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Nilabja Guha


Nilabja Guha
Nilabja GuhaAssistant Professor

Research Interests

Bayesian Modeling, Inverse Problem, Uncertainty Quantification, Graphical Models, Scalable Modeling in High-Dimensional Data, Stochastic Approximation, Random Measure, Small area Model, Deconvolution, Posterior Consistency, Risk Assessment, Shape Restricted Regression

Education

  • Ph D: Statistics, (2014), University of Maryland Baltimore County - Baltimore, MD
    Dissertation/Thesis Title: Bayesian Estimation Under Shape Restriction and Some Deconvolution Problems
  • MS: Statistics , (2008), Indian Statistical Institute - Kolkata, India
    Supporting Area: Mathematical Statistics & Probability
  • BS: Statistics, (2006), Indian Statistical Institute - Kolkata, India

Selected Publications

  • Guha, N., Baladandayuthapani, V., Mallick, B.K. (2020). Quantile Graphical Models: Bayesian Approaches. Journal of Machine Learning Research, to appear.
  • Payne, R.D., Guha, N., Ding, Y., Mallick, B.K. (2019). A conditional density estimation partition model using logistic Gaussian processes. Biometrika.
  • Das, N., Ghosh, R.P., Guha, N., Bhattacharya, R., Mallick, B. (2019). Optimal Transport Based Tracking of Space Objects in Cylindrical Manifolds. The Journal of the Astronautical Sciences, 66(4) 582-606.
  • Cheung, S.W., Guha, N. (2019). Dynamic data-driven Bayesian GMsFEM. Journal of Computational and Applied Mathematics, 353 72-85.
  • Yang, K., Guha, N., Efendiev, Y., Mallick, B.K. (2017). Bayesian and variational Bayesian approaches for flows in heterogeneous random media. Journal of Computational Physics, 345 275–293.
  • Efendiev, Y., Leung, W.T., Cheung, S.W., Hoang, V.H., Mallick, B., Guha, N. (2017). Bayesian Multiscale Finite Element Methods. Modeling missing subgrid information probabilistically. International Journal for Multiscale Computational Engineering.
  • Guha, N., Tan, X. (2017). Multilevel approximate Bayesian approaches for flows in highly heterogeneous porous media and their applications. Journal of Computational and Applied Mathematics, 700.
  • Guha, N., Roy, A., Malinovsky, Y., Datta, G. (2016). An optimal shrinkage factor in prediction of ordered random effects. Statistica Sinica, 26(4) 1709.
  • Mallick, B.K., Yang, K., Guha, N., Efendiev, Y. (2016). Comment on article by Chkrebtii, Campbell, Calderhead, and Girolami [MR3577378]. Bayesian Analysis, 11(4) 1279.
  • Guha, N., Wu, X., Efendiev, Y., Jin, B., Mallick, B.K. (2015). A variational Bayesian approach for inverse problems with skew-t error distributions. Journal of Computational Physics, 377.
  • Guha, N. (2014). Bayesian Estimation Under Shape Restriction and Some Deconvolution Problems. ProQuest LLC, Ann Arbor, MI
  • Guha, N., Roy, I., Roy, A. (2013). Bayesian estimation of Huff curves. Electronic Journal of Statistics, 7 2794.
  • Guha, N., Roy, A., Kopylev, L., Fox, J., Spassova, M., White, P. (2013). Nonparametric Bayesian Methods for Benchmark Dose Estimation. Risk Analysis, (9) 1608.

Selected Presentations

  • Quantile Graphical Model: An Approximate Bayesian Approach - Joint Statistical Meeting, 2015 - Seattle
  • On the Estimation of Order Statistics Under Measurement Error - JPSM Conference, 2014 - College Park, MD
  • On the Estimation of Order Statistics Under Measurement Error - Indian International Statistical Organization Annual conference, 2013 - Chennai, India
  • On the Estimation of Order Statistics Under Measurement Error - 2012 Joint Statistical Meetings, 2012 - San Diego
  • Bayesian Estimation of Huff Curves - Annual probability and Statistics Day: UMBC, 2011