Anindya Bhadra
Mathematics · Purdue University West Lafayette
Publications
105
Citations
1,561
Est. group size
~7
Recurring co-author estimate
Active years
17
Publishing since 2010
Anindya Bhadra works in statistics, developing Bayesian methods for analyzing complex, high-dimensional data such as gene and protein networks, spatial data, and graphical models (mathematical structures that represent relationships between many variables). Much of the work focuses on building more efficient computational algorithms and flexible probability models, including connections between deep learning and traditional statistical approaches, with applications in genomics, proteomics, and tumor biology.
Publication output rose from 2017 to a peak around 2019-2020, then has gradually declined through the mid-2020s, though the researcher remains active with several 2025-2026 preprints.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- The Reverse Telescoping Coordinate System for Positive Definite Matrices: Geometry, Computation, and Generative Modeling
arXiv (Cornell University) · 2026
- The Reverse Telescoping Coordinate System for Positive Definite Matrices: Geometry, Computation, and Generative Modeling
arXiv (Cornell University) · 2026
- Robust Bayesian graphical regression models for assessing tumor heterogeneity in proteomic networks
Biometrics · 2025
- Multivariate Confluent Hypergeometric Covariance Functions with Simultaneous Flexibility over Smoothness and Tail Decay
Mathematical Geosciences · 2025
- Posterior concentration for Gaussian process priors under rescaled and hierarchical Matérn and Confluent Hypergeometric covariance functions
Electronic Journal of Statistics · 2025
- An Order of Magnitude Time Complexity Reduction for Gaussian Graphical Model Posterior Sampling Using a Reverse Telescoping Block Decomposition
arXiv (Cornell University) · 2025
- Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model
arXiv (Cornell University) · 2025
- Precision matrix estimation under the horseshoe-like prior–penalty dual
Electronic Journal of Statistics · 2024
- Merging two cultures: Deep and statistical learning
Wiley Interdisciplinary Reviews Computational Statistics · 2024
- Maximum a posteriori estimation in graphical models using local linear approximation
Stat · 2024
- Measurement error models with zero inflation and multiple sources of zeros, with applications to hard zeros
Lifetime Data Analysis · 2024
- Bayesian robust learning in chain graph models for integrative pharmacogenomics
The Annals of Applied Statistics · 2024
- Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing Constants
arXiv (Cornell University) · 2024
- Deep Kernel Posterior Learning under Infinite Variance Prior Weights
arXiv (Cornell University) · 2024
- Maximum a Posteriori Estimation in Graphical Models Using Local Linear Approximation
arXiv (Cornell University) · 2023
- arXiv (Cornell University)×33
- Current Developments in Nutrition×11
- Nutrients×6
- Journal of Nutrition×6
- American Journal of Clinical Nutrition×2
- Roger S. Zoh
Mathematics · Indiana University
- Dabao Zhang
Mathematics · Purdue University West Lafayette
- Jun Xie
Mathematics · Purdue University West Lafayette
- Dayu Sun
Mathematics · Indiana University
- Fei Xue
Mathematics · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile