Publications in journals
 Shubhroshekhar Ghosh, Sanjay Chaudhuri, and Ujan Gangopadhyay (2023). Maximum likelihood estimation under constraints: Singularities and random critical points. IEEE Transactions on Information Theory, Vol 69(12), 7976–7997.
 Sanjay, Chaudhuri, Tatsuya, Kubokawa and Shonosuke, Sugasawa. (2022) Covariance based Moment Equations for Improved Variance Component Estimation. Statistics, Vol 56(6), pp 12901318.
 Satarupa Bhattacharjee, Shuting Liao, Debashis Paul, and Sanjay Chaudhuri. (2022) Taming the pandemic by doing the mundane. Ghosh, Aurobindo, Haldar, Amit, and Bahumik, Kalyan (Eds.), Managing Complexity and Covid19: Life, Liberty or the Pursuit of Happiness. Routledge.pp 6282
 Satarupa Bhattacharjee, Shuting Liao, Debashis Paul, and Sanjay Chaudhuri. (2022) Inference on the dynamics of COVID19 in the United States. Scientific Reports, Vol 12(1):2253.
 Tatsuya Kubokawa, Shonosuke Sugasawa, Hiromasa Tamae and Sanjay Chaudhuri. (2021) General Unbiased Estimating Equations for Variance Components in Linear Mixed Models. Japanese Journal of Statistics and Data Science, Vol 4, pp 841–859.
 Sanjay Chaudhuri, and Mark S. Handcock (2018) A Conditional Empirical Likelihood Based Method for Model Parameter Estimation from Complex Survey Datasets. The special J. N. K. Rao felicitation issue, The Society of Statistics, Computer and Application, Vol 16, No 1, pp 245–268.
 Meng Hwee Victor Ong, Sanjay Chaudhuri, and Berwin Turlach. (2018) Edge selection for undirected graphs. Journal of Statistical Computation and Simulation, Vol 88, No 17, pp 3291–3322.
 Sanjay Chaudhuri, Debashis Mondal, and Teng Yin (2017). Hamiltonian Monte Carlo in Bayesian Empirical likelihood computation. Journal of the Royal Statistical Society Series B, Vol 79, Issue 1, pp 293320.
 Tatsuya Kubokawa, Shonosuke Sugasawa, Malay Ghosh, and Sanjay Chaudhuri (2016). Prediction in heteroscedastic nested error regression models with random dispersions. Statistica Sinica, Vol 26, pp 465492.
 Kim Cuc Pham, David J. Nott, Sanjay Chaudhuri (2014), A note on approximating ABCMCMC using flexible classifiers. STAT, Vol 3, Issue 1, pp 218227.
 Sanjay Chaudhuri (2014). Qualitative inequalities for squared partial correlations of a Gaussian random vector. Annals of Institute of Statistical Mathematics, Vol 66, No 2, pp 345367.
 Antar Bandypadhyay and Sanjay Chaudhuri (2014). Variance estimation for tree order restricted normal models. Statistics, Vol 48, Issue 5, pp 11221137.
 Michael D. Perlman and Sanjay Chaudhuri (2012). Reversing the Stein Effect. Statistical Science, Vol 27, No 1, pp 135143.
 Sanjay Chaudhuri and Malay Ghosh (2010). Empirical Likelihood for Small Area Estimation. Biometrika, Vol 98(2), pp 473480.
 Sanjay Chaudhuri and Gui Liu Tan (2010). On qualitative comparison of partial regression coefficients for Gaussian graphical Markov models. in Algebraic Methods in Statistics and Probability II, Contemporary Mathematics, 519, Vianna, Marlos A. G. and Wynn, Henry P., editors, pp 125133.
 Sanjay Chaudhuri, Mark S. Handcock, and Michael Rendall (2008). Generalised linear models incorporating population level information: An empirical likelihood based approach. Journal of the Royal Statistical Society Series B, Vol 70, Part 2, pp 311328.
 Abhijit Kar, Sanjay Chaudhuri, Pratik K. Sen, and Ajoy Kumar Ray (2007). Evaluation of hardness of the interfacial reaction products at the aluminastainless steel brazed interface by modeling of nanoindentation results. Scripta Materalia, Vol 57, pp 881884.
 Sanjay Chaudhuri and Michael D. Perlman (2007) Consistent estimation of the minimum normal mean under the treeorder restriction. Journal of statistical planning and inference, Vol 137, pp 3317 – 3335.
 Sanjay Chaudhuri, Mathias Drton, and Thomas S. Richardson (2007). Estimation of a covariance matrix with zeros. Biometrika, Vol 94(1), pp 199216.
 Sanjay Chaudhuri, Mark S. Handcock, and Michael S. Rendall (2007). A 2step empirical likelihood based approach for combining sample and population data in regression estimation. Proceedings of the ISI 2007.
 Sanjay Chaudhuri and Michael D. Perlman (2006) Two Stepdown Tests for Equality of Covariance Matrices. Linear algebra and its applications, vol 417, pp 4263.
 Sanjay Chaudhuri and Michael D. Perlman (2005). Biases of the maximum likelihood and CohenSackrowitz estimators for the treeorder model. Statistics & Probability Letters, vol 71, pp 267276.
 Sanjay Chaudhuri and Michael D. Perlman (2005). On the Bias and Meansquared Error of Orderrestricted Maximum Likelihood Estimators. Journal of statistical planning and inference, vol 130, pp 229250.
 Michael D. Perlman and Sanjay Chaudhuri (2004).The Role of Reversals in Orderrestricted Inference. The Canadian Journal of Statistics, Vol 32, No 2, pp 193198.
 Sanjay Chaudhuri and Thomas Richardson (2003). Using the structure of dconnecting paths as a qualitative measure of strength of dependence. 19th conference of Uncertainty in Artificial Intelligence. 116–123.
 Krishna Kumar, Sanjay Chaudhuri, and Alaka Das (2002).Quasiperiodic waves at the onset of zeroPrandtlnumber convection with rotation. Physical Review E, Volume 65, 2002.
Technical Reports
 Sanjay Chaudhuri, Mark S. Handcock, and Michael S. Rendall (2010). A Conditional Empirical Likelihood Approach to Combine Sampling Design and Population Level Information. Tech. rep. 03_2010. Department of Statistics and Applied Probability.
 Sanjay Chaudhuri, and Mathias Drton (2003). On the Bias and Meansquared Error of the Sample Minimum and the Maximum Likelihood Estimator for two Ordered Normal Means. Tech. rep. 432. Department of Statistics, University of Washington.
PhD. Thesis
 Sanjay Chaudhuri (2005). Using the structure of dconnecting paths as a qualitative measure of the strength of dependence. PhD thesis. University of Washington.
