Bani
K. Mallick
Susan M. Arseven `75 Chair in Data Science and Computational
Statistics
University
Distinguished Professor
Office: 401B
Blocker Building.
Hours: TBA
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
Awards and Honors
· Palmetto Lecture, University of South
Carolina, Spring, 2023.
· 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
STAT652 Course Description
STAT633 Course
Description
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
Resume
Current
Selected
Publications (from 2013)
- Luo, Z., Sang, H. and Mallick, B.
(2023) ``A Nonstationary soft partitioned Gaussian process model via
random spanning trees'', Journal of the American Statistical
Association, To Appear.
- Niu, Y.,
Ni, Y., Pati, D. and Mallick, B. (2023) ``Covariate-Assisted Bayesian
Graph Learning for Heterogeneous Data'', Journal of the American
Statistical Association, To Appear.
- Mohseni, P.,
Duffield, N., Mallick, B. and Hasanzadeh (2023)
``Adaptive Conditional Quantile Neural Processes'', The Conference on
Uncertainty in Artificial Intelligence (UAI), To appear.
- Lee, K., Zhao, P.,
Bhattacharya, A., Mallick, B. and Xie, L. (2023)
``An Active Learning-based Approach for Hosting Capacity Analysis in
Distribution Systems'', IEEE
Transactions on Smart Grid, To appear.
- Lei, B., Xu, D., Zhang, R.,
Mallick, B. (2023) ``Calibrating the Rigged Lottery: Making All Tickets
Reliable'', International Conference on Learning Representations (ICLR).
- Luo, Z., Sang H., Mallick B
(2021) ``BAST: Bayesian Additive Regression spanning 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 inflammationâ€, 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
· 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. PCANCode
· 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., NY.
- Nonlinear
Estimation and Classification, Springer.
- 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)
Postdoctorate Fellows
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)