| Social media data and post-disaster recovery M Jamali, A Nejat, S Ghosh, F Jin, G Cao International Journal of Information Management 44, 25-37, 2019 | 147 | 2019 |
| Dual impacts of climate change: forest migration and turnover through life history K Zhu, CW Woodall, S Ghosh, AE Gelfand, JS Clark Global change biology 20 (1), 251-264, 2014 | 142 | 2014 |
| Representation of features as images with neighborhood dependencies for compatibility with convolutional neural networks O Bazgir, R Zhang, SR Dhruba, R Rahman, S Ghosh, R Pal Nature communications 11 (1), 4391, 2020 | 127 | 2020 |
| Heterogeneity aware random forest for drug sensitivity prediction R Rahman, K Matlock, S Ghosh, R Pal Scientific reports 7 (1), 11347, 2017 | 79 | 2017 |
| A generalized linear mixed model for longitudinal binary data with a marginal logit link function M Parzen, S Ghosh, S Lipsitz, D Sinha, GM Fitzmaurice, BK Mallick, ... The annals of applied statistics 5 (1), 449, 2011 | 74 | 2011 |
| Functional random forest with applications in dose-response predictions R Rahman, SR Dhruba, S Ghosh, R Pal Scientific reports 9 (1), 1628, 2019 | 73 | 2019 |
| LASSO model of postdisaster housing recovery: Case study of Hurricane Sandy A Nejat, S Ghosh Natural Hazards Review 17 (3), 04016007, 2016 | 66 | 2016 |
| A hierarchical Bayesian spatio‐temporal model for extreme precipitation events S Ghosh, BK Mallick Environmetrics 22 (2), 192-204, 2011 | 66 | 2011 |
| Investigation of model stacking for drug sensitivity prediction K Matlock, C De Niz, R Rahman, S Ghosh, R Pal BMC bioinformatics 19, 21-33, 2018 | 62 | 2018 |
| A copula based approach for design of multivariate random forests for drug sensitivity prediction S Haider, R Rahman, S Ghosh, R Pal PloS one 10 (12), e0144490, 2015 | 46 | 2015 |
| Application of transfer learning for cancer drug sensitivity prediction SR Dhruba, R Rahman, K Matlock, S Ghosh, R Pal BMC bioinformatics 19, 51-63, 2018 | 42 | 2018 |
| Inference for size demography from point pattern data using integral projection models S Ghosh, AE Gelfand, JS Clark Journal of agricultural, biological, and environmental statistics 17, 641-677, 2012 | 34 | 2012 |
| A multivariate regression approach toward prioritizing BIM adoption barriers in the Ethiopian construction industry S Alemayehu, A Nejat, T Ghebrab, S Ghosh Engineering, Construction and Architectural Management 29 (7), 2635-2664, 2022 | 29 | 2022 |
| Social media data and housing recovery following extreme natural hazards M Jamali, A Nejat, S Moradi, S Ghosh, G Cao, F Jin International Journal of Disaster Risk Reduction 51, 101788, 2020 | 29 | 2020 |
| The k-ZIG: flexible modeling for zero-inflated counts S Ghosh, AE Gelfand, K Zhu, JS Clark Biometrics 68 (3), 878-885, 2012 | 28 | 2012 |
| Design of probabilistic random forests with applications to anticancer drug sensitivity prediction R Rahman, S Haider, S Ghosh, R Pal Cancer informatics 14, CIN. S30794, 2015 | 24 | 2015 |
| Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma NE Berlow, R Rikhi, M Geltzeiler, J Abraham, MN Svalina, LE Davis, ... BMC cancer 19, 1-23, 2019 | 22 | 2019 |
| Attaching uncertainty to deterministic spatial interpolations S Ghosh, AE Gelfand, T Mølhave Statistical Methodology 9 (1-2), 251-264, 2012 | 21 | 2012 |
| Drivers of post-disaster relocations: The case of Moore and Hattiesburg tornados J Mayer, S Moradi, A Nejat, S Ghosh, Z Cong, D Liang International journal of disaster risk reduction 49, 101643, 2020 | 20 | 2020 |
| A spatially explicit model of postdisaster housing recovery A Nejat, RJ Javid, S Ghosh, S Moradi Computer‐Aided Civil and Infrastructure Engineering 35 (2), 150-161, 2020 | 20 | 2020 |
