Mallick, Bani individual record
Distinguished Professor

Bayesian hierarchical Modeling, Nonparametric Regression and classification, Bioinformatics, Spatio-temporal Modeling, Machine learning, Functional Data analysis, Bayesian nonparametrics, Petroleum reservoir characterization, Uncertainty analysis of Computer Model outputs

education and training
selected publications
Academic Articles114
  • Biegler, L., Biros, G., Ghattas, O., Heinkenschloss, M., Keyes, D., Mallick, B., ... Willcox, K. (2010). Large-Scale Inverse Problems and Quantification of Uncertainty. Wiley.
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  • Mallick, B. K., Gold, D. L., & Baladandayuthapani, V. (2009). Bayesian Analysis of Gene Expression Data. John Wiley & Sons, Ltd.
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  • Baladandayuthapani, V., Ray, S., & Mallick, B. K. (2005). Bayesian Methods for DNA Microarray Data Analysis. Elsevier.
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  • Baladandayuthapan, V., Wang, X., Mallick, B. K., & Do, K. (2015). Bayesian Functional Mixed Models for Survival Responses with Application to Prostate Cancer. Chen, Z., Liu, A., Qu, Y., Tang, L., Ting, N., & Tsong, Y. (Eds.), Applied Statistics in Biomedicine and Clinical Trials Design. (pp. 35-59). Springer International Publishing.
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  • Richardson, S., Bottolo, L., & Rosenthal, J. S. (2011). Bayesian Models for Sparse Regression Analysis of High Dimensional Data*. Bayesian Statistics 9. (pp. 539-568). Oxford University Press.
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  • Maity, A., & Mallick, B. K. (2010). In-Vitro to In-Vivo Factor Profiling in Expression Genomics Machines. Chapman & Hall/CRC Biostatistics Series. (pp. 317-342). Chapman and Hall/CRC.
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  • Efendiev, Y., Datta-Gupta, A., Hwang, K., Ma, X., & Mallick, B. (2010). Bayesian Partition Models for Subsurface Characterization. Large-Scale Inverse Problems and Quantification of Uncertainty. (pp. 107-122). John Wiley & Sons, Ltd.
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  • Mallick, B., Ghosh, D., & Ghosh, M. (2008). Bayesian Machine-Learning Methods for Tumor Classification Using Gene Expression Data. Introduction to Machine Learning and Bioinformatics. (pp. 303-325). Chapman and Hall/CRC.
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Conference Papers4
chaired theses and dissertations
First Name
Last Name
mailing address
Texas A&M University; Department Of Statistics; 3143 TAMU
College Station, TX 77843-3143