2026 David M. Blei: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	109	230	224	129	125	332	122521

David M. Blei publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where David M. Blei sits on this spectrum.

32 publications 991+

This scientist: 332 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

David M. Blei D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where David M. Blei sits on this spectrum.

30 D-Index 131+

This scientist: 109 D-Index — 98th percentile

98% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

2017 - Fellow of John Simon Guggenheim Memorial Foundation
2015 - ACM Fellow For contributions to the theory and practice of probabilistic topic modeling and Bayesian machine learning.
2013 - ACM Prize in Computing For pioneering the area of topic modeling, which has had profound influence on machine learning foundations as well as industrial practice.
2010 - Fellow of Alfred P. Sloan Foundation

Overview

David M. Blei is affiliated with Columbia University in the United States. Their research spans primarily the field of computer science, with a strong focus on artificial intelligence and statistics and probability. Their work also intersects with molecular biology, economics and econometrics, and immunology.

The main topics covered by their research include:

Statistical Methods and Inference
Advanced Causal Inference Techniques
Bayesian Modeling and Causal Inference
Topic Modeling
Gaussian Processes and Bayesian Inference
Bayesian Methods and Mixture Models
Computational and Text Analysis Methods

David M. Blei has contributed extensively to multiple venues, with frequent publications in:

arXiv (Cornell University)
The Annals of Applied Statistics
bioRxiv (Cold Spring Harbor Laboratory)
Journal of Biomedical Informatics
Transactions of the Association for Computational Linguistics

Their recent papers include:

"Variational Inference: A Review for Statisticians" (2023), published in OPAL (Open@LaTrobe) at La Trobe University
"Starfysh integrates spatial transcriptomic and histologic data to reveal heterogeneous tumor-immune hubs" (2024), published in Nature Biotechnology
"Adjusting for indirectly measured confounding using large-scale propensity score" (2022), published in Journal of Biomedical Informatics
"SHOPPER: A probabilistic model of consumer choice with substitutes and complements" (2020), published in The Annals of Applied Statistics
"Counterfactual inference for consumer choice across many product categories" (2021), published in Quantitative Marketing and Economics

The scientist has frequently collaborated with several notable co-authors, including:

Achille Nazaret
Zhaoran Wang
John P. Cunningham
Claudia Shi
Keyon Vafa

David M. Blei's recognition includes being named an ACM Fellow in 2015 for contributions to probabilistic topic modeling and Bayesian machine learning. In 2013, they received the ACM Prize in Computing for pioneering work in topic modeling, influencing machine learning both theoretically and practically.

Additional honors include being a Fellow of the John Simon Guggenheim Memorial Foundation in 2017 and a Fellow of the Alfred P. Sloan Foundation in 2010. These awards reflect engagement with foundational aspects of machine learning, probabilistic modeling, and applied statistics.

Best Publications

Latent dirichlet allocation

David M. Blei;Andrew Y. Ng;Michael I. Jordan

44013
Citations
Variational Inference: A Review for Statisticians

David M. Blei;Alp Kucukelbir;Jon D. McAuliffe

5212
Citations
Probabilistic topic models

David M. Blei

5125
Citations
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes

Yee W. Teh;Michael I. Jordan;Matthew J. Beal;David M. Blei

4473
Citations
Dynamic topic models

David M. Blei;John D. Lafferty

3500
Citations
Reading Tea Leaves: How Humans Interpret Topic Models

Jonathan Chang;Sean Gerrish;Chong Wang;Jordan L. Boyd-graber

2782
Citations
Mixed Membership Stochastic Blockmodels

Edoardo M. Airoldi;David M. Blei;Stephen E. Fienberg;Eric P. Xing

2491
Citations
Stochastic variational inference

Matthew D. Hoffman;David M. Blei;Chong Wang;John Paisley

2241
Citations
A correlated topic model of Science

David M. Blei;John D. Lafferty

2168
Citations
Matching words and pictures

Kobus Barnard;Pinar Duygulu;David Forsyth;Nando de Freitas

2078
Citations
Online Learning for Latent Dirichlet Allocation

Matthew Hoffman;Francis R. Bach;David M. Blei

2006
Citations
Collaborative topic modeling for recommending scientific articles

Chong Wang;David M. Blei

1982
Citations
Variational Inference for Dirichlet Process Mixtures

David M. Blei;Michael I. Jordan

1877
Citations
Supervised Topic Models

David M. Blei;Jon D. Mcauliffe

1858
Citations
Correlated Topic Models

John D. Lafferty;David M. Blei

1556
Citations
Modeling annotated data

David M. Blei;Michael I. Jordan

1544
Citations
Hierarchical Topic Models and the Nested Chinese Restaurant Process

Thomas L. Griffiths;Michael I. Jordan;Joshua B. Tenenbaum;David M. Blei

1433
Citations
Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of U.S. government arts funding

Paul DiMaggio;Manish Nag;David Blei

1121
Citations
Black Box Variational Inference

Rajesh Ranganath;Sean Gerrish;David M. Blei

984
Citations
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies

David M. Blei;Thomas L. Griffiths;Michael I. Jordan

894
Citations

Frequent Co-Authors

Rajesh Ranganath New York University

Edoardo M. Airoldi Temple University

Stephen E. Fienberg Carnegie Mellon University

Dustin Tran Google (United States)

Michael I. Jordan University of California, Berkeley

John Paisley Columbia University

Matthew D. Hoffman Google (United States)

Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence

Jordan Boyd-Graber University of Maryland, College Park

Samuel J. Gershman Harvard University

External Links

Wikipedia of David M. Blei Google Scholar page

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