--- title: "Michael I. Jordan — author profile and papers" description: "Michael I. Jordan, Institut national de recherche en sciences et technologies du numérique: 2 papers on Elamur Research (2003–2009), h-index 159 —…" canonical: "https://research.elamur.ai/free/en/authors/michael-i-jordan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/michael-i-jordan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Michael I. Jordan # Michael I. Jordan Michael I. Jordan works on statistical machine learning, and the two papers here, from 2003 and 2009, apply probabilistic generative models to language. Both treat text as the visible output of hidden structure, either the themes running through a document collection or the alignment between words and the facts they describe, and both fit that structure without labelled examples. The more cited paper, [Latent Dirichlet Allocation](https://md.research.elamur.ai/free/en/papers/blei-2003-latent-dirichlet-allocation/) (2003), written with [David M. Blei](https://md.research.elamur.ai/free/en/authors/david-m-blei/) and [Andrew Y. Ng](https://md.research.elamur.ai/free/en/authors/andrew-y-ng/), introduces a three-level hierarchical Bayesian model of documents. Each document draws a mixture of topics from a Dirichlet prior, and each word is generated from one of those topics. The model gives compact representations of discrete data and, unlike earlier approaches, can assign probabilities to documents not seen during training. The later paper, [Learning Semantic Correspondences with Less Supervision](https://md.research.elamur.ai/free/en/papers/liang-2009-learning-semantic-correspondences-less-supervision/) (2009), with [Percy Liang](https://md.research.elamur.ai/free/en/authors/percy-liang/) and [Dan Klein](https://md.research.elamur.ai/free/en/authors/dan-klein/), turns to grounded language. Given a world state stored as typed records and an unsegmented text about it, a hierarchical semi-Markov model trained with EM learns how the text splits into utterances and which records and fields each piece describes. Jordan's current affiliations are the [University of California, Berkeley](https://md.research.elamur.ai/free/en/universities/university-of-california-berkeley/) (since 1999) and Inria in France (since 2010); an earlier one is the [Massachusetts Institute of Technology](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/). Michael I. Jordan has 2 papers in our library, in 2003–2009; often with [Andrew Y. Ng](https://md.research.elamur.ai/free/en/authors/andrew-y-ng/), [Dan Klein](https://md.research.elamur.ai/free/en/authors/dan-klein/), [David M. Blei](https://md.research.elamur.ai/free/en/authors/david-m-blei/). 2 papers in our library · 2003–2009 [OpenAlex](https://openalex.org/A5049812527) · [ORCID](https://orcid.org/0000-0001-8935-817X) · [**h-index 159**](https://openalex.org/authors/A5049812527) · [989 works](https://openalex.org/works?filter=author.id:A5049812527) · [186,968 citations](https://openalex.org/works?filter=author.id:A5049812527&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/michael-i-jordan/#papers) · [🔗 2,256 citations in our library](https://md.research.elamur.ai/free/en/authors/michael-i-jordan/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Star rank #38](https://md.research.elamur.ai/free/en/paper-stars/#star-38) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Michael+I.+Jordan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Michael+I.+Jordan) · [dblp](https://dblp.org/search?q=Michael+I.+Jordan) · [ACL Anthology](https://aclanthology.org/search/?q=Michael+I.+Jordan) ## Affiliations [🎓**University of California, Berkeley** Berkeley · United States 1999–2026 · 716 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-california-berkeley/) · [🔬**Institut national de recherche en sciences et technologies du numérique** Le Chesnay-Rocquencourt · France 2010–2026 · 42 papers*current*](https://md.research.elamur.ai/free/en/labs/institut-national-de-recherche-en-sciences-et-technologies-du-numerique/) · [🎓**University of California System** Oakland · United States 2007–2026 · 6 papers*current*](https://ror.org/00pjdza24) · [🎓**Massachusetts Institute of Technology** Cambridge · United States 1989–2023 · 99 papers](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) · [🎓**École Normale Supérieure** Bujumbura · Burundi 2024–2026 · 9 papers](https://ror.org/01dp7jr64) · [🎓**Stanford University** Stanford · United States 1992–2019 · 6 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🔬**SIERRA: Apprentissage Statistique et optimisation** Paris · France 2023–2025 · 5 papers](https://ror.org/0485z7y90) · [🎓**Berkeley College** New York · United States 2025–2026 · 4 papers](https://ror.org/02xewxa75) · [🔬**École Normale Supérieure - PSL** Paris · France 2023–2026 · 4 papers](https://md.research.elamur.ai/free/en/labs/ecole-normale-superieure-psl/) · [🎓**The University of Texas at Austin** Austin · United States 2019–2020 · 3 papers](https://md.research.elamur.ai/free/en/universities/the-university-of-texas-at-austin/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 48 more institutions on single bylines are not listed. ## Works by year ### 2000s [**2009** 1 paper](https://md.research.elamur.ai/free/en/papers/liang-2009-learning-semantic-correspondences-less-supervision/) · [**2003** 1 paper](https://md.research.elamur.ai/free/en/papers/blei-2003-latent-dirichlet-allocation/) ## Papers The most cited first (OpenAlex and our library). 1. **[Latent Dirichlet Allocation](https://md.research.elamur.ai/free/en/papers/blei-2003-latent-dirichlet-allocation/)** *(2003 · 28,297 citations)* The paper addresses how to obtain compact, statistically meaningful representations of documents and other collections of discrete data. 2. **[Learning Semantic Correspondences with Less Supervision](https://md.research.elamur.ai/free/en/papers/liang-2009-learning-semantic-correspondences-less-supervision/)** *(2009 · 455 citations)* The paper addresses grounded language acquisition with very weak supervision. The input is a world state, stored as a set of typed records, and a raw, unsegmented text that describes it. The system must work out how the text splits into utterances, which records and fields are mentioned, and how text pieces align to… ## Also in our library 1 more work of theirs is in our library without a page here yet; it will appear as we publish them. ## Co-authors here 4 co-authors with a page, the most papers together first. - [Andrew Y. Ng](https://md.research.elamur.ai/free/en/authors/andrew-y-ng/) - [Dan Klein](https://md.research.elamur.ai/free/en/authors/dan-klein/) - [David M. Blei](https://md.research.elamur.ai/free/en/authors/david-m-blei/) - [Percy Liang](https://md.research.elamur.ai/free/en/authors/percy-liang/) ## Cited by Papers of our library cite their works 2,256 times (of the 140,884 papers whose bibliographies we read); [107 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/michael-i-jordan/cited-by/).