Debdeep Pati

Professor, Department of Statistics, Texas A&M University

(September 1, 2022 to present)

Director of the PhD program, Department of Statistics, Texas A&M University

(September 1, 2021 to present)


debdeep@stat.tamu.edu
(979) 845-3141

Research Interests

Bayes theory and methods in high dimensions; Approximate Bayesian methods; high dimensional network analysis, Bayesian graphical models, efficient Bayesian computation, hierarchical modeling of complex shapes, point pattern data modeling, real-time tracking algorithms.

Updates

  • (May 2024) A new NSF proposal as a PI (with Anirban Bhattacharya as co-PI) on Wasserstein guided nonparametric Bayes is funded.
  • (May 2024) An article on variational inference on dynamic latent space models tentatively accepted by the Journal of Machine Learning Research.
  • (May 2024) An article on blocked Gibbs sampler for hierarchical Dirichlet process accepted at Journal of Computational and Graphical Statistics.
  • (May 2024) An article on a hybrid approach to marginal likelihood estimation accepted at Algorithms.
  • (April 2024) Article Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data won the JASA reproducibility award.
  • (April 2024) Keynote speaker at the Probability and Statistics Day 2024, University of Maryland Baltimore County.
  • (April 2024) A software-based article on covariate-dependent approach to Gaussian graphical modeling accepted at the ACM transactions on Mathematical software.
  • (March 2024) Talk at the department of Biostatistics at University of Michigan on Wasserstein guided nonparametric Bayes.
  • (March 2024) Proposal [link] for a 5 day workshop to be held at Banff on March 2025 accepted by BIRS.
  • (January 2024) Article on fair-clustering accepted at Entropy.
  • (December 2023) Virtual Talk at CFE-CMStatistics 2023 on adaptive finite element type decomposition of Gaussian random fields.
  • (December 2023) Article on distributional reweighting using optimal transport accepted at Entropy.
  • (October 2023) Talk at IMSI, University of Chicago on singular models.
  • (October 2023) Talk at University of Houston on theoretical guarantees on variational inference.
  • (September 2023) Talk at USC Marshall School of Business on theoretical guarantees on variational inference.
  • (July 2023) Article on exact tests for block models (part of Mathematical Research Communities collaboration [link]) accepted at JRSS-B.
  • (June 2023) Article on covariate-assisted graphical models accepted at JASA-T&M.
  • (June 2023) Bayes Comp 2027 happening at TAMU [link]!
  • (June 2023) Talk at Centre International de Rencontres Mathématiques, Luminy, France on adaptive finite element type decomposition of Gaussian random fields.
  • (June 2023) Talk at IISA 2023, Golden, CO on adaptive finite element type decomposition of Gaussian random fields.
  • (May 2023) A proposal on fast statistical learning of anomalous behavior on streaming data funded by National Technology & Engineering Solutions of Sandia.
  • (May 2023) Article on Gaussian processes with error in variables accepted at JMLR.
  • (April 2023) Virtual talk at Virginia Commonwealth University seminar series on robust probabilistic inference via a constrained transport metric.
  • (March 2023) Virtual talk at BayesComp 2023 on robust probabilistic inference via a constrained transport metric.
  • (January 2023) Article on monotone single index model for missing-at-random longitudinal proportion data accepted at Journal of Applied Stat.
  • (December 2022) Article on Bayesian hierarchical modeling of covariance valued data accepted at STAT.
  • (December 2022) Virtual talk at IISA 2022 on robust probabilistic inference via a constrained transport metric.
  • (September 2022) Article on mass-shifting property of truncated multivariate Gaussian distributions accepted at JASA-T&M.
  • (September 2022) A new NIH R21 (as a co-I, with Dipankar Bandyopadhyay as PI) proposal on developing risk index to evaluate the elderly with comorbidity for oral health event times is funded.
  • (August 2022) A new NIH R01 (as a co-PI/MPI, with Dipankar Bandyopadhyay as PI) proposal to understand gender influences on periodontal disease and diabetes is funded.
  • (July 2022) Co-organizing an IMSI workshop on the usage of algebraic methods in Bayesian statistics [link].
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