Debdeep Pati

Professor, Department of Statistics, University of Wisconsin - Madison

(August 19, 2024 to present)

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

(August 2024) Moved to UW Madison as a Professor in the Department of Statistics.
(August 2024) Became an associate editor of JCGS.
(June 2024) Talk on blocked Gibbs sampler for hierarchical Dirichlet processes at ICSA 2024.
(July 2024) Virtual talk on sequential and parallel variational inference at Ecosta 2024.
(June 2024) Talk on blocked Gibbs sampler for hierarchical Dirichlet processes at ICSA 2024.
(June 2024) Virtual talk on variational inference at WNAR/IMS/Graybill meeting.
(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].