Bani K. Mallick

Susan M. Arseven `75 Chair in Data Science and Computational Statistics

University Distinguished Professor

Director, Center for statistical Bioinformatics

Director, Texas A&M TRIPODS Data Science Institute

Texas A&M University

Phone: (979) 845-1275.(office)
FAX: (979) 845-3144.
E-mail: bmallick@stat.tamu.edu
Address: Statistics Department , Texas A&M University , College Station, TX 77843-3143 USA.

Education

• Ph. D., Statistics, University of Connecticut.

Awards and Honors

• Distinguished Alumnus Award, Department of Statistics, UCONN, 2021
• Association of Former students Distinguished Achievement in graduate mentoring, Texas A&M University, 2019
• Fulbright Nehru Distinguished Chair Professor Award, 2017-2018
• Fellow of the American Association for the Advancement of Science, elected in 2013
• Fellow of the Institute of Mathematical Statistics, elected in 2008
• University Distinguished Achievement Award in Research, Texas A&M University, 2006
• Fellow of the American Statistical Association, elected in 2005
• Member of the International Statistical Institute, elected in 1999
• Elected Fellow of the Royal Statistical Society
• Noether Award by University of Connecticut for outstanding performance in graduate study, 1992
• Mahalanobis award by Presidency College for outstanding performance in under graduate study

Editorial Service
Past Editor: Sankhya, B
Past Associate Editor: Journal of the American Statistical association, A&C
Current Associate Editor: SIAM Journal on Uncertainty Quantification
Past Associate Editor: Journal of Computation and Graphical Statistics
Past Associate Editor: Biostatistics

Grants
Funded by multiple NSF, NIH, DOE grants

Course I'm Teaching

Research Interests

• 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

Selected Publications (from 2013)

• Luo, Z., Sang H., Mallick B (2021) ``BAST: Bayesian Additive RegressionSspanning Tree for complex constrained domain'', 35th Conference on Neural Information Processing Systems(NeurIPS 2021)
• Ghosh, R., Mallick, B. and Pourahmadi, M. (2021) ``Bayesian Estimation of C orrelation Matrices of Longitudinal Data'', Bayesian Analysis , 16(3), 1039-1058
• Lei, B., Kirk, T., Bhattacharya, A., Pati, D., Qian, X., Arroyave, R. and Mallick, B. (2021)`` Bayesian optimization with adaptive surrogate models for automated eperimental design'', Nature Computational Materials, 7, 194,https://doi.org/10.1038/s41524-021-00662-x
• Maity, A., Lee, SC, Hu, L, Bell-Pederson, D., Mallick, B. and Roy Sarkar, T. (2021) ``Circadian gene selection for time-to-event phenotype by integrating CNV and RNAseq data'', Chemometrics and Intelligent Laboratory Systems , 212, 104276. PMC8775911
• Luo, Z., Sang, H. and Mallick, B. (2021)`` A Bayesian contiguous partitioning method for learning clustered latent variables'', Journal of Machine Learning Research, 22, 1-52
• Sarkar, A., Pati, D., Mallick, B. and carroll, R. (2021) ``Bayesian Copula Density Deconvolution for Zero- Inflated Data in Nutritional Epidemiology'', Journal of the American Statistical Association , 116, 535, 1075-1087. PMC8654344
• Niu, Y., Pati, D., Mallick, B. (2021) ``Bayesian Graph selection consistency under Model Misspecification", Bernoulli , 27(1), 637-672. PMC8300537
• Geng, Xinbo, Lang Tong, Anirban Bhattacharya, Bani Mallick, and Le Xie. "Probabilistic hosting capacity analysis via bayesian optimization." In 2021 IEEE Power & Energy Society General Meeting (PESGM) , pp. 1-5. IEEE, 2021
• Gangula, R., Arora, M., Lepiz, M., Niu, Y., Mallick, B., Pflugfelder, S., Scott, E., and M.N.V. Ravikumar (2020) “Systemic anti-inflammatory therapy aided by double-headed nanoparticles in a canine model of acute intraocular inflammation”, Science Advances, 6, 10.1126/sciadv.abb7878
• Guha, N., Baladandayuthapani, V., Mallick, B. (2020) ``Quantile Graphical Models: a Bayesian Approach'', Journal of Machine Learning Research, 21, 1-47. PMC8297664
• Lee, SY, Lei, B. and Mallick, B. (2020) `` Estimation of COVID-19 spread curves integrating global data and borrowing information'', PLOS ONE: Infectious Disease , e0236860. https://doi.org/10.1371/journal.pone.0236860
• Payne, R., Guha, N., Ding, Y. and Mallick, B. (2019) ``A conditional Density Estimation Partition model using Logistic Gaussian Processes", Biometrika , 107, 173-190
• Chakraborty, A., Bhattacharya, A., Mallick, B. (2020) ``Bayesian sparse multiple regression for simultaneous rank reduction and variable selection", Biometrika , 107, 205-221
• Maity, A., Lee, S., Mallick, B., Roysarkar, T. (2020) ``Bayesian structural equation modeling in multiple omics data with application to circadian genes'', Bioinformatics , 36, 3951-3958
• Maity, A. K., Bhattacharyya, A., Mallick, B. K., and Baladandayuthapani, V. (2020) ``Data Integration and Variable Selection for Pan-Cancer Survival Prediction using Protein Expressions", Biometrics , 76, 316-325
• Maity, A. K., Carroll, R. J., and Mallick, B. K. (2019) ``Integration of Survival and Binary Data for Variable Selection and Prediction: A Bayesian Approach", Journal of the Royal Statistical Society: Series C, 68, 1577-1595
• Sarkar, T. R., Maity, A. K., Niu, Y., and Mallick, B. K. (2019) ``Multiple Omics Data Integration to Identify Long Noncoding RNA Responsible for Breast Cancer Related Mortality", Cancer Informatics, To Appear
• Das, N., Ghosh, R., Guha, N., Bhattacharya, R. And Mallick, B. (2019) ``Optimal Transport based tracking of space objects in cylindrical manifolds", 1-25, The Journal of the Astronautical Sciences
• Kundu, S., Mallick, B.K., and Baladandayuthapani, V. (2019)``Efficient Bayesian Regularization for Graphical Model Selection", Bayesian Analysis, 14,449-476
• Song, J. and Mallick, B. (2018) ``Hierarchical Bayesian Models for predicting spatially correlated data, Statistics , 53, 196-209.
• Zoh, R., Sarkar, A., R. J. Carroll, and Mallick, B. K. (2018) `` A powerful Bayesian test for equality of means in high dimensions'', Journal of the American Statistical Association, 113,524,1733-1741.
• Sarkar, A., Pati, D., Mallick, B. K., and Carroll, R. J. (2018) `` Bayesian semiparametric multivariate density deconvolution'', Journal of American Statistical Association, 113, 521, 401-416.
• Kundu, S., Cheng, Y., Shin, M., Manyam, G., Mallick, B.K., Baladandayuthapani, V. , (2018), Bayesian Variable Selection with Structure Learning: Applications to Integrative Genomics, PLOS One, 13(7): e0195070.
• Payne, R and Mallick, B. (2018) "Two-stage Metropolis-Hastings for Tall Data", Journal of Classification, Volume 35, 1, 29-51.
• Yang, K., Guha, N., Efendiev, E. and Mallick, B. (2017) ``Bayesian and Variational Bayes approaches for flows in heterogeneous random media ," Journal of Computational Physics 345, 275-293.
• Chakraborty, A., Bingham, D., Dhavala, S., Kuranz, C., Drake, P., Grosskopf, M., Rutter, E., Holloway, J., McClarren, R and Mallick, B. (2016) ``Emulation of Numerical Models with over-specified basis functions'', Technometrics. 59, 153-164
• Bhattacharya A, Chakraborty A and Mallick, B. (2016) ``Fast sampling with Gaussian scale mixture priors in high-dimensional regression'', Biometrika 4, 985-991.
• Zoh, R., Mallick, B., Ivanov, I., Baladandayuthapani, V., Chapkin, R. and Carroll, R. (2016) ``PCAN: Probabilistic Correlation analysis of two Non-Normal Data sets'' Biometrics 72, 1358-1368.
• Guha, N., Wu,X., Efendiev, Y, Jin, B, and Mallick, B. (2015) ``A Variational approach for inverse problems with skew-t error distributions,'', Journal of Computational Physics 301, 377-393.
• Baladandydayuthapani, V., Talluri, R., Ji, Y., Coombes, K., Hennessy, B., Davies, M. and Mallick, B. (2014) ``Bayesian sparse graphical models for classification with application to protein expression data'', Annals of Applied Statistics 8, 1443-1468.
• B. A Konomi, H. Sang, B. K Mallick (2014) `` Adaptive Bayesian nonstationary modeling for large spatial datasets using covariance approximations", Journal of Computational and Graphical Statistics 23, 802-829.
• Sarkar, A., Mallick, B. and carroll, R. (2014), ``Bayesian semiparametric regression in the presence of conditionally heteroscedastic measurement and regression error", Biometrics 70, 823-834.
• Sarkar, A., Mallick, B, Staudenmayer, J., Pati, D. and Carroll, R (2014), `` Bayesian semiparametric density deconvolution in the presence of conditionally heteroscedastic measurement errors'' Journal of Computational and Graphical Statistics 24,1101-1125.
• Mondal, A., Mallick, B., Efendiev, Y. and Datta-Gupta, A. (2014) ````Bayesian uncertainty quantification for subsurface inversion using multiscale hierarchical model", Technometrics 56, 3, 381-392.
• Zhang, L., Baladandayuthapani, V., Mallick, B., Manyam, G., Thompson, P., Bondy, M. and K. Do (2014) ``Bayesian hierarchical structured variable selection with application to molecular inversion probe studies in breast cancer'', Journal of the Royal Statistical Society, C 63, 595-620.
• Xun, X., Cao, J., Mallick, B., Carroll, R. and Maity, A. (2013) ``Parameter estimation of partial differential equation model'', Journal of the American Statistical Association. 108,1009-1020.
• Ryu, D., Liang, F. and Mallick, B. (2013) ``A Dynamically particle filter with radial basis function networks for sea surface temperature modeling'', Journal of the American Statistical Association. 108, 111-123.
• Chakraborty, A., Mallick, B., McClareren, R., Kuranz, C. and Drake, P. (2013) ``Spline based emulators for radiative shock experiments with measurement error'', Journal of the American Statistical Association. 108, 411-428.
• Konomoi, A, Park, C., Huang, J., Huitink, D., Kundu, S., Liang, H. and Ding, Y., Mallick, B. (2013) ``Bayesian modeling for analyzing the morphology of gold nanoparticles'', Annals of Applied Statistics.7,640-668.
• Bhadra, A. and Mallick, B. (2013) , ``Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis", Biometrics, 69, 444-457.
• Zhao, K., Valle, D., Popescu, S., Zhang, X. & Mallick, B. (2013) , ``Hyperspectral RemoteSensing of Plant Biochemistry using Bayesian Model Averaging with Variable and Band Selection", Remote sensing and environment, 132,102-119.

Software