Bani K. Mallick
Susan M. Arseven `75 Chair in Data Science and Computational Statistics
University Distinguished Professor
Office: 401B Blocker Building.
Phone: (979) 845-1275.(office)
FAX: (979) 845-3144.
Statistics Department , Texas
A&M University ,
College Station, TX 77843-3143 USA.
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
under graduate study
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
Funded by multiple NSF, NIH, DOE grants
Course I'm Teaching
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- Bayesian hierarchical Modeling
- Nonparametric Regression and classification
- 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.
The R code for implemeting Probabilistic correlation calculation for count data in the paper 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.
The MATLAB code for implemnting the algorithm proposed in Bhattacharya, A., Chakraborty, A. and Mallick, B. (2015). Fast samppling with Gaussian scale mixture priors in high-dimensional regression. Biometrika 4, 985-991. [arxiv] [Matlab implementation]
BayesME: an R package for nonparametric density deconvolution and nonparametric regression (not yet implemented) allowing for heteroscadastic measurement error and heteroscedastic regression error .Based on Sarkar, A., Mallick, B. K., Staudenmayer, J., Pati, D. and Carroll, R. J. (2014). Bayesian semiparametric density deconvolution in the presence of conditionally heteroscedastic measurement errors. Journal of Computational and Graphical Statistics, 25, 1101-1125 and Sarkar, A., Mallick, B. K. and Carroll, R. J. (2014). Bayesian semiparametric regression in the presence of conditionally heteroscedastic measurement and regression errors. Biometrics, 70, 823-834. Packages mvtnorm and msm are required.
The books I have written
Bayesian Analysis of gene expression Data, Wiley.
Bayesian methods for nonlinear classification and
Regression, Wiley, NY.
The books I have edited
- Generalized Linear Models: A Bayesian perspective,
Marcel Dekker inc.,
- Nonlinear Estimation and Classification,
- Large-scale inverse problems and quantification of
uncertainty, Wiley, NY.
- Dey, D., Ghosh, S. and Mallick, B. Bayesian Modeling Issues in Bioinformatics and Biostatistics, Chapman and Hall/CRC .
Former Ph.D Students
D. Denison, (Winner of the Savage award, 1998, as the best Bayesian Thesis) (Lecturer, Imperial College, London, UK)
C. Holmes (Professor, Oxford University, U.K)
H. M. Kim. ( Professor, Konkuk Univeresity Korea)
N. Rose (IBM)
Kyeong Eun Lee. (Kyungpook University, Korea)
Joon Jin Song. ( Associate Professor, Baylor University)
Duchwan Ryu (Associate Professor, Northern Illinois University )
K Bae. Graduated (Chief Statistician, Penn Cancer center)
Veera Baladandayuthapani [with Raymond Carroll] ( Professor, University of Michigan)
I.S. Chang [with James Calvin] (Glaxco-SmithKline)
S. Ray (Marc)
X.S. Wang (Associate Professor, University of Texas)
D. Gold (Assistant Professor, SUNY Buffalo)
Souparno Ghosh (Associate Professor, University of Nebraska)
Rajesh Talluri (Assistant Professor, University of Mississippi)
S. Dhavala (Dow Agroscience)
Alex Konomoi[joint with H. Sang] (Associate Professor, University of Cincinnati)
B. Hartman (Associate Professor, BYU)
A. Mondal (Associate Professor, Case Western Reserve)
X.Xun [Joint with R Carroll] (Novartis)
Lin Zhang [Joint with Veera] (Assistant Professor, University of Minnesota)
Abhra Sarkar [joint with R Carroll] (Assistant Professor, UT Austin)
Antik Chakraborty [joint with A Bhattacharya] (Assistant Professor, Purdue)
Richard Payne (Eli Lilly)
Yabo Niu [Joint with D Pati] (Assistant Professor, University of Houston)
R. Ghosh [joint with M Pourahmadi] (Assistant Professor, Bowling Green State University)
Se Yoon Lee (Johnson & Johnson)
Zhao Tang Luo [Joint with H Sang] (Apple)
W. Fu ( Associate Professor, Michigan State University)
Sima Chao (Research Scientist, Texas A&M)
Ivan Zorych (Columbia University)
S. Dey (SAS)
Anindya Bhadra (Associate Professor, Purdue University)
Avishek Chakraborty (Associate Professor, University of Arkansas)
Supratik Kundu(Associate Professor, MD Anderson)
R Zoe(Assistant Professor, Indiana University, Bloomington)
Nilabja Guha (Assistant Professor, UMass)
Arnab Maity (Marc)
Sutanoy Dasgupta (Visiting Assistant Professor, Texas A&M)
Peng Zhao (Current)
Prateek Jaiswal (Current)
- <!a href="633/Lecs/Lec0.pdf">Lecture-0
Syllabus:             <!a href="633/syllabus1.pdf"> here