Faculty Directory A to Z

• Markov chain Monte Carlo, Bayesian Methodology, Statistical Methodology on Compact Manifolds, Modelling Directional Data, Causal Inference, Analysis of Neuroimaging Data, Regression Analysis.

• Assistant Professor:
  • Operations Management, Quantitative Methods and Information Systems, Indian Institute Of Management–Udaipur. (2022 May - Present)
  • Department of Biostatistics and Bioinformatics, University of Louisville (2017 January - April 2022)
• Postdoctoral fellow: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University (2015 August - 2016 December)
• Affiliate: Center for Biomedical Imaging Statistics (2015 August - Present)

• Recipient of the Kenneth and Janet Keene Endowed Dissertation Fellowship award in the Mathematical Sciences, Collage of Liberal Arts and Science, University of Florida.
• Recipient of Travel Grant Award for attending the conference ICOSDA 2019.
• Recipient of Travel Grant Award for attending the conference Conference at the Cleveland Clinic.
• Nominated for Faculty Favorites Award in the Year 2018-2019, University of Louisville.
• Recipient of University scholarship at Indian Statistical Institute, Kolkata.

• Pal, S. and Gaskins, J., "Modified Polya-Gamma Data Augmentation for Bayesian Analysis of Directional Data.", 2022, Journal of Statistical Computation and Simulation, to appear.
• Bhattacharyya. A., Pal, S., Mitra, R. and Shesh, N. R., "Applications of Bayesian Shrinkage Prior Models in Clinical Research Data with Categorical Responses", 2022, BMC Medical Research Methodology, to appear.
• Bhattachariya, S., Khare, K. and Pal, S., "Geometric Ergodicity of Gibbs Samplers for the Horseshoe and its Regularized Variants", 2022, Electronic Journal of Statistics, Volume 16, pages 1–57.
• Sun, J., Maying, K., Pal, S., "The Modified-Half-Normal distribution: properties and efficient sampling scheme.", 2021, Communication in Statistics: Theory and Methods, to appear.
• Wu, B., Pal, S., Kang. J and Guo, Y. "Distributional Independent Component Analysis for Diverse Neuroimaging Modalities", 2021, Biometrics, to appear.
• Pal, S., Sengupta, S., , Mitra R., , and Banerjee, A. , "Conjugate Priors and Posterior Inference for the Matrix Langevin Distribution on the Stiefel Manifold",Bayesian Analysis, Volume 15, Number 3 (2020), 871-908
• Khare, K., Pal, S. and Su, Z., "A Bayesian approach for Envelope models", 2017, The Annals of Statistics, 45(1), 196-222.
• Pal, S. and Khare, K. and Hobert, J.P., "A trace class Gibbs sampler for Bayesian inference with generalized double Pareto shrinkage priors", 2017, Scandinavian Journal of Statistics, 44(2), 307-323.
• Pal, S., Khare, K. and Hobert, J.P., "Improving the data augmentation algorithm in the two-block setup", 2015, Journal of Computational and Graphical Statistics, Volume 24, Issue 4, 2015.
• Pal, S. and Khare, K., "Geometric ergodicity for Bayesian shrinkage models", 2014, Electronic Journal of Statistics 8, 604-645.
• Mukherjee, A., Williams, D.A., Wheeler, G.S., Cuda, J.P., Pal, S. and Overholt, W. A., "Brazilian peppertree (Schinus terebinthifolius) in Florida and South America: evidence of a possible niche shift driven by hybridization", 2012, Biological Invasions, Volume 14, Issue 7, pp 1415-1430.

• Sengupta, S., Pal, S., Mitra, Guo, Y., and Beneerjee, A. , A Bayesian Mixture Model for Clustering on the Stiefel Manifold.
• John, C., Pal, S. and Kong, M. , Unified Bayesian Model for Propensity Score and the Causal Parameter Estimation in Observational Studies.

• Sun, J., Pal, S., Duncan, S., Kong. M., Directed Acyclic Graph Assisted Methods For Estimating Average Treatment Effect.
• Kulkarni, S., Gaskins, J., Pal, S. , A Bayesian Approach for Joint Estimation for Sparse Canonical Correlation and Graphical Models.
• Kulkarni, S., Pal, S., Efficient Bayesian Methods for Clustering directional data with application to Diffusion Tensors Imaging Data.

• Data Augmentation Algorithms for Bayesian Analysis of Directional Data, UpStat2022, University of Buffalo, New York Statistics Conference, 2022.
• Data Augmentation Algorithms for Bayesian Analysis of Directional Data, University of Kentucky, 2020.
• Conjugate Priors and Posterior Inference for the Matrix Langevin Distribution on the Stiefel Manifold, 2019, THE 3RD international Conference on Statistical Distributions and Application (ICOSDA 2019), Eberhard Conference Center, Grand Rapids, Michigan, USA, October, 2019.
• Conjugate Priors and Posterior Inference for the Matrix Langevin Distribution on the Stiefel Manifold, Southern Regional Council on Statistics, 2019.
• Conjugate Priors and Posterior Inference for the Matrix Langevin Distribution on the Stiefel Manifold, 2018, Colloquium at the Department of Statistics, Indiana University, Bloomington, Indiana.
• A Bayesian Framework for Modeling Data on the Stiefel Manifold, IISA 2018, Florida, 2018.
• A Bayesian Framework for Modeling Data on the Stiefel Manifold, Mathematics Colloquium, University of Louisville, 2018.
• Data Augmentation Algorithms for Bayesian Analysis of Directional Data, University of Louisville, Biostatistics Department Seminar, 2018.
• A Bayesian Mixture Model for clustering on the Stiefel Manifold with an application to Neuroimaging DTI data, 2017, North Shore Research Institute, 2650 Ridge Ave, Evanston, Illinois.
• A Bayesian Mixture Model for Clustering on the Stiefel Manifold, Joint Statistical Meetings, 2017, Baltimore.
• Distributional ICA: A new approach for analyzing neuroimaging data, ICSA Applied Statistics Symposium in Chicago , 2017.
• A Distributional ICA model for decomposing multimodal neuroimaging, Statistical Methods in Imaging Conference, University of Pittsburgh, 2017,.
• Challenges and Advances on Big Data in Neuroimaging, Cleveland Clinic, 2016, poster on "Distributional ICA: A new approach for analyzing neuroimaging data.".
• ASA Florida chapter meeting 2014, poster on “Scale invariant Principal component analysis”.
• The Georgia Statistics Day 2015, poster on “ A Bayesian Approach for Envelope Models”,
• The Calcutta Statistical Triennial, 2006, presentation on “Optimizing food production using a time dependent loss function”, Calcutta University, Kolkata.

University of Louisville, Louisville, Kentucky USA

Instructor

• Fall 2017, Fall 2018, Fall 2019, Fall 2020: PHST 781 - Advanced Linear models.
• Spring 2017, Fall 2018: PHST 780 - Advanced non-parametric Statistics.
• Fall 2019: PHST 762 - Advanced Statistical Inference.
• Fall 2020 : PHST 680- Biostatistical Methods
• Fall 2020 : PHST 310- Applied Regression Analysis
• Spring 2019: PHST 650 - Advanced topics in statistics: Structural Equation modeling
• Fall 2017, Spring 2018, Fall 2018, Spring 2018: PHST 602 - Bio statistics Seminar.

University of Florida, Gainesville, Florida USA

Instructor

• Summer 2012: STA 3032 - Engineering Statistics
• Spring 2014: BCN6036 Research Methods in Construction.
• Fall 2012: STA 3032 - Engineering Statistics.

Lab instructor for STA 2023 on multiple semester

• Teaching Assistant for several Statistics and Probability Courses.