Anindya Bhadra

Anindya Bhadra is a Professor in the Department of Statistics at Purdue University and a University Faculty Scholar. His research focuses on Bayesian methods for high-dimensional and complex data, computational statistics, and applications in life sciences including genomics, infectious disease epidemiology, and nutrition.

Research Interests:

• Bayesian inference for graphical models and high-dimensional data
• Gaussian processes with novel covariance functions (e.g., Confluent Hypergeometric)
• Deep learning and statistical learning intersections
• Measurement error models and zero-inflated data analysis
• Spatiotemporal modeling for geostatistics

Scientific Contributions:

• Developed horseshoe+ estimator for ultra-sparse signal recovery
• Designed confluent hypergeometric covariance functions for spatial modeling
• Advanced posterior inference in infinite-width neural networks with heavy-tailed weights
• Created evidence estimation techniques for Gaussian graphical models

Scientific Awards:

• University Faculty Scholar, Purdue University
• IISA 2022 Best Poster Award (for student K. Sagar)
• ENAR Distinguished Student Paper Award 2022 (for student K. Sagar)

Editorial Roles:

• Associate Editor, Journal of the American Statistical Association (2020–2023)
• Associate Editor, Journal of Computational and Graphical Statistics (2021–present)
• Associate Editor, Statistical Analysis and Data Mining (2021–present)
• Associate Editor, Sankhya A (2018–present)

Email: bhadra@purdue.edu