Siuli Mukhopadhyay

A multi-region discrete time chain binomial model for infectious disease transmission (2025) Sinha, P. Niphadkar, S. and Mukhopadhyay, S., preprint

An age-stratified mathematical model to inform optimal measles vaccination strategies (2025) Ghosh, S. Ghosh, I. and Mukhopadhyay, S., in revision

Estimation of Undetected Covid-19 Infections in India, (2020) Mukhopadhyay, S. and Chakraborty, D.

Efficient designs for multivariate crossover trials (2025) Niphadkar, S. and  Mukhopadhyay, S., Metrika, https://doi.org/10.1007/s00184-025-01003-4

Sample size determinations in four-level longitudinal cluster randomized trials with random slope (2025) Majumder, P., Mukhopadhyay, S., Wang, B., Ghosh, S., Statistical Methods in Medical Research 34(4) 751-762. doi:10.1177/09622802251321996

Likelihood-based Inference for Skewed Responses in a Crossover Trial Setup (2025) Pareek, S., Das, K., Mukhopadhyay, S., Communication in Statistics -  Simulation and Computation 1-24 https://doi.org/10.1080/03610918.2025.2453469

Universally Optimal Multivariate Crossover Designs (2024) Niphadkar, S. and  Mukhopadhyay, S., Sankhya B 86: 586-603

G-optimal grid designs for kriging models (2024) Dasgupta, S., Mukhopadhyay, S., Keith, J. Scandinavian Journal of Statistics. 51:1061–1085 

Pareek, S., Das, K., Mukhopadhyay, S. (2023), Likelihood based missing data analysis in multivariate crossover trials  Brazilian Journal of Probability and Statistics 37(2): 329-350. DOI: 10.1214/23-BJPS570

Dasgupta, S., Mukhopadhyay, S., Keith, J. (2022), Designs for some bivariate cokriging models, Journal of Statistical Planning and Inference, 221, pp. 9-28

Ghosh, S., Mukhopadhyay, S., Mazumder, P., Wang, B. (2022), Statistical power and sample size requirements to detect an intervention by time interaction in four level longitudinal cluster randomized trials, Statistics in Medicine, 41(14):2542-2556

Sathish, V, Mukhopadhyay, S., Tiwari, R.  (2022) Autoregressive and Moving Average Models for Zero-Inflated Count Time Series, Statistica Neerlandica, 76, pp. 190-218.

Singh, S.P., Mukhopadhyay, S. and Raj, H. (2021) Min–Max Crossover Designs for Generalized Linear Models, Statistics and Computing 31, DOI: 10.1007/s11222-021-10029-3

Khetan, M., Pareek, S., Mukhopadhyay, S. and Das, K. (2021) Clustering gene expression time series data embedded in a non-parametric setup, Journal of Statistical Research (special issue) 55, pp. 207-224

Mukhopadhyay, S., Singh, S.P, and Singh, A (2021) Locally Optimal Binary Crossover Designs. Statistics and Applications Special Issue "Contributions to Combinatorics, Design of Experiments, Linear Algebra and Related Areas" in the memory of Late Professor Aloke Dey, 19, pp. 223-246 

Das, I., Mukhopadhyay, S. (2019): Robust Designs for Multinomial Models. Communications in Statistics - Simulation and Computation 48, pp. 2998-3021

Singh, R., Mukhopadhyay, S. (2019): Exact Bayesian Designs for Count Time Series. Computational Statistics and Data Analysis 134, pp. 157-170 

Mukhopadhyay, S., Sathish, V. (2019): Predictive Likelihood for Coherent Forecasting of Count Time Series. Journal of Forecasting 38, pp. 222-235 

Singh, S.P., Mukhopadhyay, S. (2016): Bayesian Crossover Designs for Generalized Linear Models. Computational Statistics and Data Analysis 104 pp. 35-50

Singh, S.P., Mukhopadhyay, S. (2016): Bayesian Optimal Cluster Designs. Statistical Methodology 32 pp. 36-52

Singh, S.P.,  Mukhopadhyay, S. and Roy, A. (2015): Comparison of Three Level Cluster Randomized Trials Using Quantile Dispersion Graphs. Journal of Applied Statistics 42 pp.1792-1812

Khuri, A.I., Mukhopadhyay, S. and Khuri, M.A. (2015): Approximating moments of continuous functions of random variables using Bernstein polynomials. Statistical Methodology 24 pp. 37-51

Das, I. Aggarwal, M. and Mukhopadhyay, S. (2015): Robust Designs in Generalized Linear Models: A Quantile Dispersion Graphs Approach. Special Issue Simulation and Computation in Statistical Inference in Communications in Statistics - Simulation and Computation 44 pp. 2348-2370

Das, I., Mukhopadhyay, S. (2014): On generalized multinomial models and joint percentile estimation. Journal of Statistical Planning and Inference 145 pp. 190-203

Das, I., Mukhopadhyay, S. and Xu, H. (2013): Individualized Dosing for Multiple Ordered Groups of Patients. Journal of Statistical Theory and Practice 7 pp. 95-106

Mukhopadhyay, S., Khuri, A.I. (2012): Comparison of Designs for Generalized Linear Models under Model Misspecification. Statistical Methodology 9 pp. 285-304

Mukhopadhyay, S., Chakraborty, D. (2011): A Computational Algorithm for Selecting Robust Designs in Safety and Quality Critical Processes. Sankhya B 73 pp. 105-122

Khuri, A.I., Mukhopadhyay, S. (2010): Response Surface Methodology. Wiley Interdisciplinary Reviews: Computational Statistics 2(2) pp. 128-149

Mukhopadhyay, S., George, V. and Xu, H. (2010): Variable Selection Method for Quantitative Trait Analysis based on Parallel Genetic Algorithm. Annals of Human Genetics 74(1) pp. 88-96(9)

Mukhopadhyay, S. and Looney, S.W. (2009): Quantile Dispersion Graphs to Compare the Efficiencies of Cluster Randomized Designs. Journal of Applied Statistics 36(11) pp. 1293-1305

Mukhopadhyay, S. and Khuri, A.I. (2008): A New Graphical Approach for Comparing Response Surface Designs on the basis of the Mean Squared Error of Prediction Criterion. Statistics and Applications 6 (Nos.1 & 2), 293-324

Mukhopadhyay, S. and Khuri, A.I. (2008): Optimization in a Multivariate Generalized Linear Model Situation. Computational Statistics and Data Analysis 52(10) pp. 4625-4634

Mukhopadhyay, S. and Khuri, A.I. (2008): Comparison of Designs for Multivariate Generalized Linear Models. Journal of Statistical Planning and Inference 138(1) pp. 169-183

Mukhopadhyay, S. and Khuri, A.I. (2007): Bias in Multivariate Generalized Linear Models. Calcutta Statistical Association Bulletin 59 pp. 87-105

Latent Graphical Models of Multivariate Disease Count Time Series (2025) Sathish, V., Chakraborty, D. and Mukhopadhyay, S. IEEE Transactions on Signal and Information Processing over Networks

A systematic review and modelling insights of factors impacting measles vaccine effectiveness, efficacy and immunogenicity (2025) Ghosh, S., Kappara, D., Majumder, N., Nath-Sain, S. and Mukhopadhyay, S., Discover Viruses

Estimation of time-varying recovery and death rates from epidemiological data: A new approach (2025) by Ghosh , S., Dhar, S. S., Banerjee, M. Mukhopadhyay, S., Mathematical Biosciences 387 September 2025, 109479

A Historical Perspective of Malaria Policy and Control in India (2024)  Sam, A. K., Karmakar, S., Mukhopadhyay, S. and Phuleria, H. C., International Society for Infectious Diseases IJID Regions journal 12 (2024) 100428

Guha,  S.K., Sarkar, I., Patgaonkar, M., Banerjee, S., Mukhopadhyay, S., Sharma, S., Pathak, S. and Vaidya, V.A. (2020) A history of juvenile mild malaria exacerbates chronic stress-evoked anxiety-like behaviour, neuroinflammation, and decline of adult hippocampal neurogenesis in mice. Journal of Neuroimmunology 348

Mukhopadhyay, S.,  Tiwari, R., Shetty, P., Gogtay, N.J., Thatte, U.M. (2019): Modelling and Forecasting Indian Malaria Incidence Using Generalized Time Series Models. Communications in Statistics - Case Studies and Data Analysis 5, pp. 111-120 

Mukhopadhyay, S., Das, I. and Das, K. (2012): Selection of a Stroke Risk Model Based on Transcranial Doppler Ultrasound Velocity. Journal of Applied Statistics 39 pp. 2699-2712

Khona, D.K., Rao, V.G., Motiwalla, M.J., Varma, S., Kashyap, A.R., Das, K., Shirolikar, S., Borde, L., Dharmadhikari, J.A., Dharmadhikari, A.K., Mukhopadhyay, S., Mathur, D. and D Souza, J.S (2012): Anomalies in the Motion Dynamics of Long Flagella Mutants of Chlamydomonas Reinhardtii. Journal of Biological Physics 39(1) pp. 1-14

Abreu, A., Loza, M.A., Elias, A., Mukhopadhyay, S., Looney, S. and Rueggeberg, F. (2009). Tensile Bond Strength of an Adhesive Resin Cement to Different Alloys having Various Surface Treatments. The Journal of Prosthetic Dentistry 101(2) pp. 107-118

Abreu, A., Loza, M.A., Elias, A., Mukhopadhyay, S. and Rueggeberg, F. (2007): Effect of Metal Type and Surface Treatment on In Vitro Tensile Strength of Copings Cemented to Minimally Retentive Preparations.The Journal of Prosthetic Dentistry 98(3) pp. 199-207

Niphadkar, S. and  Mukhopadhyay, S., (2025) Studying Optimal Designs for Multivariate Crossover Trials. In the book-volume ‘Linear Algebra, Matrices, and their Applications’ dedicated to ICLAA 2023 published by AMS Contemporary Mathematics

Sam, A. K., Patil, S., Mukhopadhyay, S., Phuleria, H.C. (2024) Epidemiological aspects of outdoor air pollution— link between air pollution and COVID-19. In Health and Environmental Effects of Ambient Air Pollution (Dehghani, M.D., Karri, R.R., Vera, T., Hassan, S.K.M., ed) Chapter 7, Academic Press

Khuri, A.I. and Mukhopadhyay, S. (2015): Response Surface Experiments and Designs. In Handbook of Design and Analysis of Experiments (D. Bingham, A. Dean, M. Morris and J. Stufken, ed) Chapter 5, Chapman & Hall/CRC

Mukhopadhyay, S. and Singh, S. P. (2015): “D­-optimal Multinomial Designs”, In “Statistical and Mathematical Sciences and their Applications”, Chapter 4, Narosa Publication, India

Khuri, A.I. and Mukhopadhyay, S. (2006): GLM Designs: The Dependence on Unknown Parameters Dilemma. In Response Surface Methodology and Related Topics (A.I. Khuri, ed) Chapter-9 pp. 203-223, World Scientific, Singapore