genomic, geospatial and digital data) from multiple platforms.

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

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  1. Thierry Chekouo, Francesco C. Stingo, Shariq Mohammed, Arvind Rao, Veerabhadran Baladandayuthapani . A Bayesian group selection with compositional responses for analysis of radiologic tumor proportions and their genomic determinants. Annals of Applied Statistics. 2023; 4(17):3013-3034. View Publication
  2. Mohammed S, Kurtek S, Bharath K, Rao A, Baladandayuthapani V. Tumor radiogenomics in gliomas with Bayesian layered variable selection. Med Image Anal. 2023 Dec; 90:102964. PMID: 37797481; PMCID: PMC10653647; DOI: 10.1016/;
  3. Romano MF, Zhou X, Balachandra AR, Jadick MF, Qiu S, Nijhawan DA, Joshi PS, Mohammad S, Lee PH, Smith MJ, Paul AB, Mian AZ, Small JE, Chin SP, Au R, Kolachalama VB. Deep learning for risk-based stratification of cognitively impaired individuals. iScience. 2023 Sep 15; 26(9):107522.View Related Profiles. PMID: 37646016; PMCID: PMC10460987; DOI: 10.1016/j.isci.2023.107522;
  4. Warner E, Lee J, Krishnan S, Wang N, Mohammed S, Srinivasan A, Bapuraj J, Rao A. Low-parameter supervised learning models can discriminate pseudoprogression and true progression in non-perfusion-based MRI. Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul; 2023:1-4. PMID: 38083692
  5. Halder, A., Mohammed, S., Dey, D.K. Bayesian variable selection in double generalized linear Tweedie spatial process models. New England Journal of Statistics and Data Science. 2023; 2(1):187-199. View Publication
  6. Halder, A., Mohammed, S., Chen, K. and Dey D.K. 2022 Proceedings of International E-Conference on Mathematical and Statistical Sciences: A Selçuk Meeting. Spatial risk estimation in Tweedie double generalized linear models. 2022; 62-91. View Publication
  7. Bhattachayya, R., Banerjee, S., Mohammed, S. and Baladandayuthapani, V. Spatial network-based modeling of COVID-19 dynamics: Early pandemic spread in India. Journal of the Indian Statistical Association. 2022.
  8. Sevcan Turk, Nicholas C. Wang, Omer Kitis, Shariq Mohammed, Tianwen Ma, Remy Lobo, John Kim, Sandra Camelo-Piragua, Timothy D. Johnson, Michelle M. Kim, Larry Junck, Toshio Moritani, Ashok Srinivasan, Arvind Rao, Jayapalli R.Bapuraj. Comparative study of radiologists vs machine learning in differentiating biopsy-proven pseudoprogression and true progression in diffuse gliomas. Neuroscience Informatics. 2022; 2(3). View Publication
  9. Panigrahi S, Mohammed S, Rao A, Baladandayuthapani V. Integrative Bayesian models using Post-selective inference: A case study in radiogenomics. Biometrics. 2023 Sep; 79(3):1801-1813. PMID: 35973786; PMCID: PMC9931934; DOI: 10.1111/biom.13740;
  10. Qin A, Lima F, Bell S, Kalemkerian GP, Schneider BJ, Ramnath N, Lew M, Krishnan S, Mohammed S, Rao A, Frankel TL. Cellular engagement and interaction in the tumor microenvironment predict non-response to PD-1/PD-L1 inhibitors in metastatic non-small cell lung cancer. Sci Rep. 2022 May 31; 12(1):9054. PMID: 35641540; PMCID: PMC9156701; DOI: 10.1038/s41598-022-13236-8;
Showing 10 of 24 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 24 publications over 6 distinct years, with a maximum of 6 publications in 2020 and 2022


2022-2025 Boston University: Rafik B. Hariri Junior Faculty Fellow
2019-2021 University of Michigan: Precision Health Scholars Award
Contact for Mentoring:

801 Massachusetts Ave
Boston MA 02118
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