David Meir Blei (also referred to as David M. Blei or David Blei) is an American computer scientist whose research primarily focuses on artificial intelligence, machine learning, and Bayesian statistics. While French Wikipedia states that he teaches as an associate professor in the Department of Computer Science at Princeton University, English, German, and Tamil sources record that he was an associate professor at Princeton prior to fall 2014 and is currently a professor in the Statistics and Computer Science departments at Columbia University, where Korean sources also identify him as a computer scientist.

Blei studied at Brown University, graduating with a Bachelor of Science degree in 1997, and received his doctorate in computer science in 2004 from the University of California, Berkeley under Michael I. Jordan with the dissertation "Probabilistic Models of Text and Images" (cataloged at http://oskicat.berkeley.edu/record=b15238730~S1).^[3] Following the completion of his Ph.D., he worked as a postdoctoral researcher under John Lafferty in the Machine Learning Department at Carnegie Mellon University until 2006, after which he became an assistant professor in 2006 and an associate professor in 2011 at Princeton University before being appointed a professor at Columbia University in 2014.

Blei founded the research field of topic modeling, establishing algorithms within the framework of probabilistic modeling that capture the thematic structure of large document collections. This framework enables the analysis, organization, and thematic summarization of digital archives with scalability to billions of documents, spanning use cases such as email archives, image archives, natural language processing, social networks, robotics, computational biology, and the social sciences and humanities. In 2003, together with Michael I. Jordan (Michael Irwin Jordan) and Andrew Ng, he introduced Latent Dirichlet Allocation (LDA), the simplest topic model.

In 2011, Blei received the Presidential Early Career Award for Scientists and Engineers (PECASE). In 2013, he was awarded the ACM Prize in Computing (ACM Infosys Award) for his contributions to the theory and practice of probabilistic modeling and Bayesian machine learning. He was elected an ACM Fellow (Fellow of the Association for Computing Machinery) in 2015, became a Guggenheim Fellow in 2017, and was awarded the ACM-AAAI Allen Newell Award for 2023. His academic homepage is hosted at Columbia University (https://www.cs.columbia.edu/~blei/).

His research interests include topic models, and he was one of the original developers of latent Dirichlet allocation, along with Andrew Ng and Michael I. Jordan. As of June 18, 2020, his publications have been cited 109,821 times, giving him an h-index reported as 116 in English Wikipedia and 97 in Tamil Wikipedia.^[1]

In 2013, Blei received the Association for Computing Machinery (ACM) Infosys Foundation Award. This award is given to a computer scientist under the age of 45 and has since been renamed the ACM Prize in Computing (Association for Computing Machinery Prize in Computing).^[2] In 2015, he was named a Fellow of the Association for Computing Machinery (ACM) "for contributions to the theory and practice of probabilistic topic modeling and Bayesian machine learning".^[2]

External links include his homepage and a directory of publications. Additional resources include a PDF on Latent Dirichlet Allocation and material regarding the 2013 ACM-Infosys Foundation Award.